WorldWideScience

Sample records for hierarchical multiagent reinforcement

  1. Hierarchical Multiagent Reinforcement Learning

    Science.gov (United States)

    2004-01-25

    In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multiagent tasks. We...introduce a hierarchical multiagent reinforcement learning (RL) framework and propose a hierarchical multiagent RL algorithm called Cooperative HRL. In

  2. Intelligent multiagent coordination based on reinforcement hierarchical neuro-fuzzy models.

    Science.gov (United States)

    Mendoza, Leonardo Forero; Vellasco, Marley; Figueiredo, Karla

    2014-12-01

    This paper presents the research and development of two hybrid neuro-fuzzy models for the hierarchical coordination of multiple intelligent agents. The main objective of the models is to have multiple agents interact intelligently with each other in complex systems. We developed two new models of coordination for intelligent multiagent systems, which integrates the Reinforcement Learning Hierarchical Neuro-Fuzzy model with two proposed coordination mechanisms: the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with a market-driven coordination mechanism (MA-RL-HNFP-MD) and the MultiAgent Reinforcement Learning Hierarchical Neuro-Fuzzy with graph coordination (MA-RL-HNFP-CG). In order to evaluate the proposed models and verify the contribution of the proposed coordination mechanisms, two multiagent benchmark applications were developed: the pursuit game and the robot soccer simulation. The results obtained demonstrated that the proposed coordination mechanisms greatly improve the performance of the multiagent system when compared with other strategies.

  3. Multi-Agent Reinforcement Learning Algorithm Based on Action Prediction

    Institute of Scientific and Technical Information of China (English)

    TONG Liang; LU Ji-lian

    2006-01-01

    Multi-agent reinforcement learning algorithms are studied. A prediction-based multi-agent reinforcement learning algorithm is presented for multi-robot cooperation task. The multi-robot cooperation experiment based on multi-agent inverted pendulum is made to test the efficency of the new algorithm, and the experiment results show that the new algorithm can achieve the cooperation strategy much faster than the primitive multiagent reinforcement learning algorithm.

  4. Multi-Agent Reinforcement Learning and Adaptive Neural Networks.

    Science.gov (United States)

    2007-11-02

    learning method. The objective was to study the utility of reinforcement learning as an approach to complex decentralized control problems. The major...accomplishment was a detailed study of multi-agent reinforcement learning applied to a large-scale decentralized stochastic control problem. This study...included a very successful demonstration that a multi-agent reinforcement learning system using neural networks could learn high-performance

  5. Optimal control in microgrid using multi-agent reinforcement learning.

    Science.gov (United States)

    Li, Fu-Dong; Wu, Min; He, Yong; Chen, Xin

    2012-11-01

    This paper presents an improved reinforcement learning method to minimize electricity costs on the premise of satisfying the power balance and generation limit of units in a microgrid with grid-connected mode. Firstly, the microgrid control requirements are analyzed and the objective function of optimal control for microgrid is proposed. Then, a state variable "Average Electricity Price Trend" which is used to express the most possible transitions of the system is developed so as to reduce the complexity and randomicity of the microgrid, and a multi-agent architecture including agents, state variables, action variables and reward function is formulated. Furthermore, dynamic hierarchical reinforcement learning, based on change rate of key state variable, is established to carry out optimal policy exploration. The analysis shows that the proposed method is beneficial to handle the problem of "curse of dimensionality" and speed up learning in the unknown large-scale world. Finally, the simulation results under JADE (Java Agent Development Framework) demonstrate the validity of the presented method in optimal control for a microgrid with grid-connected mode.

  6. A Comprehensive Survey of Multiagent Reinforcement Learning

    NARCIS (Netherlands)

    Busoniu, L.; Babuska, R.; De Schutter, B.

    2008-01-01

    Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity ofmany tasks arising in these domains makes them difficult to solve with preprogrammed agent behaviors. The agents must, instead, di

  7. Traffic Light Control by Multiagent Reinforcement Learning Systems

    NARCIS (Netherlands)

    Bakker, B.; Whiteson, S.; Kester, L.J.H.M.; Groen, F.C.A.

    2010-01-01

    Traffic light control is one of the main means of controlling road traffic. Improving traffic control is important because it can lead to higher traffic throughput and reduced traffic congestion. This chapter describes multiagent reinforcement learning techniques for automatic optimization of

  8. A new accelerating algorithm for multi-agent reinforcement learning

    Institute of Scientific and Technical Information of China (English)

    ZHANG Ru-bo; ZHONG Yu; GU Guo-chang

    2005-01-01

    In multi-agent systems, joint-action must be employed to achieve cooperation because the evaluation of the behavior of an agent often depends on the other agents' behaviors. However, joint-action reinforcement learning algorithms suffer the slow convergence rate because of the enormous learning space produced by jointaction. In this article, a prediction-based reinforcement learning algorithm is presented for multi-agent cooperation tasks, which demands all agents to learn predicting the probabilities of actions that other agents may execute. A multi-robot cooperation experiment is run to test the efficacy of the new algorithm, and the experiment results show that the new algorithm can achieve the cooperation policy much faster than the primitive reinforcement learning algorithm.

  9. A neural signature of hierarchical reinforcement learning.

    Science.gov (United States)

    Ribas-Fernandes, José J F; Solway, Alec; Diuk, Carlos; McGuire, Joseph T; Barto, Andrew G; Niv, Yael; Botvinick, Matthew M

    2011-07-28

    Human behavior displays hierarchical structure: simple actions cohere into subtask sequences, which work together to accomplish overall task goals. Although the neural substrates of such hierarchy have been the target of increasing research, they remain poorly understood. We propose that the computations supporting hierarchical behavior may relate to those in hierarchical reinforcement learning (HRL), a machine-learning framework that extends reinforcement-learning mechanisms into hierarchical domains. To test this, we leveraged a distinctive prediction arising from HRL. In ordinary reinforcement learning, reward prediction errors are computed when there is an unanticipated change in the prospects for accomplishing overall task goals. HRL entails that prediction errors should also occur in relation to task subgoals. In three neuroimaging studies we observed neural responses consistent with such subgoal-related reward prediction errors, within structures previously implicated in reinforcement learning. The results reported support the relevance of HRL to the neural processes underlying hierarchical behavior.

  10. Multiagent reinforcement learning through merging individually learned value functions

    Institute of Scientific and Technical Information of China (English)

    ZHANG Hua-xiang; HUANG Shang-teng

    2005-01-01

    In cooperative multiagent systems, to learn the optimal policies of multiagents is very difficult. As the numbers of states and actions increase exponentially with the number of agents, their action policies become more intractable. By learning these value functions, an agent can learn its optimal action policies for a task. If a task can be decomposed into several subtasks and the agents have learned the optimal value functions for each subtask, this knowledge can be helpful for the agents in learning the optimal action policies for the whole task when they are acting simultaneously. When merging the agents' independently learned optimal value functions,a novel multiagent online reinforcement learning algorithm LU-Q is proposed. By applying a transformation to the individually learned value functions, the constraints on the optimal value functions of each subtask are loosened. In each learning iteration process in algorithm LU-Q, the agents ' joint action set in a state is processed. Some actions of that state are pruned from the available action set according to the defined multiagent value function in LU-Q. As the items of the available action set of each state are reduced gradually in the iteration process of LU-Q, the convergence of the value functions is accelerated. LU-Q's effectiveness, soundness and convergence are analyzed, and the experimental results show that the learning performance of LU-Q is better than the performance of standard Q learning.

  11. Hierarchical cooperative control for multiagent systems with switching directed topologies.

    Science.gov (United States)

    Hu, Jianqiang; Cao, Jinde

    2015-10-01

    The hierarchical cooperative control problem is concerned for a two-layer networked multiagent system under switching directed topologies. The group cooperative objective is to achieve finite-time formation control for the upper layer of leaders and containment control for the lower layer of followers. Two kinds of cooperative strategies, including centralized-distributed control and distributed-distributed control, are proposed for two types of switching laws: 1) random switching law with the dwell time and 2) Markov switching law with stationary distribution. Utilizing the state transition matrix methods and matrix measure techniques, some sufficient conditions are derived for asymptotical containment control and exponential almost sure containment control, respectively. Finally, some numerical examples are provided to demonstrate the effectiveness of the proposed control schemes.

  12. Multiagent cooperation and competition with deep reinforcement learning

    Science.gov (United States)

    Kodelja, Dorian; Kuzovkin, Ilya; Korjus, Kristjan; Aru, Juhan; Aru, Jaan; Vicente, Raul

    2017-01-01

    Evolution of cooperation and competition can appear when multiple adaptive agents share a biological, social, or technological niche. In the present work we study how cooperation and competition emerge between autonomous agents that learn by reinforcement while using only their raw visual input as the state representation. In particular, we extend the Deep Q-Learning framework to multiagent environments to investigate the interaction between two learning agents in the well-known video game Pong. By manipulating the classical rewarding scheme of Pong we show how competitive and collaborative behaviors emerge. We also describe the progression from competitive to collaborative behavior when the incentive to cooperate is increased. Finally we show how learning by playing against another adaptive agent, instead of against a hard-wired algorithm, results in more robust strategies. The present work shows that Deep Q-Networks can become a useful tool for studying decentralized learning of multiagent systems coping with high-dimensional environments. PMID:28380078

  13. Emotional Multiagent Reinforcement Learning in Spatial Social Dilemmas.

    Science.gov (United States)

    Yu, Chao; Zhang, Minjie; Ren, Fenghui; Tan, Guozhen

    2015-12-01

    Social dilemmas have attracted extensive interest in the research of multiagent systems in order to study the emergence of cooperative behaviors among selfish agents. Understanding how agents can achieve cooperation in social dilemmas through learning from local experience is a critical problem that has motivated researchers for decades. This paper investigates the possibility of exploiting emotions in agent learning in order to facilitate the emergence of cooperation in social dilemmas. In particular, the spatial version of social dilemmas is considered to study the impact of local interactions on the emergence of cooperation in the whole system. A double-layered emotional multiagent reinforcement learning framework is proposed to endow agents with internal cognitive and emotional capabilities that can drive these agents to learn cooperative behaviors. Experimental results reveal that various network topologies and agent heterogeneities have significant impacts on agent learning behaviors in the proposed framework, and under certain circumstances, high levels of cooperation can be achieved among the agents.

  14. Multiagent cooperation and competition with deep reinforcement learning.

    Science.gov (United States)

    Tampuu, Ardi; Matiisen, Tambet; Kodelja, Dorian; Kuzovkin, Ilya; Korjus, Kristjan; Aru, Juhan; Aru, Jaan; Vicente, Raul

    2017-01-01

    Evolution of cooperation and competition can appear when multiple adaptive agents share a biological, social, or technological niche. In the present work we study how cooperation and competition emerge between autonomous agents that learn by reinforcement while using only their raw visual input as the state representation. In particular, we extend the Deep Q-Learning framework to multiagent environments to investigate the interaction between two learning agents in the well-known video game Pong. By manipulating the classical rewarding scheme of Pong we show how competitive and collaborative behaviors emerge. We also describe the progression from competitive to collaborative behavior when the incentive to cooperate is increased. Finally we show how learning by playing against another adaptive agent, instead of against a hard-wired algorithm, results in more robust strategies. The present work shows that Deep Q-Networks can become a useful tool for studying decentralized learning of multiagent systems coping with high-dimensional environments.

  15. Hierarchical Distributed Control Design for Multi-agent Systems Using Approximate Simulation

    Institute of Scientific and Technical Information of China (English)

    TANG Yu-Tao; HONG Yi-Guang

    2013-01-01

    In this paper,we consider a hierarchical control design for multi-agent systems based on approximate simulation.To reduce complexity,we first construct a simple abstract system to guide the agents,then we discuss the simulation relations between the abstract system and multiple agents.With the help of this abstract system,distributed hierarchical control is proposed to complete a coordination task.By virtue of a common Lyapunov function,we analyze the collective behaviors with switching multi-agent topology in light of simulation functions.

  16. Priority-Based Hierarchical Operational Management for Multiagent-Based Microgrids

    Directory of Open Access Journals (Sweden)

    Takumi Kato

    2014-03-01

    Full Text Available Electricity consumption in the world is constantly increasing, making our lives become more and more dependent on electricity. There are several new paradigms proposed in the field of power grids. In Japan, especially after the Great East Japan Earthquake in March 2011, the new power grid paradigms are expected to be more resilient to survive several difficulties during disasters. In this paper, we focus on microgrids and propose priority-based hierarchical operational management for multiagent-based microgrids. The proposed management is a new multiagent-based load shedding scheme and multiagent-based hierarchical architecture to realize such resilient microgrids. We developed a prototype system and performed an evaluation of the proposed management using the developed system. The result of the evaluation shows the effectiveness of our proposal in power shortage situations, such as disasters.

  17. Multi-agent reinforcement learning with cooperation based on eligibility traces

    Institute of Scientific and Technical Information of China (English)

    杨玉君; 程君实; 陈佳品

    2004-01-01

    The application of reinforcement learning is widely used by multi-agent systems in recent years. An agent uses a multi-agent system to cooperate with other agents to accomplish the given task, and one agent's be-havior usually affects the others' behaviors. In traditional reinforcement learning, one agent takes the others lo-cation, so it is difficult to consider the others' behavior, which decreases the learning efficiency. This paper proposes multi-agent reinforcement learning with cooperation based on eligibility traces, i.e. one agent esti-mates the other agent's behavior with the other agent's eligibility traces. The results of this simulation prove the validity of the proposed learning method.

  18. APPLICATION OF HIERARCHICAL REINFORCEMENT LEARNING IN ENGINEERING DOMAIN

    Institute of Scientific and Technical Information of China (English)

    WEI LI; Qingtai YE; Changming ZHU

    2005-01-01

    The slow convergence rate of reinforcement learning algorithms limits their wider application.In engineering domains, hierarchical reinforcement learning is developed to perform actions temporally according to prior knowledge. This system can converge fast due to reduced state space.There is a test of elevator group control to show the power of the new system. Two conventional group control algorithms are adopted as prior knowledge. Performance indicates that hierarchical reinforcement learning can reduce the learning time dramatically.

  19. Multiagent reinforcement learning for urban traffic control using coordination graphs

    NARCIS (Netherlands)

    Kuyer, L.; Whiteson, S.; Bakker, B.; Vlassis, N.

    2008-01-01

    Since traffic jams are ubiquitous in the modern world, optimizing the behavior of traffic lights for efficient traffic flow is a critically important goal. Though most current traffic lights use simple heuristic protocols, more efficient controllers can be discovered automatically via multiagent rei

  20. Multi-agent reinforcement learning based on policies of global objective

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    In general-sum games, taking all agent's collective rationality into account, we define agents' global objective,and propose a novel multi-agent reinforcement learning(RL) algorithm based on global policy. In each learning step, all agents commit to select the global policy to achieve the global goal. We prove this learning algorithm converges given certain restrictions on stage games of learned Q values, and show that it has quite lower computation time complexity than already developed multi-agent learning algorithms for general-sum games. An example is analyzed to show the algorithm' s merits.

  1. Adaptive Design of Role Differentiation by Division of Reward Function in Multi-Agent Reinforcement Learning

    Science.gov (United States)

    Taniguchi, Tadahiro; Tabuchi, Kazuma; Sawaragi, Tetsuo

    There are several problems which discourage an organization from achieving tasks, e.g., partial observation, credit assignment, and concurrent learning in multi-agent reinforcement learning. In many conventional approaches, each agent estimates hidden states, e.g., sensor inputs, positions, and policies of other agents, and reduces the uncertainty in the partially-observable Markov decision process (POMDP), which partially solve the multiagent reinforcement learning problem. In contrast, people reduce uncertainty in human organizations in the real world by autonomously dividing the roles played by individual agents. In a framework of reinforcement learning, roles are mainly represented by goals for individual agents. This paper presents a method for generating internal rewards from manager agents to worker agents. It also explicitly divides the roles, which enables a POMDP task for each agent to be transformed into a simple MDP task under certain conditions. Several situational experiments are also described and the validity of the proposed method is evaluated.

  2. Robust central pattern generators for embodied hierarchical reinforcement learning

    NARCIS (Netherlands)

    Snel, M.; Whiteson, S.; Kuniyoshi, Y.

    2011-01-01

    Hierarchical organization of behavior and learning is widespread in animals and robots, among others to facilitate dealing with multiple tasks. In hierarchical reinforcement learning, agents usually have to learn to recombine or modulate low-level behaviors when facing a new task, which costs time t

  3. Fast Conflict Resolution Based on Reinforcement Learning in Multi-agent System

    Institute of Scientific and Technical Information of China (English)

    PIAOSonghao; HONGBingrong; CHUHaitao

    2004-01-01

    In multi-agent system where each agen thas a different goal (even the team of agents has the same goal), agents must be able to resolve conflicts arising in the process of achieving their goal. Many researchers presented methods for conflict resolution, e.g., Reinforcement learning (RL), but the conventional RL requires a large computation cost because every agent must learn, at the same time the overlap of actions selected by each agent results in local conflict. Therefore in this paper, we propose a novel method to solve these problems. In order to deal with the conflict within the multi-agent system, the concept of potential field function based Action selection priority level (ASPL) is brought forward. In this method, all kinds of environment factor that may have influence on the priority are effectively computed with the potential field function. So the priority to access the local resource can be decided rapidly. By avoiding the complex coordination mechanism used in general multi-agent system, the conflict in multi-agent system is settled more efficiently. Our system consists of RL with ASPL module and generalized rules module. Using ASPL, RL module chooses a proper cooperative behavior, and generalized rule module can accelerate the learning process. By applying the proposed method to Robot Soccer, the learning process can be accelerated. The results of simulation and real experiments indicate the effectiveness of the method.

  4. The Study of Reinforcement Learning for Traffic Self-Adaptive Control under Multiagent Markov Game Environment

    Directory of Open Access Journals (Sweden)

    Lun-Hui Xu

    2013-01-01

    Full Text Available Urban traffic self-adaptive control problem is dynamic and uncertain, so the states of traffic environment are hard to be observed. Efficient agent which controls a single intersection can be discovered automatically via multiagent reinforcement learning. However, in the majority of the previous works on this approach, each agent needed perfect observed information when interacting with the environment and learned individually with less efficient coordination. This study casts traffic self-adaptive control as a multiagent Markov game problem. The design employs traffic signal control agent (TSCA for each signalized intersection that coordinates with neighboring TSCAs. A mathematical model for TSCAs’ interaction is built based on nonzero-sum markov game which has been applied to let TSCAs learn how to cooperate. A multiagent Markov game reinforcement learning approach is constructed on the basis of single-agent Q-learning. This method lets each TSCA learn to update its Q-values under the joint actions and imperfect information. The convergence of the proposed algorithm is analyzed theoretically. The simulation results show that the proposed method is convergent and effective in realistic traffic self-adaptive control setting.

  5. 基于强化学习的多Agent系统%The Multi-Agent System Based on Reinforcement Learning

    Institute of Scientific and Technical Information of China (English)

    唐文彬; 朱淼良

    2003-01-01

    Reinforcement learning allows agent that has no knowledge of an environment to cooperate more efficacious each other. This paper presents an approach for developing multi-agent reinforcement learning systems based on equation principle. The experiment shows agent can produces the desired behavior under all kinds of situation.

  6. Tree-Based Hierarchical Reinforcement Learning

    Science.gov (United States)

    2002-08-01

    algorithms for Reinforce- ment Learning and Semi-Markov Decision Problem solving ( Puterman , 1994; Sutton and Barto, 1998). This chapter formally describes...learn a policy. A policy is a method of controlling an agent in an environment, see Puterman (1994) for a complete taxonomy. In this thesis we...to work with and so we refer to the interested reader to Puterman (1994) and instead use the next approximation. The reformulation we use is known as

  7. Multi-agent machine learning a reinforcement approach

    CERN Document Server

    Schwartz, H M

    2014-01-01

    The book begins with a chapter on traditional methods of supervised learning, covering recursive least squares learning, mean square error methods, and stochastic approximation. Chapter 2 covers single agent reinforcement learning. Topics include learning value functions, Markov games, and TD learning with eligibility traces. Chapter 3 discusses two player games including two player matrix games with both pure and mixed strategies. Numerous algorithms and examples are presented. Chapter 4 covers learning in multi-player games, stochastic games, and Markov games, focusing on learning multi-pla

  8. Hierarchical adaptation scheme for multiagent data fusion and resource management in situation analysis

    Science.gov (United States)

    Benaskeur, Abder R.; Roy, Jean

    2001-08-01

    Sensor Management (SM) has to do with how to best manage, coordinate and organize the use of sensing resources in a manner that synergistically improves the process of data fusion. Based on the contextual information, SM develops options for collecting further information, allocates and directs the sensors towards the achievement of the mission goals and/or tunes the parameters for the realtime improvement of the effectiveness of the sensing process. Conscious of the important role that SM has to play in modern data fusion systems, we are currently studying advanced SM Concepts that would help increase the survivability of the current Halifax and Iroquois Class ships, as well as their possible future upgrades. For this purpose, a hierarchical scheme has been proposed for data fusion and resource management adaptation, based on the control theory and within the process refinement paradigm of the JDL data fusion model, and taking into account the multi-agent model put forward by the SASS Group for the situation analysis process. The novelty of this work lies in the unified framework that has been defined for tackling the adaptation of both the fusion process and the sensor/weapon management.

  9. IMPLEMENTATION OF MULTIAGENT REINFORCEMENT LEARNING MECHANISM FOR OPTIMAL ISLANDING OPERATION OF DISTRIBUTION NETWORK

    DEFF Research Database (Denmark)

    Saleem, Arshad; Lind, Morten

    2008-01-01

    among electric power utilities to utilize modern information and communication technologies (ICT) in order to improve the automation of the distribution system. In this paper we present our work for the implementation of a dynamic multi-agent based distributed reinforcement learning mechanism......The Electric Power system of Denmark exhibits some unique characteristics. An increasing part of the electricity is produced by local generators called distributed generators DGs. Most of these DGs are connected to network through the distribution system. This situation has created an incentive...... for the islanding operation of the distribution system. Purpose of this system is to dynamically divide the distribution network in different sections (islands), in a fault scenario when they are separated from main utility system, and make them survive on local DGs....

  10. $QD$-Learning: A Collaborative Distributed Strategy for Multi-Agent Reinforcement Learning Through Consensus + Innovations

    CERN Document Server

    Kar, Soummya; Poor, H Vincent

    2012-01-01

    The paper considers a class of multi-agent Markov decision processes (MDPs), in which the network agents respond differently (as manifested by the instantaneous one-stage random costs) to a global controlled state and the control actions of a remote controller. The paper investigates a distributed reinforcement learning setup with no prior information on the global state transition and local agent cost statistics. Specifically, with the agents' objective consisting of minimizing a network-averaged infinite horizon discounted cost, the paper proposes a distributed version of $Q$-learning, $\\mathcal{QD}$-learning, in which the network agents collaborate by means of local processing and mutual information exchange over a sparse (possibly stochastic) communication network to achieve the network goal. Under the assumption that each agent is only aware of its local online cost data and the inter-agent communication network is \\emph{weakly} connected, the proposed distributed scheme is almost surely (a.s.) shown to ...

  11. Urban Traffic Control Using Adjusted Reinforcement Learning in a Multi-agent System

    Directory of Open Access Journals (Sweden)

    Mahshid Helali Moghadam

    2013-09-01

    Full Text Available Dynamism, continuous changes of states and the necessity to respond quickly are the specific characteristics of the environment in a traffic control system. Proposing an appropriate and flexible strategy to meet the existing requirements is always an important issue in traffic control. This study presents an adaptive approach to control urban traffic using multi-agent systems and a reinforcement learning augmented by an adjusting pre-learning stage. In this approach, the agent primarily uses some statistical traffic data and then uses traffic engineering theories for computing appropriate values of the traffic parameters. Having these primary values, the agents start the reinforcement learning based on the basic calculated information. The proposed approach, at first finds the approximate optimal zone for traffic parameters based on traffic engineering theories. Then using an appropriate reinforcement learning, it tries to exploit the best point according to different conditions. This approach was implemented on a network in traffic simulator software. The network was composed of six four phased intersections and 17 two lane streets. In the simulation, pedestrians were not considered in the system. The load of the network is defined in terms of Origin-Destination matrices whose entries represent the number of trips from an origin to a destination as a function of time. The simulation ran for five hours and an average traffic volume was used. According to the simulation results, the proposed approach behaved adaptively in different conditions and had better performance than the theory-based fixed-time control.

  12. MODEM: a multi-agent hierarchical structure to model the human motor control system.

    Science.gov (United States)

    Emadi Andani, Mehran; Bahrami, Fariba; Jabehdar Maralani, Parviz; Ijspeert, Auke Jan

    2009-12-01

    In this study, based on behavioral and neurophysiological facts, a new hierarchical multi-agent architecture is proposed to model the human motor control system. Performance of the proposed structure is investigated by simulating the control of sit to stand movement. To develop the model, concepts of mixture of experts, modular structure, and some aspects of equilibrium point hypothesis were brought together. We have called this architecture MODularized Experts Model (MODEM). Human motor system is modeled at the joint torque level and the role of the muscles has been embedded in the function of the joint compliance characteristics. The input to the motor system, i.e., the central command, is the reciprocal command. At the lower level, there are several experts to generate the central command to control the task according to the details of the movement. The number of experts depends on the task to be performed. At the higher level, a "gate selector" block selects the suitable subordinate expert considering the context of the task. Each expert consists of a main controller and a predictor as well as several auxiliary modules. The main controller of an expert learns to control the performance of a given task by generating appropriate central commands under given conditions and/or constraints. The auxiliary modules of this expert learn to scrutinize the generated central command by the main controller. Auxiliary modules increase their intervention to correct the central command if the movement error is increased due to an external disturbance. Each auxiliary module acts autonomously and can be interpreted as an agent. Each agent is responsible for one joint and, therefore, the number of the agents of each expert is equal to the number of joints. Our results indicate that this architecture is robust against external disturbances, signal-dependent noise in sensory information, and changes in the environment. We also discuss the neurophysiological and behavioral basis of

  13. Spiking neural networks with different reinforcement learning (RL) schemes in a multiagent setting.

    Science.gov (United States)

    Christodoulou, Chris; Cleanthous, Aristodemos

    2010-12-31

    This paper investigates the effectiveness of spiking agents when trained with reinforcement learning (RL) in a challenging multiagent task. In particular, it explores learning through reward-modulated spike-timing dependent plasticity (STDP) and compares it to reinforcement of stochastic synaptic transmission in the general-sum game of the Iterated Prisoner's Dilemma (IPD). More specifically, a computational model is developed where we implement two spiking neural networks as two "selfish" agents learning simultaneously but independently, competing in the IPD game. The purpose of our system (or collective) is to maximise its accumulated reward in the presence of reward-driven competing agents within the collective. This can only be achieved when the agents engage in a behaviour of mutual cooperation during the IPD. Previously, we successfully applied reinforcement of stochastic synaptic transmission to the IPD game. The current study utilises reward-modulated STDP with eligibility trace and results show that the system managed to exhibit the desired behaviour by establishing mutual cooperation between the agents. It is noted that the cooperative outcome was attained after a relatively short learning period which enhanced the accumulation of reward by the system. As in our previous implementation, the successful application of the learning algorithm to the IPD becomes possible only after we extended it with additional global reinforcement signals in order to enhance competition at the neuronal level. Moreover it is also shown that learning is enhanced (as indicated by an increased IPD cooperative outcome) through: (i) strong memory for each agent (regulated by a high eligibility trace time constant) and (ii) firing irregularity produced by equipping the agents' LIF neurons with a partial somatic reset mechanism.

  14. Nearly Cyclic Pursuit and its Hierarchical variant for Multi-agent Systems

    DEFF Research Database (Denmark)

    Iqbal, Muhammad; Leth, John-Josef; Ngo, Trung Dung

    2015-01-01

    The rendezvous problem for multiple agents under nearly cyclic pursuit and hierarchical nearly cyclic pursuit is discussed in this paper. The control law designed under nearly cyclic pursuit strategy enables the agents to converge at a point dictated by a beacon. A hierarchical version of the nea......The rendezvous problem for multiple agents under nearly cyclic pursuit and hierarchical nearly cyclic pursuit is discussed in this paper. The control law designed under nearly cyclic pursuit strategy enables the agents to converge at a point dictated by a beacon. A hierarchical version...

  15. Multiagent-Based Simulation of Temporal-Spatial Characteristics of Activity-Travel Patterns Using Interactive Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Min Yang

    2014-01-01

    Full Text Available We propose a multiagent-based reinforcement learning algorithm, in which the interactions between travelers and the environment are considered to simulate temporal-spatial characteristics of activity-travel patterns in a city. Road congestion degree is added to the reinforcement learning algorithm as a medium that passes the influence of one traveler’s decision to others. Meanwhile, the agents used in the algorithm are initialized from typical activity patterns extracted from the travel survey diary data of Shangyu city in China. In the simulation, both macroscopic activity-travel characteristics such as traffic flow spatial-temporal distribution and microscopic characteristics such as activity-travel schedules of each agent are obtained. Comparing the simulation results with the survey data, we find that deviation of the peak-hour traffic flow is less than 5%, while the correlation of the simulated versus survey location choice distribution is over 0.9.

  16. Best Response Bayesian Reinforcement Learning for Multiagent Systems with State Uncertainty

    NARCIS (Netherlands)

    F.A. Oliehoek; C. Amato

    2014-01-01

    It is often assumed that agents in multiagent systems with state uncertainty have full knowledge of the model of dy- namics and sensors, but in many cases this is not feasible. A more realistic assumption is that agents must learn about the environment and other agents while acting. Bayesian methods

  17. Single photon in hierarchical architecture for physical reinforcement learning: Photon intelligence

    CERN Document Server

    Naruse, Makoto; Drezet, Aurélien; Huant, Serge; Hori, Hirokazu; Kim, Song-Ju

    2016-01-01

    Understanding and using natural processes for intelligent functionalities, referred to as natural intelligence, has recently attracted interest from a variety of fields, including post-silicon computing for artificial intelligence and decision making in the behavioural sciences. In a past study, we successfully used the wave-particle duality of single photons to solve the two-armed bandit problem, which constitutes the foundation of reinforcement learning and decision making. In this study, we propose and confirm a hierarchical architecture for single-photon-based reinforcement learning and decision making that verifies the scalability of the principle. Specifically, the four-armed bandit problem is solved given zero prior knowledge in a two-layer hierarchical architecture, where polarization is autonomously adapted in order to effect adequate decision making using single-photon measurements. In the hierarchical structure, the notion of layer-dependent decisions emerges. The optimal solutions in the coarse la...

  18. Development of hierarchical cellulosic reinforcement for polymer composites

    OpenAIRE

    2014-01-01

    Cellulose is an environmentally friendly material which is obtainable in vast quantities, since it is present in every plant. Cellulosic fibers are commercially found in two forms: natural (flax, hemp, cotton, sisal, wood, etc.) and regenerated cellulose fibers (RCF). The biodegradability, the morphological and mechanical properties make these fibers a good alternative to the synthetic reinforcement (e.g. glass fibers). However, as all other cellulosic fibers these materials also have similar...

  19. Scaling Ant Colony Optimization with Hierarchical Reinforcement Learning Partitioning

    Science.gov (United States)

    2007-09-01

    on Mathematical Statistics and Probabilities, 281–297. 1967. 14. Parr , Ronald and Stuart Russell . “Reinforcement Learning with Hierarchies of...to affect the environment and the environment to affect the learning [14]. Parr does explain the environment can be partially observable and the...the execution of all other machines and monitors the completion of all machine actions. Parr uses a grid world to explain the setup of the navigation

  20. The contribution of reinforcement sensitivity to the personality-psychopathology hierarchical structure in childhood and adolescence.

    Science.gov (United States)

    Slobodskaya, Helena R

    2016-11-01

    This study examined the contribution of reinforcement sensitivity to the hierarchical structure of child personality and common psychopathology in community samples of parent reports of children aged 2-18 (N = 968) and self-reports of adolescents aged 10-18 (N = 1,543) using the Inventory of Child Individual Differences-Short version (ICID-S), the Strengths and Difficulties Questionnaire (SDQ), and the Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ). A joint higher-order factor analysis of the ICID-S and SDQ scales suggested a 4-factor solution; congruence coefficients indicated replicability of the factors across the 2 samples at all levels of the personality-psychopathology hierarchy. The canonical correlation analyses indicated that reinforcement sensitivity and personality-psychopathology dimensions shared much of their variance. The main contribution of reinforcement sensitivity was through opposing effects of reward and punishment sensitivities. The superordinate factors Beta and Internalizing were best predicted by reinforcement sensitivity, followed by the Externalizing and Positive personality factors. These findings provide evidence for consistency of the hierarchical structure of personality and common psychopathology across informants and highlight the role of reinforcement systems in the development of normal and abnormal patterns of behavior and affect. (PsycINFO Database Record

  1. Q D$-Learning: A Collaborative Distributed Strategy for Multi-Agent Reinforcement Learning Through Consensus + Innovations

    Science.gov (United States)

    Kar, Soummya; Moura, José M. F.; Poor, H. Vincent

    2013-04-01

    The paper considers a class of multi-agent Markov decision processes (MDPs), in which the network agents respond differently (as manifested by the instantaneous one-stage random costs) to a global controlled state and the control actions of a remote controller. The paper investigates a distributed reinforcement learning setup with no prior information on the global state transition and local agent cost statistics. Specifically, with the agents' objective consisting of minimizing a network-averaged infinite horizon discounted cost, the paper proposes a distributed version of $Q$-learning, $\\mathcal{QD}$-learning, in which the network agents collaborate by means of local processing and mutual information exchange over a sparse (possibly stochastic) communication network to achieve the network goal. Under the assumption that each agent is only aware of its local online cost data and the inter-agent communication network is \\emph{weakly} connected, the proposed distributed scheme is almost surely (a.s.) shown to yield asymptotically the desired value function and the optimal stationary control policy at each network agent. The analytical techniques developed in the paper to address the mixed time-scale stochastic dynamics of the \\emph{consensus + innovations} form, which arise as a result of the proposed interactive distributed scheme, are of independent interest.

  2. Multi-agent reinforcement learning using modular neural network Q-learning algorithms

    Institute of Scientific and Technical Information of China (English)

    YANG Yin-xian; FANG Kai

    2005-01-01

    Reinforcement learning is an excellent approach which is used in artificial intelligence,automatic control, etc. However, ordinary reinforcement learning algorithm, such as Q-learning with lookup table cannot cope with extremely complex and dynamic environment due to the huge state space. To reduce the state space, modular neural network Q-learning algorithm is proposed, which combines Q-learning algorithm with neural network and module method. Forward feedback neural network, Elman neural network and radius-basis neural network are separately employed to construct such algorithm. It is revealed that Elman neural network Q-learning algorithm has the best performance under the condition that the same neural network training method, i.e. gradient descent error back-propagation algorithm is applied.

  3. Mechanisms of hierarchical reinforcement learning in corticostriatal circuits 1: computational analysis.

    Science.gov (United States)

    Frank, Michael J; Badre, David

    2012-03-01

    Growing evidence suggests that the prefrontal cortex (PFC) is organized hierarchically, with more anterior regions having increasingly abstract representations. How does this organization support hierarchical cognitive control and the rapid discovery of abstract action rules? We present computational models at different levels of description. A neural circuit model simulates interacting corticostriatal circuits organized hierarchically. In each circuit, the basal ganglia gate frontal actions, with some striatal units gating the inputs to PFC and others gating the outputs to influence response selection. Learning at all of these levels is accomplished via dopaminergic reward prediction error signals in each corticostriatal circuit. This functionality allows the system to exhibit conditional if-then hypothesis testing and to learn rapidly in environments with hierarchical structure. We also develop a hybrid Bayesian-reinforcement learning mixture of experts (MoE) model, which can estimate the most likely hypothesis state of individual participants based on their observed sequence of choices and rewards. This model yields accurate probabilistic estimates about which hypotheses are attended by manipulating attentional states in the generative neural model and recovering them with the MoE model. This 2-pronged modeling approach leads to multiple quantitative predictions that are tested with functional magnetic resonance imaging in the companion paper.

  4. A special hierarchical fuzzy neural-networks based reinforcement learning for multi-variables system

    Institute of Scientific and Technical Information of China (English)

    ZHANG Wen-zhi; LU Tian-sheng

    2005-01-01

    Proposes a reinforcement learning scheme based on a special Hierarchical Fuzzy Neural-Networks (HFNN) for solving complicated learning tasks in a continuous multi-variables environment. The output of the previous layer in the HFNN is no longer used as if-part of the next layer, but used only in then-part. Thus it can deal with the difficulty when the output of the previous layer is meaningless or its meaning is uncertain. The proposed HFNN has a minimal number of fuzzy rules and can successfully solve the problem of rules combination explosion and decrease the quantity of computation and memory requirement. In the learning process, two HFNN with the same structure perform fuzzy action composition and evaluation function approximation simultaneously where the parameters of neural-networks are tuned and updated on line by using gradient descent algorithm. The reinforcement learning method is proved to be correct and feasible by simulation of a double inverted pendulum system.

  5. Mechanically Viscoelastic Properties of Cellulose Nanocrystals Skeleton Reinforced Hierarchical Composite Hydrogels.

    Science.gov (United States)

    Yang, Jun; Han, ChunRui

    2016-09-28

    With inspiration from the concept of natural dynamic materials, binary-component composite hydrogels with excellent mechanical properties and recovery capability were prepared from the cellulose nanocrystal (CNC) skeleton reinforced covalently cross-linked polyacrylamide (PAAm) networks. The hierarchical skeleton obtained by freeze-drying of CNC aqueous suspension was directly impregnated into acrylamide (AAm) monomer solution, and in situ polymerization occurred in the presence of hydrophilic cross-linker PEGDA575. Under stress, hydrogen bonds at the interface between CNC and PAAm as well as inside the CNC skeleton acted as sacrificial bonds to dissipate energy, while the covalently cross-linked PAAm chains bind the network together by providing adhesion to CNC and thereby suppress the catastrophic craze propagation. The above synergistic effects of the CNC skeleton and the elastic PAAm network enabled the composite hydrogels to withstand up to 181 kPa of tensile stress, 1.01 MPa of compressive strength, and 1392% elongation at break with the fracture energy as high as 2.82 kJ/m(2). Moreover, the hydrogels recovered more than 70% elasticity after eight loading-unloading cycles, revealing excellent fatigue resistance. The depth-sensing instrumentation by indentation test corroborated that the CNC skeleton contributed simultaneous improvements in hardness and elasticity by as much as 500% in comparison with the properties of the pristine PAAm hydrogels. This elegant strategy by using the CNC skeleton as a reinforcing template offers a new perspective for the fabrication of robust hydrogels with exceptional mechanical properties that may be important for biomedical applications where high strength is required, such as scaffolds for tissue engineering.

  6. Study on Multi-agent Systems with Colored Petri Nets

    Institute of Scientific and Technical Information of China (English)

    兰顺国; 李军

    2008-01-01

    The approach to model multi-agent systems with hierarchical colored Peal nets is introduced.In a multi-agent system,every agent is modeled with colored Petri net system,and the colored Petri net system of the multi-agent system is a hierarchical colored Petri net system,such that the agents planning deadlock detection and avoidance,can be analyzed with the Petri net system.

  7. 3D hierarchical computational model of wood as a cellular material with fibril reinforced, heterogeneous multiple layers

    DEFF Research Database (Denmark)

    Qing, Hai; Mishnaevsky, Leon

    2009-01-01

    A 3D hierarchical computational model of deformation and stiffness of wood, which takes into account the structures of wood at several scale levels (cellularity, multilayered nature of cell walls, composite-like structures of the wall layers) is developed. At the mesoscale, the softwood cell...... is presented as a 3D hexagon-shape-tube with multilayered walls. The layers in the softwood cell are considered as considered as composite reinforced by microfibrils (celluloses). The elastic properties of the layers are determined with Halpin–Tsai equations, and introduced into mesoscale finite element...... cellular model. With the use of the developed hierarchical model, the influence of the microstructure, including microfibril angles (MFAs, which characterizes the orientation of the cellulose fibrils with respect to the cell axis), the thickness of the cell wall, the shape of the cell cross...

  8. Hierarchically Organized Behavior and Its Neural Foundations: A Reinforcement Learning Perspective

    Science.gov (United States)

    Botvinick, Matthew M.; Niv, Yael; Barto, Andrew C.

    2009-01-01

    Research on human and animal behavior has long emphasized its hierarchical structure--the divisibility of ongoing behavior into discrete tasks, which are comprised of subtask sequences, which in turn are built of simple actions. The hierarchical structure of behavior has also been of enduring interest within neuroscience, where it has been widely…

  9. Hierarchically Organized Behavior and Its Neural Foundations: A Reinforcement Learning Perspective

    Science.gov (United States)

    Botvinick, Matthew M.; Niv, Yael; Barto, Andrew C.

    2009-01-01

    Research on human and animal behavior has long emphasized its hierarchical structure--the divisibility of ongoing behavior into discrete tasks, which are comprised of subtask sequences, which in turn are built of simple actions. The hierarchical structure of behavior has also been of enduring interest within neuroscience, where it has been widely…

  10. A CBR-Based Multiagent Reinforcement Learning Approach%一种基于案例推理的多agent强化学习方法研究

    Institute of Scientific and Technical Information of China (English)

    李珺; 潘启树; 洪炳殚

    2009-01-01

    A multiagent reinforcement learning approach based on CBR (case-based reasoning) is proposed. The system policy case library is built, and the relevant policy case subset is chosen by judging the cooperation relationship between the agents. Simulated annealing is used to find the fittest and reuseful case policy, and then the agents choose their actions based on the case. And if there is no practicable case in the case library, the agents carry out joint action learning (JAL). The system policy case library can be updated in real time based on the learning results. The detailed simulation results on pursuit problem are presented to show the superiority of the presented method in learning speed and convergency.%提出一种基于案例推理的多agent强化学习方法.构建了系统策略案例库,通过判断agent之间的协作关系选择相应案例库子集.利用模拟退火方法从中寻找最合适的可再用案例策略,agent按照案例指导执行动作选择.在没有可用案例的情况下,agent执行联合行为学习(JAL).在学习结果的基础上实时更新系统策略案例库.追捕问题的仿真结果表明所提方法明显提高了学习速度与收敛性.

  11. Carbon fiber/carbon nanotube reinforced hierarchical composites: Effect of CNT distribution on shearing strength

    DEFF Research Database (Denmark)

    Zhou, H. W.; Mishnaevsky, Leon; Yi, H. Y.;

    2016-01-01

    The strength and fracture behavior of carbon fiber reinforced polymer composites with carbon nanotube (CNT) secondary reinforcement are investigated experimentally and numerically. Short Beam Shearing tests have been carried out, with SEM observations of the damage evolution in the composites. 3D...... multiscale computational (FE) models of the carbon/polymer composite with varied CNT distributions have been developed and employed to study the effect of the secondary CNT reinforcement, its distribution and content on the strength and fracture behavior of the composites. It is shown that adding secondary...... CNT nanoreinforcement into the matrix and/or the sizing of carbon fiber/reinforced composites ensures strong increase of the composite strength. The effect of secondary CNTs reinforcement is strongest when some small addition of CNTs in the polymer matrix is complemented by the fiber sizing with high...

  12. Multiagent systems

    National Research Council Canada - National Science Library

    Sycara, Katia P

    1998-01-01

    ... of such multiagent systems (MASs) are a core set of issues and research questions that have been studied over the years by the distributed AT community. In this article, I present some of the critical notions in MASs and the research work that has addressed them. I organize these notions around the concept of problem-solving coherence,...

  13. Reinforcement Learning Multi-Agent Modeling of Decision-Making Agents for the Study of Transboundary Surface Water Conflicts with Application to the Syr Darya River Basin

    Science.gov (United States)

    Riegels, N.; Siegfried, T.; Pereira Cardenal, S. J.; Jensen, R. A.; Bauer-Gottwein, P.

    2008-12-01

    In most economics--driven approaches to optimizing water use at the river basin scale, the system is modelled deterministically with the goal of maximizing overall benefits. However, actual operation and allocation decisions must be made under hydrologic and economic uncertainty. In addition, river basins often cross political boundaries, and different states may not be motivated to cooperate so as to maximize basin- scale benefits. Even within states, competing agents such as irrigation districts, municipal water agencies, and large industrial users may not have incentives to cooperate to realize efficiency gains identified in basin- level studies. More traditional simulation--optimization approaches assume pre-commitment by individual agents and stakeholders and unconditional compliance on each side. While this can help determine attainable gains and tradeoffs from efficient management, such hardwired policies do not account for dynamic feedback between agents themselves or between agents and their environments (e.g. due to climate change etc.). In reality however, we are dealing with an out-of-equilibrium multi-agent system, where there is neither global knowledge nor global control, but rather continuous strategic interaction between decision making agents. Based on the theory of stochastic games, we present a computational framework that allows for studying the dynamic feedback between decision--making agents themselves and an inherently uncertain environment in a spatially and temporally distributed manner. Agents with decision-making control over water allocation such as countries, irrigation districts, and municipalities are represented by reinforcement learning agents and coupled to a detailed hydrologic--economic model. This approach emphasizes learning by agents from their continuous interaction with other agents and the environment. It provides a convenient framework for the solution of the problem of dynamic decision-making in a mixed cooperative / non

  14. A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

    CERN Document Server

    Brochu, Eric; de Freitas, Nando

    2010-01-01

    We present a tutorial on Bayesian optimization, a method of finding the maximum of expensive cost functions. Bayesian optimization employs the Bayesian technique of setting a prior over the objective function and combining it with evidence to get a posterior function. This permits a utility-based selection of the next observation to make on the objective function, which must take into account both exploration (sampling from areas of high uncertainty) and exploitation (sampling areas likely to offer improvement over the current best observation). We also present two detailed extensions of Bayesian optimization, with experiments---active user modelling with preferences, and hierarchical reinforcement learning---and a discussion of the pros and cons of Bayesian optimization based on our experiences.

  15. Computational Properties of the Hippocampus Increase the Efficiency of Goal-Directed Foraging through Hierarchical Reinforcement Learning.

    Science.gov (United States)

    Chalmers, Eric; Luczak, Artur; Gruber, Aaron J

    2016-01-01

    The mammalian brain is thought to use a version of Model-based Reinforcement Learning (MBRL) to guide "goal-directed" behavior, wherein animals consider goals and make plans to acquire desired outcomes. However, conventional MBRL algorithms do not fully explain animals' ability to rapidly adapt to environmental changes, or learn multiple complex tasks. They also require extensive computation, suggesting that goal-directed behavior is cognitively expensive. We propose here that key features of processing in the hippocampus support a flexible MBRL mechanism for spatial navigation that is computationally efficient and can adapt quickly to change. We investigate this idea by implementing a computational MBRL framework that incorporates features inspired by computational properties of the hippocampus: a hierarchical representation of space, "forward sweeps" through future spatial trajectories, and context-driven remapping of place cells. We find that a hierarchical abstraction of space greatly reduces the computational load (mental effort) required for adaptation to changing environmental conditions, and allows efficient scaling to large problems. It also allows abstract knowledge gained at high levels to guide adaptation to new obstacles. Moreover, a context-driven remapping mechanism allows learning and memory of multiple tasks. Simulating dorsal or ventral hippocampal lesions in our computational framework qualitatively reproduces behavioral deficits observed in rodents with analogous lesions. The framework may thus embody key features of how the brain organizes model-based RL to efficiently solve navigation and other difficult tasks.

  16. Computational Properties of the Hippocampus Increase the Efficiency of Goal-Directed Foraging through Hierarchical Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Eric Chalmers

    2016-12-01

    Full Text Available The mammalian brain is thought to use a version of Model-based Reinforcement Learning (MBRL to guide goal-directed behavior, wherein animals consider goals and make plans to acquire desired outcomes. However, conventional MBRL algorithms do not fully explain animals’ ability to rapidly adapt to environmental changes, or learn multiple complex tasks. They also require extensive computation, suggesting that goal-directed behavior is cognitively expensive. We propose here that key features of processing in the hippocampus support a flexible MBRL mechanism for spatial navigation that is computationally efficient and can adapt quickly to change. We investigate this idea by implementing a computational MBRL framework that incorporates features inspired by computational properties of the hippocampus: a hierarchical representation of space, forward sweeps through future spatial trajectories, and context-driven remapping of place cells. We find that a hierarchical abstraction of space greatly reduces the computational load (mental effort required for adaptation to changing environmental conditions, and allows efficient scaling to large problems. It also allows abstract knowledge gained at high levels to guide adaptation to new obstacles. Moreover, a context-driven remapping mechanism allows learning and memory of multiple tasks. Simulating dorsal or ventral hippocampal lesions in our computational framework qualitatively reproduces behavioral deficits observed in rodents with analogous lesions. The framework may thus embody key features of how the brain organizes model-based RL to efficiently solve navigation and other difficult tasks.

  17. Hierarchical fiber-optic delamination detection system for carbon fiber reinforced plastic structures

    Science.gov (United States)

    Minakuchi, Shu; Banshoya, Hidehiko; Shingo, Ii; Takeda, Nobuo

    2012-10-01

    This study develops a delamination detection system by extending our previous approach for monitoring surface cracks in a large-scale composite structure. In the new system, numerous thin glass capillaries are embedded into a composite structure, and internal pressure in the built-in capillary sensors, based on comparative vacuum monitoring (CVM), is maintained as a vacuum. When delamination is induced, the capillary sensors located within the delaminated area are breached, and atmospheric air flows into the capillaries. The consequent pressure change within the capillaries is then converted into axial strain in a surface-mounted optical fiber through a transducing mechanism, which is connected to the capillaries. By monitoring the strain distribution along the optical fiber, it is possible to identify a transducing mechanism in which the pressure change occurred and thus to specify the location of the delamination. This study begins by establishing a novel sensor embedding/extracting method. The airflow characteristic in the capillary sensors is then comprehensively evaluated, determining the basic performance of the new system. The proposed detection technique is validated by taking a step-by-step approach, and finally the hierarchical fiber-optic delamination detection system is demonstrated. A further advance to be combined with a self-healing concept is also discussed.

  18. "Notice of Violation of IEEE Publication Principles" Multiobjective Reinforcement Learning: A Comprehensive Overview.

    Science.gov (United States)

    Liu, Chunming; Xu, Xin; Hu, Dewen

    2013-04-29

    Reinforcement learning is a powerful mechanism for enabling agents to learn in an unknown environment, and most reinforcement learning algorithms aim to maximize some numerical value, which represents only one long-term objective. However, multiple long-term objectives are exhibited in many real-world decision and control problems; therefore, recently, there has been growing interest in solving multiobjective reinforcement learning (MORL) problems with multiple conflicting objectives. The aim of this paper is to present a comprehensive overview of MORL. In this paper, the basic architecture, research topics, and naive solutions of MORL are introduced at first. Then, several representative MORL approaches and some important directions of recent research are reviewed. The relationships between MORL and other related research are also discussed, which include multiobjective optimization, hierarchical reinforcement learning, and multi-agent reinforcement learning. Finally, research challenges and open problems of MORL techniques are highlighted.

  19. Research on Multiagent Cooperation with Markov Game and Reinforcement Learning%基于 MarkoV对策和强化学习的多智能体协作研究

    Institute of Scientific and Technical Information of China (English)

    李晓萌; 杨煜普; 许晓鸣

    2001-01-01

    Non zero-sum Markov game and reinforcement learning based on Q-algorithm is a feasible frame for the research on the mechanism of multiagent system's cooperation. In fact, the independent learning is accentuated for agent regardless of other agents' actions under this frame. So, the mechanism of cooperation is deficient. And, it is over idealized that the perfect observed information is required when agents are interacting with environment. In the paper, cooperated learning under joined action and imperfect information was proposed for solving these two problems. Convergence of the improving algorithm was proved.%MAS的协作机制研究,当前比较适用的研究框架是非零和Markov对策及基于Q-算法的强化学习.但实际上在这种框架下的Agent强调独立学习而不考虑其他Agent的行为,故MAS缺乏协作机制.并且,Q-算法要求Agent与环境的交互时具有完备的观察信息,这种情况过于理想化.文中针对以上两个不足,提出了在联合行动和不完备信息下的协调学习.理论分析和仿真实验表明,协调学习算法具有收敛性.

  20. A statistical property of multiagent learning based on Markov decision process.

    Science.gov (United States)

    Iwata, Kazunori; Ikeda, Kazushi; Sakai, Hideaki

    2006-07-01

    We exhibit an important property called the asymptotic equipartition property (AEP) on empirical sequences in an ergodic multiagent Markov decision process (MDP). Using the AEP which facilitates the analysis of multiagent learning, we give a statistical property of multiagent learning, such as reinforcement learning (RL), near the end of the learning process. We examine the effect of the conditions among the agents on the achievement of a cooperative policy in three different cases: blind, visible, and communicable. Also, we derive a bound on the speed with which the empirical sequence converges to the best sequence in probability, so that the multiagent learning yields the best cooperative result.

  1. Polyhedral oligomeric silsesquioxanes/carbon nanotube/carbon fiber multiscale composite: Influence of a novel hierarchical reinforcement on the interfacial properties

    Science.gov (United States)

    Zhang, R. L.; Wang, C. G.; Liu, L.; Cui, H. Z.; Gao, B.

    2015-10-01

    A novel hierarchical reinforcing carbon fiber through co-grafting carbon nanotube (CNTs) and polyhedral oligomeric silsesquioxanes (POSS) was prepared in this paper. The structure and surface characteristics of the grafted carbon fiber were investigated by Fourier transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), thermogravimetry (TG) and scanning electron microscope (SEM), respectively. The surface energy and the functional groups of the carbon fiber surface were increased obviously after modification. The ILSS results showed that there was a remarkable improvement in the interfacial properties of the new hybrid CF-CNTs-POSS composites. The investigation can prove an effective way to increase the interfacial adhesion and improve the mechanical performance of the fiber/resin composites on the desired application.

  2. Dynamic hierarchical reinforcement learning based on probability model%基于概率模型的动态分层强化学习

    Institute of Scientific and Technical Information of China (English)

    戴朝晖; 袁姣红; 吴敏; 陈鑫

    2011-01-01

    为解决大规模强化学习中的"维度灾难"问题,克服以往学习算法的性能高度依赖于先验知识的局限性,本文提出一种基于概率模型的动态分层强化学习方法.首先基于贝叶斯学习对状态转移概率进行建模,建立基于概率参数的关键状态识别方法,进而通过聚类动态生成若干状态子空间和学习分层结构下的最优策略.仿真结果表明该算法能显著提高复杂环境下智能体的学习效率,适用于未知环境中的大规模学习.%To deal with the overwhelming dimensionality in the large-scale reinforcement-learning and the strong depen-dence on prior knowledge in existing learning algorithms,we propose the method of dynamic hierarchical reinforcement learning based on the probability model(DHRL--model).This method identifies some key states automatically based on probability parameters of the state-transition probability model established based on Bayesian learning,then generates some state-subspaces dynamically by clustering,and learns the optimal policy based on hierarchical structure.Simulation results show that DHRL--model algorithm improves the learning efficiency of the agent remarkably in the complex environment,and can be applied to learning in the unknown large-scale world.

  3. Towards an Intelligent Possibilistic Web Information Retrieval Using Multiagent System

    Science.gov (United States)

    Elayeb, Bilel; Evrard, Fabrice; Zaghdoud, Montaceur; Ahmed, Mohamed Ben

    2009-01-01

    Purpose: The purpose of this paper is to make a scientific contribution to web information retrieval (IR). Design/methodology/approach: A multiagent system for web IR is proposed based on new technologies: Hierarchical Small-Worlds (HSW) and Possibilistic Networks (PN). This system is based on a possibilistic qualitative approach which extends the…

  4. Towards an Intelligent Possibilistic Web Information Retrieval Using Multiagent System

    Science.gov (United States)

    Elayeb, Bilel; Evrard, Fabrice; Zaghdoud, Montaceur; Ahmed, Mohamed Ben

    2009-01-01

    Purpose: The purpose of this paper is to make a scientific contribution to web information retrieval (IR). Design/methodology/approach: A multiagent system for web IR is proposed based on new technologies: Hierarchical Small-Worlds (HSW) and Possibilistic Networks (PN). This system is based on a possibilistic qualitative approach which extends the…

  5. Engineering Multiagent Systems - Reflections

    DEFF Research Database (Denmark)

    Villadsen, Jørgen

    2012-01-01

    In the first part I look at a theater performance by artistic director Troels Christian Jakobsen as a multiagent system. It is designed as a self-organising critical system using a framework where within its borders but without a script there is real interaction between the elements...... a curriculum for the MSc in Computer Science and Engineering program at the Technical University of Denmark with a focus on multiagent systems. As the director of studies I have observed that the students are working hard and with much creativity in advanced courses and projects involving intelligent agents...

  6. Cognitive Medical Multiagent Systems

    Directory of Open Access Journals (Sweden)

    Barna Iantovics

    2010-01-01

    Full Text Available The development of efficient and flexible agent-based medical diagnosis systems represents a recent research direction. Medical multiagent systems may improve the efficiency of traditionally developed medical computational systems, like the medical expert systems. In our previous researches, a novel cooperative medical diagnosis multiagent system called CMDS (Contract Net Based Medical Diagnosis System was proposed. CMDS system can solve flexibly a large variety of medical diagnosis problems. This paper analyses the increased intelligence of the CMDS system, which motivates its use for different medical problem’s solving.

  7. Hierarchical regional cooperative Q-learning%分层的局部合作Q-学习

    Institute of Scientific and Technical Information of China (English)

    刘亮; 李龙澍

    2009-01-01

    多智能体Q-学习问题往往因为联合动作的个数指数级增长而变得无法解决.从研究分层强化学习入手,通过对强化学习中合作MAS的研究,在基于系统工作逻辑的研究基础上,提出了基于学习过程分层的局部合作强化学习,通过对独立Agent强化学习的知识考察,改进多Agent系统学习的效率,进一步提高了局部合作强化学习的效能.从而解决强化学习中的状态空间的维数灾难,并通过仿真足球的2vsl防守证明了算法的有效性.%Many multi-agent Q-learning problems can not be solved because of the number of joint actions is exponential in the number of agents.Based on the study of the cooperation in MAS in reinforcement learning and on the basis of the research in the system logic,this paper puts forward the hierarchical regional cooperation reinforcement learning based on learning process.By studying the knowledge of Agent reinforcement learning and improving the multi-Agent study efficiency,the performance of the regional cooperation reinforcement learning is further enhanced,combining with the mission action based on joint action and potential field model so as to solve the dimensional disaster in state space of reinforcement learning.This algorithm is used in a subtask of robot soccer and its effectiveness is validated by experiments.

  8. Optimal Response Learning and Its Convergence in Multiagent Domains

    Institute of Scientific and Technical Information of China (English)

    ZHANG Hua-xiang; HUANG Shang-teng; LE Jia-jin

    2005-01-01

    In multiagent reinforcement learning, with different assumptions of the opponents' policies, an agent adopts quite different learning rules, and gets different learning performances. We prove that, in nultiagent domains, convergence of the Q values is guaranteed only when an agent behaves optimally and its opponents' strategies satisfy certain conditions, and an agent can get best learning performances when it adopts the same learning algorithm as that of its opponents.

  9. A Behavior-based Approach for Multi-agent Q-learning for Autonomous Exploration

    CERN Document Server

    Ray, Dip Narayan; Mukhopadhyay, Sumit

    2011-01-01

    The use of mobile robots is being popular over the world mainly for autonomous explorations in hazardous/ toxic or unknown environments. This exploration will be more effective and efficient if the explorations in unknown environment can be aided with the learning from past experiences. Currently reinforcement learning is getting more acceptances for implementing learning in robots from the system-environment interactions. This learning can be implemented using the concept of both single-agent and multiagent. This paper describes such a multiagent approach for implementing a type of reinforcement learning using a priority based behaviour-based architecture. This proposed methodology has been successfully tested in both indoor and outdoor environments.

  10. Reinforcement learning control with approximation of time-dependent agent dynamics

    Science.gov (United States)

    Kirkpatrick, Kenton Conrad

    Reinforcement Learning has received a lot of attention over the years for systems ranging from static game playing to dynamic system control. Using Reinforcement Learning for control of dynamical systems provides the benefit of learning a control policy without needing a model of the dynamics. This opens the possibility of controlling systems for which the dynamics are unknown, but Reinforcement Learning methods like Q-learning do not explicitly account for time. In dynamical systems, time-dependent characteristics can have a significant effect on the control of the system, so it is necessary to account for system time dynamics while not having to rely on a predetermined model for the system. In this dissertation, algorithms are investigated for expanding the Q-learning algorithm to account for the learning of sampling rates and dynamics approximations. For determining a proper sampling rate, it is desired to find the largest sample time that still allows the learning agent to control the system to goal achievement. An algorithm called Sampled-Data Q-learning is introduced for determining both this sample time and the control policy associated with that sampling rate. Results show that the algorithm is capable of achieving a desired sampling rate that allows for system control while not sampling "as fast as possible". Determining an approximation of an agent's dynamics can be beneficial for the control of hierarchical multiagent systems by allowing a high-level supervisor to use the dynamics approximations for task allocation decisions. To this end, algorithms are investigated for learning first- and second-order dynamics approximations. These algorithms are respectively called First-Order Dynamics Learning and Second-Order Dynamics Learning. The dynamics learning algorithms are evaluated on several examples that show their capability to learn accurate approximations of state dynamics. All of these algorithms are then evaluated on hierarchical multiagent systems

  11. Metrics for Multiagent Systems

    Science.gov (United States)

    Lass, Robert N.; Sultanik, Evan A.; Regli, William C.

    A Multiagent System (MAS) is a software paradigm for building large scale intelligent distributed systems. Increasingly these systems are being deployed on handheld computing devices that rely on non-traditional communications mediums such as mobile ad hoc networks and satellite links. These systems present new challenges for computer scientists in describing system performance and analyzing competing systems. This chapter surveys existing metrics that can be used to describe MASs and related components. A framework for analyzing MASs is provided and an example of how this framework might be employed is given for the domain of distributed constraint reasoning.

  12. Event-triggered hybrid control based on multi-Agent systems for Microgrids

    DEFF Research Database (Denmark)

    Dou, Chun-xia; Liu, Bin; Guerrero, Josep M.

    2014-01-01

    of distributed energy resources, thus it is typical hybrid dynamic network. Considering the complex hybrid behaviors, a hierarchical decentralized coordinated control scheme is firstly constructed based on multi-agent sys-tem, then, the hybrid model of the microgrid is built by using differential hybrid Petri...

  13. Stability of Evolving Multiagent Systems.

    Science.gov (United States)

    De Wilde, P; Briscoe, G

    2011-08-01

    A multiagent system is a distributed system where the agents or nodes perform complex functions that cannot be written down in analytic form. Multiagent systems are highly connected, and the information they contain is mostly stored in the connections. When agents update their state, they take into account the state of the other agents, and they have access to those states via the connections. There is also external user-generated input into the multiagent system. As so much information is stored in the connections, agents are often memory less. This memory-less property, together with the randomness of the external input, has allowed us to model multiagent systems using Markov chains. In this paper, we look at multiagent systems that evolve, i.e., the number of agents varies according to the fitness of the individual agents. We extend our Markov chain model and define stability. This is the start of a methodology to control multiagent systems. We then build upon this to construct an entropy-based definition for the degree of instability (entropy of the limit probabilities), which we used to perform a stability analysis. We then investigated the stability of evolving agent populations through simulation and show that the results are consistent with the original definition of stability in nonevolving multiagent systems, proposed by Chli and De Wilde. This paper forms the theoretical basis for the construction of digital business ecosystems, and applications have been reported elsewhere.

  14. Learning and stabilization of altruistic behaviors in multi-agent systems by reciprocity.

    Science.gov (United States)

    Zamora, J; Millán, J R; Murciano, A

    1998-03-01

    Optimization of performance in collective systems often requires altruism. The emergence and stabilization of altruistic behaviors are difficult to achieve because the agents incur a cost when behaving altruistically. In this paper, we propose a biologically inspired strategy to learn stable altruistic behaviors in artificial multi-agent systems, namely reciprocal altruism. This strategy in conjunction with learning capabilities make altruistic agents cooperate only between themselves, thus preventing their exploitation by selfish agents, if future benefits are greater than the current cost of altruistic acts. Our multi-agent system is made up of agents with a behavior-based architecture. Agents learn the most suitable cooperative strategy for different environments by means of a reinforcement learning algorithm. Each agent receives a reinforcement signal that only measures its individual performance. Simulation results show how the multi-agent system learns stable altruistic behaviors, so achieving optimal (or near-to-optimal) performances in unknown and changing environments.

  15. Multiagent scheduling models and algorithms

    CERN Document Server

    Agnetis, Alessandro; Gawiejnowicz, Stanisław; Pacciarelli, Dario; Soukhal, Ameur

    2014-01-01

    This book presents multi-agent scheduling models in which subsets of jobs sharing the same resources are evaluated by different criteria. It discusses complexity results, approximation schemes, heuristics and exact algorithms.

  16. Micromechanics of hierarchical materials

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon, Jr.

    2012-01-01

    A short overview of micromechanical models of hierarchical materials (hybrid composites, biomaterials, fractal materials, etc.) is given. Several examples of the modeling of strength and damage in hierarchical materials are summarized, among them, 3D FE model of hybrid composites...... with nanoengineered matrix, fiber bundle model of UD composites with hierarchically clustered fibers and 3D multilevel model of wood considered as a gradient, cellular material with layered composite cell walls. The main areas of research in micromechanics of hierarchical materials are identified, among them......, the investigations of the effects of load redistribution between reinforcing elements at different scale levels, of the possibilities to control different material properties and to ensure synergy of strengthening effects at different scale levels and using the nanoreinforcement effects. The main future directions...

  17. Multiagent distributed watershed management

    Science.gov (United States)

    Giuliani, M.; Castelletti, A.; Amigoni, F.; Cai, X.

    2012-04-01

    Deregulation and democratization of water along with increasing environmental awareness are challenging integrated water resources planning and management worldwide. The traditional centralized approach to water management, as described in much of water resources literature, is often unfeasible in most of the modern social and institutional contexts. Thus it should be reconsidered from a more realistic and distributed perspective, in order to account for the presence of multiple and often independent Decision Makers (DMs) and many conflicting stakeholders. Game theory based approaches are often used to study these situations of conflict (Madani, 2010), but they are limited to a descriptive perspective. Multiagent systems (see Wooldridge, 2009), instead, seem to be a more suitable paradigm because they naturally allow to represent a set of self-interested agents (DMs and/or stakeholders) acting in a distributed decision process at the agent level, resulting in a promising compromise alternative between the ideal centralized solution and the actual uncoordinated practices. Casting a water management problem in a multiagent framework allows to exploit the techniques and methods that are already available in this field for solving distributed optimization problems. In particular, in Distributed Constraint Satisfaction Problems (DCSP, see Yokoo et al., 2000), each agent controls some variables according to his own utility function but has to satisfy inter-agent constraints; while in Distributed Constraint Optimization Problems (DCOP, see Modi et al., 2005), the problem is generalized by introducing a global objective function to be optimized that requires a coordination mechanism between the agents. In this work, we apply a DCSP-DCOP based approach to model a steady state hypothetical watershed management problem (Yang et al., 2009), involving several active human agents (i.e. agents who make decisions) and reactive ecological agents (i.e. agents representing

  18. Specialization in multi-agent systems through learning.

    Science.gov (United States)

    Murciano, A; Millán, J R; Zamora, J

    1997-05-01

    Specialization is a common feature in animal societies that leads to an improvement in the fitness of the team members and to an increase in the resources obtained by the team. In this paper we propose a simple reinforcement learning approach to specialization in an artificial multi-agent system. The system is composed of homogeneous and non-communicating agents. Because there is no communication, the number of agents in the team can easily scale up. Agents have the same initial functionalities, but they learn to specialize and so cooperate to achieve a complex gathering task efficiently. Simulation experiments show how the multi-agent system specializes appropriately so as to reach optimal (or near-to-optimal) performance in unknown and changing environments.

  19. Planning for Multiagent Using ASP-Prolog

    Science.gov (United States)

    Son, Tran Cao; Pontelli, Enrico; Nguyen, Ngoc-Hieu

    This paper presents an Answer Set Programming based approach to multiagent planning. The proposed methodology extends the action language \\cal B in [12] to represent and reason about plans with cooperative actions of an individual agent operating in a multiagent environment. This language is used to formalize multiagent planning problems and the notion of a joint plan for multiagent in the presence of cooperative actions. Finally, the paper presents a system for computing joint plans based on the ASP-Prolog system.

  20. The Construction of a Self-adaptive Multi-Agent System Based on Reinforcement Learning%基于强化学习的自适应多Agent系统的构造

    Institute of Scientific and Technical Information of China (English)

    沈乐; 毛新军; 董孟高

    2011-01-01

    The environment of self-adaptive systems is often uncertain, and the changes are difficult to predict. To develop such complex self-adaptive software systems has become a great challenge in the domain of software engineering. Reinforcement learning is an important branch of machine learning. A reinforcement learning system can learn the optimal mapping policy from the states of environment to the actions by means of trail-and-error. Aiming to deal with the uncertainty of environments, this paper combines the agent technology and the reinforcement learning technology together, and proposes an a-daptive mechanism based on reinforcement learning and the corresponding approach to construct complex self-adaptive systems that can adapt to the changes of uncertain environments. A case is illustrated to validate the effectiveness of the proposed mechanism and approach.%自适应系统所处的环境往往是不确定的,其变化事先难以预测,如何支持这种环境下复杂自适应系统的开发已经成为软件工程领域面临的一项重要挑战.强化学习是机器学习领域中的一个重要分支,强化学习系统能够通过不断试错的方式,学习环境状态到可执行动作的最优对应策略.本文针对自适应系统环境不确定的问题,将Agent技术与强化学习技术相结合,提出复杂自适应系统开发的核心运行机制和构造技术,从而使得所开发的自适应系统具备在不确定环境下适应环境变化的能力.论文通过案例分析阐述了如何基于学习机制来进行自适应多Agent系统的开发,验证了该机制和方法的有效性.

  1. Multiagent -Learning for Aloha-Like Spectrum Access in Cognitive Radio Systems

    Directory of Open Access Journals (Sweden)

    Li Husheng

    2010-01-01

    Full Text Available An Aloha-like spectrum access scheme without negotiation is considered for multiuser and multichannel cognitive radio systems. To avoid collisions incurred by the lack of coordination, each secondary user learns how to select channels according to its experience. Multiagent reinforcement leaning (MARL is applied for the secondary users to learn good strategies of channel selection. Specifically, the framework of -learning is extended from single user case to multiagent case by considering other secondary users as a part of the environment. The dynamics of the -learning are illustrated using a Metrick-Polak plot, which shows the traces of -values in the two-user case. For both complete and partial observation cases, rigorous proofs of the convergence of multiagent -learning without communications, under certain conditions, are provided using the Robins-Monro algorithm and contraction mapping, respectively. The learning performance (speed and gain in utility is evaluated by numerical simulations.

  2. MULTIAGENT LEARNING WITHIN A COLLABORATIVE ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    LJUBICA KAZI

    2012-05-01

    Full Text Available Multiagent Learning is at the intersection of multiagent systems and Machine Learning, two subdomains of artificial intelligence. Traditional Machine Learning technologies usually imply a single agent that is trying to maximize some utility functions without having any knowledge about other agents within its environment. The multiagent systems domain refers to the domains where several agents are involved and mechanisms for the independent agents’ behaviors interaction have to be considered. Due to multiagent systems’ complexity, there have to be found solutions for using Machine Learning technologies to manage this complexity.

  3. Consensus of Hybrid Multi-Agent Systems.

    Science.gov (United States)

    Zheng, Yuanshi; Ma, Jingying; Wang, Long

    2017-01-27

    In this brief, we consider the consensus problem of hybrid multiagent systems. First, the hybrid multiagent system is proposed, which is composed of continuous-time and discrete-time dynamic agents. Then, three kinds of consensus protocols are presented for the hybrid multiagent system. The analysis tool developed in this brief is based on the matrix theory and graph theory. With different restrictions of the sampling period, some necessary and sufficient conditions are established for solving the consensus of the hybrid multiagent system. The consensus states are also obtained under different protocols. Finally, simulation examples are provided to demonstrate the effectiveness of our theoretical results.

  4. 一种基于启发式奖赏函数的分层强化学习方法%A Hierarchical Reinforcement Learning Method Based on Heuristic Reward Function

    Institute of Scientific and Technical Information of China (English)

    刘全; 闫其粹; 伏玉琛; 胡道京; 龚声蓉

    2011-01-01

    针对强化学习在应用中经常出现的“维数灾”问题,即状态空间的大小随着特征数量的增加而发生指数级的增长,以及收敛速度过慢的问题,提出了一种基于启发式奖赏函数的分层强化学习方法.该方法不仅能够大幅度减少环境状态空间,还能加快学习的收敛速度.将此算法应用到俄罗斯方块的仿真平台中,通过对实验中的参数进行设置及对算法性能进行分析,结果表明:采用启发式奖赏函数的分层强化学习方法能在一定程度上解决“维数灾”问题,并具有很好的收敛速度.%Reinforcement learning is about controlling an autonomous agent in an unknown enviroment-often called the state space. The agent has no prior knowledge about the environment and can only obtain some knowledge by acting in the environment. Reinforcement learning, and Q-learning particularly, encounters a major problem. Learning the Q-function in tablular form may be infeasible because the amount of memory needed to store the table is excessive, and the Q-f unction converges only after each state being visited a lot of times. So "curse of dimensionality" is inevitably produced by large state spaces. A hierarchical reinforcement learning method based on heuristic reward function is proposed to solve the problem of "curse of dimensionality", which make the states space grow exponentially by the number of features and slow down the convergence speed. The method can reduce state spaces greatly and quicken the speed of the study. Actions are chosen with favorable purpose and efficiency so as to optimize the reward function and quicken the convergence speed. The Tetris game is applied in the method. Analysis of algorithms and the experiment result show that the method can partly solve the "curse of dimensionality" and quicken the convergence speed prominently.

  5. 一种基于多Agent强化学习的多星协同任务规划算法%An Algorithm of Cooperative Multiple Satellites Mission Planning Based on Multi-agent Reinforcement Learning

    Institute of Scientific and Technical Information of China (English)

    王冲; 景宁; 李军; 王钧; 陈浩

    2011-01-01

    在分析任务特点和卫星约束的基础上给出了多星协同任务规划问题的数学模型.引入约束惩罚算子和多星联合惩罚算子对卫星Agent原始的效用值增益函数进行改进,在此基础上提出了一种多卫星Agent强化学习算法以求解多星协同任务分配策略,设计了基于黑板结构的多星交互方式以降低学习交互过程中的通信代价.通过仿真实验及分析证明该方法能够有效解决多星协同任务规划问题.%A multi-satellite cooperative planning problem model was given considering the characteristics of the task requests and satellite constraints. Then the original performance function of each satellite agent was modified by introducing both the constraint punishing operator and the multi-satellite joint punishing operator. Next, a multi-satellite reinforcement learning algorithm (MUSARLA)was proposed to derive the coordinated task allocation strategy. Furethermore, the interaction among multiple satellites was designed based on blackboard architecture to reduce the communication cost while learning. Fimally, simulated experiments are carried out which verified the effectiveness of the proposed algorithm.

  6. Deliberate evolution in multi-agent systems

    NARCIS (Netherlands)

    Brazier, F.M.T.; Jonker, C.M.; Treur, J.; Wijngaards, N.J.E.

    1998-01-01

    This paper presents an architecture for an agent capable of deliberation about the creation of new agents, and of actually creating a new agent in the multi-agent system, on the basis of this deliberation. After its creation the new agent participates fully in the running multi-agent system. The age

  7. Of Mechanism Design and Multiagent Planning

    NARCIS (Netherlands)

    Van der Krogt, R.P.J.; De Weerdt, M.M.; Zhang, Y.

    2008-01-01

    Multiagent planning methods are concerned with planning by and for a group of agents. If the agents are selfinterested, they may be tempted to lie in order to obtain an outcome that is more rewarding for them. We therefore study the multiagent planning problem from a mechanism design perspective,

  8. Multi-agent for manufacturing systems optimization

    Science.gov (United States)

    Ciortea, E. M.; Tulbure, A.; Huţanu, C.-tin

    2016-08-01

    The paper is meant to be a dynamic approach to optimize manufacturing systems based on multi-agent systems. Multi-agent systems are semiautonomous decision makers and cooperate to optimize the manufacturing process. Increasing production the capacity is achieved by developing, implementing efficient and effective systems from control based on current manufacturing process. The model multi-agent proposed in this paper is based on communication between agents who, based on their mechanisms drive to autonomous decision making. Methods based on multi-agent programming are applied between flexible manufacturing processes and cooperation with agents. Based on multi-agent technology and architecture of intelligent manufacturing can lead to development of strategies for control and optimization of scheduled production resulting from the simulation.

  9. Multi-Agent System based Event-Triggered Hybrid Controls for High-Security Hybrid Energy Generation Systems

    DEFF Research Database (Denmark)

    Dou, Chun-Xia; Yue, Dong; Guerrero, Josep M.

    2017-01-01

    This paper proposes multi-agent system based event- triggered hybrid controls for guaranteeing energy supply of a hybrid energy generation system with high security. First, a mul-ti-agent system is constituted by an upper-level central coordi-nated control agent combined with several lower...... switching control, distributed dynamic regulation and coordinated switching con-trol are designed fully dependent on the hybrid behaviors of all distributed energy resources and the logical relationships be-tween them, and interact with each other by means of the mul-ti-agent system to form hierarchical......-level unit agents. Each lower-level unit agent is responsible for dealing with internal switching control and distributed dynamic regula-tion for its unit system. The upper-level agent implements coor-dinated switching control to guarantee the power supply of over-all system with high security. The internal...

  10. Synchronized Task Decomposition for Cooperative Multi-agent Systems

    CERN Document Server

    Karimadini, M

    2009-01-01

    The key challenge in cooperative control for multi-agent systems could be how to design the local interaction rules and coordination principles among agents so as to achieve certain desired global behaviors. In this paper, we try to tackle this challenge from the angle of hierarchical control, and propose a divide-and-conquer approach. The basic idea is to decompose the requested global specification into subtasks for individual agents or small clusters of agents. It should be noted that the decomposition is not arbitrary. The global specification should be decomposed in such a way that the fulfilment of these subtasks by each individual agent will imply the satisfaction of the global specification as a team. Formally, a given global specification can be represented as an automaton A, while a multi-agent system can be captured as a set of parallel distributed systems. The first question needs to be answered is whether it is always possible to decompose a given task automaton A into a finite number of sub-auto...

  11. THE INTEGRATED AGENT IN MULTI-AGENT SYSTEMS

    OpenAIRE

    Maleković, Mirko; Čubrilo, Mirko

    2000-01-01

    [n this paper, we characterize the integrated agent in multi-agent systems. The following result is proved: if a multi-agent system is reflexive (symmetric, transitive, Euclidean) then the integrated agent of the multi-agent system is reflexive (symmetric, transitive, Euclidean), respectively. We also prove that the analogous result does not hold for multi-agent system's serial ness. A knowledge relationship between the integrated agent and agents in a multiagent system is presented.

  12. Multiagent Learning of Coordination in Loosely Coupled Multiagent Systems.

    Science.gov (United States)

    Yu, Chao; Zhang, Minjie; Ren, Fenghui; Tan, Guozhen

    2015-12-01

    Multiagent learning (MAL) is a promising technique for agents to learn efficient coordinated behaviors in multiagent systems (MASs). In MAL, concurrent multiple distributed learning processes can make the learning environment nonstationary for each individual learner. Developing an efficient learning approach to coordinate agents' behaviors in this dynamic environment is a difficult problem, especially when agents do not know the domain structure and have only local observability of the environment. In this paper, a coordinated MAL approach is proposed to enable agents to learn efficient coordinated behaviors by exploiting agent independence in loosely coupled MASs. The main feature of the proposed approach is to explicitly quantify and dynamically adapt agent independence during learning so that agents can make a trade-off between a single-agent learning process and a coordinated learning process for an efficient decision making. The proposed approach is employed to solve two-robot navigation problems in different scales of domains. Experimental results show that agents using the proposed approach can learn to act in concert or independently in different areas of the environment, which results in great computational savings and near optimal performance.

  13. Model learning and knowledge sharing for a multiagent system with Dyna-Q learning.

    Science.gov (United States)

    Hwang, Kao-Shing; Jiang, Wei-Cheng; Chen, Yu-Jen

    2015-05-01

    In a multiagent system, if agents' experiences could be accessible and assessed between peers for environmental modeling, they can alleviate the burden of exploration for unvisited states or unseen situations so as to accelerate the learning process. Since how to build up an effective and accurate model within a limited time is an important issue, especially for complex environments, this paper introduces a model-based reinforcement learning method based on a tree structure to achieve efficient modeling and less memory consumption. The proposed algorithm tailored a Dyna-Q architecture to multiagent systems by means of a tree structure for modeling. The tree-model built from real experiences is used to generate virtual experiences such that the elapsed time in learning could be reduced. As well, this model is suitable for knowledge sharing. This paper is inspired by the concept of knowledge sharing methods in multiagent systems where an agent could construct a global model from scattered local models held by individual agents. Consequently, it can increase modeling accuracy so as to provide valid simulated experiences for indirect learning at the early stage of learning. To simplify the sharing process, the proposed method applies resampling techniques to grafting partial branches of trees containing required and useful experiences disseminated from experienced peers, instead of merging the whole trees. The simulation results demonstrate that the proposed sharing method can achieve the objectives of sample efficiency and learning acceleration in multiagent cooperation applications.

  14. Multi-agent and complex systems

    CERN Document Server

    Ren, Fenghui; Fujita, Katsuhide; Zhang, Minjie; Ito, Takayuki

    2017-01-01

    This book provides a description of advanced multi-agent and artificial intelligence technologies for the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field. A complex system features a large number of interacting components, whose aggregate activities are nonlinear and self-organized. A multi-agent system is a group or society of agents which interact with others cooperatively and/or competitively in order to reach their individual or common goals. Multi-agent systems are suitable for modeling and simulation of complex systems, which is difficult to accomplish using traditional computational approaches.

  15. Hierarchical photocatalysts.

    Science.gov (United States)

    Li, Xin; Yu, Jiaguo; Jaroniec, Mietek

    2016-05-01

    As a green and sustainable technology, semiconductor-based heterogeneous photocatalysis has received much attention in the last few decades because it has potential to solve both energy and environmental problems. To achieve efficient photocatalysts, various hierarchical semiconductors have been designed and fabricated at the micro/nanometer scale in recent years. This review presents a critical appraisal of fabrication methods, growth mechanisms and applications of advanced hierarchical photocatalysts. Especially, the different synthesis strategies such as two-step templating, in situ template-sacrificial dissolution, self-templating method, in situ template-free assembly, chemically induced self-transformation and post-synthesis treatment are highlighted. Finally, some important applications including photocatalytic degradation of pollutants, photocatalytic H2 production and photocatalytic CO2 reduction are reviewed. A thorough assessment of the progress made in photocatalysis may open new opportunities in designing highly effective hierarchical photocatalysts for advanced applications ranging from thermal catalysis, separation and purification processes to solar cells.

  16. Multi-agent autonomous system

    Science.gov (United States)

    Fink, Wolfgang (Inventor); Dohm, James (Inventor); Tarbell, Mark A. (Inventor)

    2010-01-01

    A multi-agent autonomous system for exploration of hazardous or inaccessible locations. The multi-agent autonomous system includes simple surface-based agents or craft controlled by an airborne tracking and command system. The airborne tracking and command system includes an instrument suite used to image an operational area and any craft deployed within the operational area. The image data is used to identify the craft, targets for exploration, and obstacles in the operational area. The tracking and command system determines paths for the surface-based craft using the identified targets and obstacles and commands the craft using simple movement commands to move through the operational area to the targets while avoiding the obstacles. Each craft includes its own instrument suite to collect information about the operational area that is transmitted back to the tracking and command system. The tracking and command system may be further coupled to a satellite system to provide additional image information about the operational area and provide operational and location commands to the tracking and command system.

  17. Tracking algorithms for multiagent systems.

    Science.gov (United States)

    Meng, Deyuan; Jia, Yingmin; Du, Junping; Yu, Fashan

    2013-10-01

    This paper is devoted to the consensus tracking issue on multiagent systems. Instead of enabling the networked agents to reach an agreement asymptotically as the time tends to infinity, the consensus tracking between agents is considered to be derived on a finite time interval as accurately as possible. We thus propose a learning algorithm with a gain operator to be determined. If the gain operator is designed in the form of a polynomial expression, a necessary and sufficient condition is obtained for the networked agents to accomplish the consensus tracking objective, regardless of the relative degree of the system model of agents. Moreover, the H∞ analysis approach is introduced to help establish conditions in terms of linear matrix inequalities (LMIs) such that the resulting processes of the presented learning algorithm can be guaranteed to monotonically converge in an iterative manner. The established LMI conditions can also enable the iterative learning processes to converge with an exponentially fast speed. In addition, we extend the learning algorithm to address the relative formation problem for multiagent systems. Numerical simulations are performed to demonstrate the effectiveness of learning algorithms in achieving both consensus tracking and relative formation objectives for the networked agents.

  18. Pass-ball trainning based on genetic reinforcement learning

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Introduces a mixture genetic algorithm and reinforcement learning computation model used for inde pendent agent learning in continuous, distributive, open environment, which takes full advantage of the reactive and robust of reinforcement learning algorithm and the property that genetic algorithm is suitable to the problem with high dimension, large collectivity, complex environment, and concludes that through proper training, the result verifies that this method is available in the complex multi-agent environment.

  19. Convergence Analysis of Distributed Control for Operation Cost Minimization of Droop Controlled DC Microgrid Based on Multiagent

    DEFF Research Database (Denmark)

    Li, Chendan; Quintero, Juan Carlos Vasquez; Guerrero, Josep M.

    2016-01-01

    In this paper we present a distributed control method for minimizing the operation cost in DC microgrid based on multiagent system. Each agent is autonomous and controls the local converter in a hierarchical way through droop control, voltage scheduling and collective decision making. The collect......In this paper we present a distributed control method for minimizing the operation cost in DC microgrid based on multiagent system. Each agent is autonomous and controls the local converter in a hierarchical way through droop control, voltage scheduling and collective decision making....... The collective decision for the whole system is made by proposed incremental cost consensus, and only nearest-neighbor communication is needed. The convergence characteristics of the consensus algorithm are analyzed considering different communication topologies and control parameters. Case studies verified...... the proposed method by comparing it without traditional methods. The robustness of system is tested under different communication latency and plug and play operation....

  20. Metamodeling of Semantic Web Enabled Multiagent Systems

    NARCIS (Netherlands)

    Kardas, G.; Göknil, Arda; Dikenelli, O.; Topaloglu, N.Y.; Weyns, D.; Holvoet, T.

    2006-01-01

    Several agent researchers are currently studying agent modeling and they propose dierent architectural metamodels for developing Multiagent Systems (MAS) according to specic agent development methodologies. When support for Semantic Web technology and its related constructs are considered, agent

  1. Massive Multi-Agent Systems Control

    Science.gov (United States)

    Campagne, Jean-Charles; Gardon, Alain; Collomb, Etienne; Nishida, Toyoaki

    2004-01-01

    In order to build massive multi-agent systems, considered as complex and dynamic systems, one needs a method to analyze and control the system. We suggest an approach using morphology to represent and control the state of large organizations composed of a great number of light software agents. Morphology is understood as representing the state of the multi-agent system as shapes in an abstract geometrical space, this notion is close to the notion of phase space in physics.

  2. Multiagent voltage and reactive power control system

    Directory of Open Access Journals (Sweden)

    I. Arkhipov

    2014-12-01

    Full Text Available This paper is devoted to the research of multiagent voltage and reactive power control system development. The prototype of the system has been developed by R&D Center at FGC UES (Russia. The control system architecture is based on the innovative multiagent system theory application that leads to the achievement of several significant advantages (in comparison to traditional control systems implementation such as control system efficiency enhancement, control system survivability and cyber security.

  3. Multiagent-Based Model For ESCM

    OpenAIRE

    Delia MARINCAS

    2011-01-01

    Web based applications for Supply Chain Management (SCM) are now a necessity for every company in order to meet the increasing customer demands, to face the global competition and to make profit. Multiagent-based approach is appropriate for eSCM because it shows many of the characteristics a SCM system should have. For this reason, we have proposed a multiagent-based eSCM model which configures a virtual SC, automates the SC activities: selling, purchasing, manufacturing, planning, inventory,...

  4. Stability of Evolving Multi-Agent Systems

    CERN Document Server

    De Wilde, Philippe; 10.1109/TSMCB.2011.2110642

    2011-01-01

    A Multi-Agent System is a distributed system where the agents or nodes perform complex functions that cannot be written down in analytic form. Multi-Agent Systems are highly connected, and the information they contain is mostly stored in the connections. When agents update their state, they take into account the state of the other agents, and they have access to those states via the connections. There is also external, user-generated input into the Multi-Agent System. As so much information is stored in the connections, agents are often memory-less. This memory-less property, together with the randomness of the external input, has allowed us to model Multi-Agent Systems using Markov chains. In this paper, we look at Multi-Agent Systems that evolve, i.e. the number of agents varies according to the fitness of the individual agents. We extend our Markov chain model, and define stability. This is the start of a methodology to control Multi-Agent Systems. We then build upon this to construct an entropy-based defi...

  5. RAO Logic for Multiagent Framework

    Institute of Scientific and Technical Information of China (English)

    SHI Zhongzhi; TIAN Qijia; LI Yunfeng

    1999-01-01

    In this paper, we deal with how agentsreason about knowledge of others in multiagent system. We firstpresent a knowledge representation framework called reasoning aboutothers (RAO) which isdesigned specifically to represent concepts and rules used inreasoning about knowledge of others. From a class of sentences usuallytaken by people in daily life to reason about others, a rule called position exchange principle (PEP) is abstracted. PEP is described as anaxiom scheme in RAO and regarded as a basic rule for agents to reasonabout others, and further it has the similar formand role to modus ponens and (K) axiom of knowledge logic. Therelationship between speech acts and common sense is also discussedwhich is necessary for RAO. Based on ideas fromsituation calculus, this relationship is characterized by an axiomschema in RAO. Our theories are also demonstrated by an example.

  6. A multiagent urban traffic simulation

    CERN Document Server

    Tranouez, Pierrick; Langlois, Patrice

    2012-01-01

    We built a multiagent simulation of urban traffic to model both ordinary traffic and emergency or crisis mode traffic. This simulation first builds a modeled road network based on detailed geographical information. On this network, the simulation creates two populations of agents: the Transporters and the Mobiles. Transporters embody the roads themselves; they are utilitarian and meant to handle the low level realism of the simulation. Mobile agents embody the vehicles that circulate on the network. They have one or several destinations they try to reach using initially their beliefs of the structure of the network (length of the edges, speed limits, number of lanes etc.). Nonetheless, when confronted to a dynamic, emergent prone environment (other vehicles, unexpectedly closed ways or lanes, traffic jams etc.), the rather reactive agent will activate more cognitive modules to adapt its beliefs, desires and intentions. It may change its destination(s), change the tactics used to reach the destination (favorin...

  7. Clustered volatility in multiagent dynamics

    CERN Document Server

    Youssefmir, M; Youssefmir, Michael; Huberman, Bernardo

    1995-01-01

    Large distributed multiagent systems are characterized by vast numbers of agents trying to gain access to limited resources in an unpredictable environment. Agents in these system continuously switch strategies in order to opportunistically find improvements in their utilities. We have analyzed the fluctuations around equilibrium that arise from strategy switching and discovered the existence of a new phenomenon. It consists of the appearance of sudden bursts of activity that punctuate the fixed point, and is due to an effective random walk consistent with overall stability. This clustered volatility is followed by relaxation to the fixed point but with different strategy mixes from the previous one. This phenomenon is quite general for systems in which agents explore strategies in search of local improvements.

  8. Angelic Hierarchical Planning: Optimal and Online Algorithms

    Science.gov (United States)

    2008-12-06

    restrict our attention to plans in I∗(Act, s0). Definition 2. ( Parr and Russell , 1998) A plan ah∗ is hierarchically optimal iff ah∗ = argmina∈I∗(Act,s0):T...Murdock, Dan Wu, and Fusun Yaman. SHOP2: An HTN planning system. JAIR, 20:379–404, 2003. Ronald Parr and Stuart Russell . Reinforcement Learning with...Angelic Hierarchical Planning: Optimal and Online Algorithms Bhaskara Marthi Stuart J. Russell Jason Wolfe Electrical Engineering and Computer

  9. Multi-agent programming languages, tools and applications

    CERN Document Server

    Seghrouchni, Amal El Fallah; Dastani, Mehdi; Bordini, Rafael H

    2009-01-01

    Multi-Agent Systems are a promising technology to develop the next generation open distributed complex software systems. This title presents a number of mature and influential multi-agent programming languages, platforms, development tools and methodologies, and realistic applications.

  10. Periodic Behaviors in Constrained Multi-agent Systems

    OpenAIRE

    YANG Tao; Meng, Ziyang; Dimarogonas, Dimos V.; Johansson, Karl H.

    2014-01-01

    In this paper, we provide two discrete-time multi-agent models which generate periodic behaviors. The first one is a multi-agent system of identical double integrators with input saturation constraints, while the other one is a multi-agent system of identical neutrally stable system with input saturation constraints. In each case, we show that if the feedback gain parameters of the local controller satisfy a certain condition, the multi-agent system exhibits a periodic solution.

  11. Impulsive Flocking of Dynamical Multiagent Systems with External Disturbances

    Directory of Open Access Journals (Sweden)

    Fujun Han

    2017-01-01

    Full Text Available Flocking motion of multiagent systems is influenced by various external disturbances in complex environment. By applying disturbance observer, flocking of multiagent systems with exogenous disturbances is studied. Based on the robust features of impulsive control, a distributed impulsive control protocol is presented with disturbance observer, and flocking motion of multiagent systems is analyzed. Moreover, a sufficient condition is obtained to ensure the flocking motion of multiagent systems following a leader. Finally, simulation results show the validity of the theoretical conclusion.

  12. Multi-agent Justification Logic : communication and evidence elimination

    NARCIS (Netherlands)

    Renne, Bryan

    2012-01-01

    This paper presents a logic combining , a framework for reasoning about multi-agent communication, with a new multi-agent version of , a framework for reasoning about evidence and justification. This novel combination incorporates a new kind of that cleanly meshes with the multi-agent communications

  13. The MultiAgent Decision Process toolbox: Software for decision-theoretic planning in multiagent-systems

    NARCIS (Netherlands)

    Spaan, M.T.J.; Oliehoek, F.A.; Shen, J.; Varakantham, P.; Maheswaran, R.

    2008-01-01

    This paper introduces the MultiAgent Decision Process software toolbox, an open source C++ library for decision-theoretic planning under uncertainty in multiagent systems. It provides support for several multiagent models, such as POSGs, Dec-POMDPs and MMDPs. The toolbox aims to reduce development

  14. Consensus and Stability Analysis of Networked Multiagent Predictive Control Systems.

    Science.gov (United States)

    Liu, Guo-Ping

    2017-04-01

    This paper is concerned with the consensus and stability problem of multiagent control systems via networks with communication delays and data loss. A networked multiagent predictive control scheme is proposed to achieve output consensus and also compensate for the communication delays and data loss actively. The necessary and sufficient conditions of achieving both consensus and stability of the closed-loop networked multiagent control systems are derived. An important result that is obtained is that the consensus and stability of closed-loop networked multiagent predictive control systems are not related to the communication delays and data loss. An example illustrates the performance of the networked multiagent predictive control scheme.

  15. Hierarchical machining materials and their performance

    DEFF Research Database (Denmark)

    Sidorenko, Daria; Loginov, Pavel; Levashov, Evgeny

    2016-01-01

    as nanoparticles in the binder, or polycrystalline, aggregate-like reinforcements, also at several scale levels). Such materials can ensure better productivity, efficiency, and lower costs of drilling, cutting, grinding, and other technological processes. This article reviews the main groups of hierarchical...

  16. Building Multi-Agent Systems Using Jason

    DEFF Research Database (Denmark)

    Boss, Niklas Skamriis; Jensen, Andreas Schmidt; Villadsen, Jørgen

    2010-01-01

    We provide a detailed description of the Jason-DTU system, including the used methodology, tools as well as team strategy. We also discuss the experience gathered in the contest. In spring 2009 the course “Artificial Intelligence and Multi- Agent Systems” was held for the first time...... on the Technical University of Denmark (DTU). A part of this course was a short introduction to the multi-agent framework Jason, which is an interpreter for AgentSpeak, an agent-oriented programming language. As the final project in this course a solution to the Multi-Agent Programming Contest from 2007, the Gold...

  17. FUZZY LOGIC MULTI-AGENT SYSTEM

    OpenAIRE

    Atef GHARBI; Ben Ahmed, Samir

    2014-01-01

    The paper deals with distributed planning in a Multi-Agent System (MAS) constituted by several intelligent agents each one has to interact with the other autonomous agents. The problem faced is how to ensure a distributed planning through the cooperation in our multi-agent system. To do so, we propose the use of fuzzy logic to represent the response of the agent in case of interaction with the other. Finally, we use JADE platform to create agents and ensure the communication be...

  18. Building Multi-Agent Systems Using Jason

    DEFF Research Database (Denmark)

    Boss, Niklas Skamriis; Jensen, Andreas Schmidt; Villadsen, Jørgen

    2010-01-01

    We provide a detailed description of the Jason-DTU system, including the used methodology, tools as well as team strategy. We also discuss the experience gathered in the contest. In spring 2009 the course “Artificial Intelligence and Multi- Agent Systems” was held for the first time...... on the Technical University of Denmark (DTU). A part of this course was a short introduction to the multi-agent framework Jason, which is an interpreter for AgentSpeak, an agent-oriented programming language. As the final project in this course a solution to the Multi-Agent Programming Contest from 2007, the Gold...

  19. Multi-agent systems simulation and applications

    CERN Document Server

    Uhrmacher, Adelinde M

    2009-01-01

    Methodological Guidelines for Modeling and Developing MAS-Based SimulationsThe intersection of agents, modeling, simulation, and application domains has been the subject of active research for over two decades. Although agents and simulation have been used effectively in a variety of application domains, much of the supporting research remains scattered in the literature, too often leaving scientists to develop multi-agent system (MAS) models and simulations from scratch. Multi-Agent Systems: Simulation and Applications provides an overdue review of the wide ranging facets of MAS simulation, i

  20. Research of Communication Mechanism of the Multi-agent in Multi-agent Robot Systems

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The cooperation of multi-robot that is based on the multi-agent system (MAS) theory of distributed artificial intelligence has become a hotspot in the robotics R&D. In the research the multi-robot is regarded as multi-agent. So the communication and cooperation of multi-agent become the key problem for gaining the dynamic running information of cooperating robots. In this paper the authors introduce the communication modes for agent and provide a common strategy which aims at the communication resources of multi-agent model-the CSMA/CD (Carrier Sense Multiple Access with Collision Detection) protocol which is based on the transmittal medium. It supports the cable-communication of multi-robot and the experiments prove its validity.

  1. Reinforcement learning in supply chains.

    Science.gov (United States)

    Valluri, Annapurna; North, Michael J; Macal, Charles M

    2009-10-01

    Effective management of supply chains creates value and can strategically position companies. In practice, human beings have been found to be both surprisingly successful and disappointingly inept at managing supply chains. The related fields of cognitive psychology and artificial intelligence have postulated a variety of potential mechanisms to explain this behavior. One of the leading candidates is reinforcement learning. This paper applies agent-based modeling to investigate the comparative behavioral consequences of three simple reinforcement learning algorithms in a multi-stage supply chain. For the first time, our findings show that the specific algorithm that is employed can have dramatic effects on the results obtained. Reinforcement learning is found to be valuable in multi-stage supply chains with several learning agents, as independent agents can learn to coordinate their behavior. However, learning in multi-stage supply chains using these postulated approaches from cognitive psychology and artificial intelligence take extremely long time periods to achieve stability which raises questions about their ability to explain behavior in real supply chains. The fact that it takes thousands of periods for agents to learn in this simple multi-agent setting provides new evidence that real world decision makers are unlikely to be using strict reinforcement learning in practice.

  2. Deliberate Evolution in Multi-Agent Systems

    NARCIS (Netherlands)

    Brazier, F.M.T.; Jonker, C.M.; Treur, J.; Wijngaards, N.J.E.

    2000-01-01

    This paper presents an architecture for an agent capable of deliberation about the creation of new agents, and of actually creating a new agent in the multi-agent system, on the basis of this deliberation. The agent architecture is based on an existing

  3. Multi-Agent Planning with Planning Graph

    NARCIS (Netherlands)

    Bui, The Duy; Jamroga, Wojciech

    2003-01-01

    In this paper, we consider planning for multi-agents situations in STRIPS-like domains with planning graph. Three possible relationships between agents' goals are considered in order to evaluate plans: the agents may be collaborative, adversarial or indifferent entities. We propose algorithms to dea

  4. Scalable Planning and Learning for Multiagent POMDPs

    NARCIS (Netherlands)

    Amato, C.; Oliehoek, F.A.

    2015-01-01

    Online, sample-based planning algorithms for POMDPs have shown great promise in scaling to problems with large state spaces, but they become intractable for large action and observation spaces. This is particularly problematic in multiagent POMDPs where the action and observation space grows exponen

  5. Introduction to Planning in Multiagent Systems

    NARCIS (Netherlands)

    De Weerdt, M.M.; Clement, B.

    2009-01-01

    In most multiagent systems planning on forehand can help to seriously improve the efficiency of executing actions. The main difference between centrally creating a plan and constructing a plan for a system of agents lies in the fact that in the latter coordination plays the main part. This introduce

  6. Multi-Agent Systems Design for Novices

    Science.gov (United States)

    Lynch, Simon; Rajendran, Keerthi

    2005-01-01

    Advanced approaches to the construction of software systems can present difficulties to learners. This is true for multi-agent systems (MAS) which exhibit concurrency, non-determinacy of structure and composition and sometimes emergent behavior characteristics. Additional barriers exist for learners because mainstream MAS technology is young and…

  7. Introduction to Planning in Multiagent Systems

    NARCIS (Netherlands)

    De Weerdt, M.M.; Clement, B.

    2009-01-01

    In most multiagent systems planning on forehand can help to seriously improve the efficiency of executing actions. The main difference between centrally creating a plan and constructing a plan for a system of agents lies in the fact that in the latter coordination plays the main part. This

  8. Hierarchical unilamellar vesicles of controlled compositional heterogeneity.

    Directory of Open Access Journals (Sweden)

    Maik Hadorn

    Full Text Available Eukaryotic life contains hierarchical vesicular architectures (i.e. organelles that are crucial for material production and trafficking, information storage and access, as well as energy production. In order to perform specific tasks, these compartments differ among each other in their membrane composition and their internal cargo and also differ from the cell membrane and the cytosol. Man-made structures that reproduce this nested architecture not only offer a deeper understanding of the functionalities and evolution of organelle-bearing eukaryotic life but also allow the engineering of novel biomimetic technologies. Here, we show the newly developed vesicle-in-water-in-oil emulsion transfer preparation technique to result in giant unilamellar vesicles internally compartmentalized by unilamellar vesicles of different membrane composition and internal cargo, i.e. hierarchical unilamellar vesicles of controlled compositional heterogeneity. The compartmentalized giant unilamellar vesicles were subsequently isolated by a separation step exploiting the heterogeneity of the membrane composition and the encapsulated cargo. Due to the controlled, efficient, and technically straightforward character of the new preparation technique, this study allows the hierarchical fabrication of compartmentalized giant unilamellar vesicles of controlled compositional heterogeneity and will ease the development of eukaryotic cell mimics that resemble their natural templates as well as the fabrication of novel multi-agent drug delivery systems for combination therapies and complex artificial microreactors.

  9. Adaptive, Distributed Control of Constrained Multi-Agent Systems

    Science.gov (United States)

    Bieniawski, Stefan; Wolpert, David H.

    2004-01-01

    Product Distribution (PO) theory was recently developed as a broad framework for analyzing and optimizing distributed systems. Here we demonstrate its use for adaptive distributed control of Multi-Agent Systems (MASS), i.e., for distributed stochastic optimization using MAS s. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (Probability dist&&on on the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. One common way to find that equilibrium is to have each agent run a Reinforcement Learning (E) algorithm. PD theory reveals this to be a particular type of search algorithm for minimizing the Lagrangian. Typically that algorithm i s quite inefficient. A more principled alternative is to use a variant of Newton's method to minimize the Lagrangian. Here we compare this alternative to RL-based search in three sets of computer experiments. These are the N Queen s problem and bin-packing problem from the optimization literature, and the Bar problem from the distributed RL literature. Our results confirm that the PD-theory-based approach outperforms the RL-based scheme in all three domains.

  10. Optimal Wonderful Life Utility Functions in Multi-Agent Systems

    Science.gov (United States)

    Wolpert, David H.; Tumer, Kagan; Swanson, Keith (Technical Monitor)

    2000-01-01

    The mathematics of Collective Intelligence (COINs) is concerned with the design of multi-agent systems so as to optimize an overall global utility function when those systems lack centralized communication and control. Typically in COINs each agent runs a distinct Reinforcement Learning (RL) algorithm, so that much of the design problem reduces to how best to initialize/update each agent's private utility function, as far as the ensuing value of the global utility is concerned. Traditional team game solutions to this problem assign to each agent the global utility as its private utility function. In previous work we used the COIN framework to derive the alternative Wonderful Life Utility (WLU), and experimentally established that having the agents use it induces global utility performance up to orders of magnitude superior to that induced by use of the team game utility. The WLU has a free parameter (the clamping parameter) which we simply set to zero in that previous work. Here we derive the optimal value of the clamping parameter, and demonstrate experimentally that using that optimal value can result in significantly improved performance over that of clamping to zero, over and above the improvement beyond traditional approaches.

  11. Product Distribution Theory for Control of Multi-Agent Systems

    Science.gov (United States)

    Lee, Chia Fan; Wolpert, David H.

    2004-01-01

    Product Distribution (PD) theory is a new framework for controlling Multi-Agent Systems (MAS's). First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint stare of the agents. Accordingly we can consider a team game in which the shared utility is a performance measure of the behavior of the MAS. For such a scenario the game is at equilibrium - the Lagrangian is optimized - when the joint distribution of the agents optimizes the system's expected performance. One common way to find that equilibrium is to have each agent run a reinforcement learning algorithm. Here we investigate the alternative of exploiting PD theory to run gradient descent on the Lagrangian. We present computer experiments validating some of the predictions of PD theory for how best to do that gradient descent. We also demonstrate how PD theory can improve performance even when we are not allowed to rerun the MAS from different initial conditions, a requirement implicit in some previous work.

  12. Multi-agents and learning: Implications for Webusage mining.

    Science.gov (United States)

    Lotfy, Hewayda M S; Khamis, Soheir M S; Aboghazalah, Maie M

    2016-03-01

    Characterization of user activities is an important issue in the design and maintenance of websites. Server weblog files have abundant information about the user's current interests. This information can be mined and analyzed therefore the administrators may be able to guide the users in their browsing activity so they may obtain relevant information in a shorter span of time to obtain user satisfaction. Web-based technology facilitates the creation of personally meaningful and socially useful knowledge through supportive interactions, communication and collaboration among educators, learners and information. This paper suggests a new methodology based on learning techniques for a Web-based Multiagent-based application to discover the hidden patterns in the user's visited links. It presents a new approach that involves unsupervised, reinforcement learning, and cooperation between agents. It is utilized to discover patterns that represent the user's profiles in a sample website into specific categories of materials using significance percentages. These profiles are used to make recommendations of interesting links and categories to the user. The experimental results of the approach showed successful user pattern recognition, and cooperative learning among agents to obtain user profiles. It indicates that combining different learning algorithms is capable of improving user satisfaction indicated by the percentage of precision, recall, the progressive category weight and F 1-measure.

  13. Improving Multi-Agent Systems Using Jason

    DEFF Research Database (Denmark)

    Vester, Steen; Boss, Niklas Skamriis; Jensen, Andreas Schmidt

    2011-01-01

    We describe the approach used to develop the multi-agent system of herders that competed as the Jason-DTU team at the Multi-Agent Programming Contest 2010. We also participated in 2009 with a system developed in the agentoriented programming language Jason which is an extension of AgentSpeak. We...... used the implementation from 2009 as a foundation and therefore much of the work done this year was on improving that implementation. We present a description which includes design and analysis of the system as well as the main features of our agent team strategy. In addition we discuss...... the technologies used to develop this system as well as our future goals in the area....

  14. Advanced Approach of Multiagent Based Buoy Communication

    Directory of Open Access Journals (Sweden)

    Gediminas Gricius

    2015-01-01

    Full Text Available Usually, a hydrometeorological information system is faced with great data flows, but the data levels are often excessive, depending on the observed region of the water. The paper presents advanced buoy communication technologies based on multiagent interaction and data exchange between several monitoring system nodes. The proposed management of buoy communication is based on a clustering algorithm, which enables the performance of the hydrometeorological information system to be enhanced. The experiment is based on the design and analysis of the inexpensive but reliable Baltic Sea autonomous monitoring network (buoys, which would be able to continuously monitor and collect temperature, waviness, and other required data. The proposed approach of multiagent based buoy communication enables all the data from the costal-based station to be monitored with limited transition speed by setting different tasks for the agent-based buoy system according to the clustering information.

  15. Network Management using Multi-Agents System

    Directory of Open Access Journals (Sweden)

    Nestor DUQUE

    2013-07-01

    Full Text Available This paper aims to present a multiagent system for network management. The models developed for the proposed system defines certain intelligent agents interact to achieve the objectives and requirements of the multiagent organization.These agents have the property of being adaptive, acquire knowledge and skills to make decisions according to the actual state of the network that is represented in the information base, MIB, SNMP devices. The ideal state of the network policy is defined by the end user entered, which contain the value that should have performance variables and other parameters such as the frequency with which these variables should be monitored.. An agent based architecture increase the integration, adaptability, cooperation, autonomy and the efficient operation in heterogeneous environment in the network supervision. 

  16. Network Management using Multi-Agents System

    Directory of Open Access Journals (Sweden)

    Gustavo ISAZA

    2012-12-01

    Full Text Available This paper aims to present a multiagent system for network management. The models developed for the proposed system defines certain intelligent agents interact to achieve the objectives and requirements of the multiagent organization.These agents have the property of being adaptive, acquire knowledge and skills to make decisions according to the actual state of the network that is represented in the information base, MIB, SNMP devices. The ideal state of the network policy is defined by the end user entered, which contain the value that should have performance variables and other parameters such as the frequency with which these variables should be monitored.. An agent based architecture increase the integration, adaptability, cooperation, autonomy and the efficient operation in heterogeneous environment in the network supervision. 

  17. Existence of Multiagent Equilibria with Limited Agents

    CERN Document Server

    Bowling, M; 10.1613/jair.1332

    2011-01-01

    Multiagent learning is a necessary yet challenging problem as multiagent systems become more prevalent and environments become more dynamic. Much of the groundbreaking work in this area draws on notable results from game theory, in particular, the concept of Nash equilibria. Learners that directly learn an equilibrium obviously rely on their existence. Learners that instead seek to play optimally with respect to the other players also depend upon equilibria since equilibria are fixed points for learning. From another perspective, agents with limitations are real and common. These may be undesired physical limitations as well as self-imposed rational limitations, such as abstraction and approximation techniques, used to make learning tractable. This article explores the interactions of these two important concepts: equilibria and limitations in learning. We introduce the question of whether equilibria continue to exist when agents have limitations. We look at the general effects limitations can have on agent b...

  18. Autonomous Formations of Multi-Agent Systems

    Science.gov (United States)

    Dhali, Sanjana; Joshi, Suresh M.

    2013-01-01

    Autonomous formation control of multi-agent dynamic systems has a number of applications that include ground-based and aerial robots and satellite formations. For air vehicles, formation flight ("flocking") has the potential to significantly increase airspace utilization as well as fuel efficiency. This presentation addresses two main problems in multi-agent formations: optimal role assignment to minimize the total cost (e.g., combined distance traveled by all agents); and maintaining formation geometry during flock motion. The Kuhn-Munkres ("Hungarian") algorithm is used for optimal assignment, and consensus-based leader-follower type control architecture is used to maintain formation shape despite the leader s independent movements. The methods are demonstrated by animated simulations.

  19. Advanced Approach of Multiagent Based Buoy Communication

    Science.gov (United States)

    Gricius, Gediminas; Drungilas, Darius; Andziulis, Arunas; Dzemydiene, Dale; Voznak, Miroslav; Kurmis, Mindaugas; Jakovlev, Sergej

    2015-01-01

    Usually, a hydrometeorological information system is faced with great data flows, but the data levels are often excessive, depending on the observed region of the water. The paper presents advanced buoy communication technologies based on multiagent interaction and data exchange between several monitoring system nodes. The proposed management of buoy communication is based on a clustering algorithm, which enables the performance of the hydrometeorological information system to be enhanced. The experiment is based on the design and analysis of the inexpensive but reliable Baltic Sea autonomous monitoring network (buoys), which would be able to continuously monitor and collect temperature, waviness, and other required data. The proposed approach of multiagent based buoy communication enables all the data from the costal-based station to be monitored with limited transition speed by setting different tasks for the agent-based buoy system according to the clustering information. PMID:26345197

  20. Improving Multi-Agent Systems Using Jason

    DEFF Research Database (Denmark)

    Vester, Steen; Boss, Niklas Skamriis; Jensen, Andreas Schmidt

    2011-01-01

    We describe the approach used to develop the multi-agent system of herders that competed as the Jason-DTU team at the Multi-Agent Programming Contest 2010. We also participated in 2009 with a system developed in the agentoriented programming language Jason which is an extension of AgentSpeak. We...... used the implementation from 2009 as a foundation and therefore much of the work done this year was on improving that implementation. We present a description which includes design and analysis of the system as well as the main features of our agent team strategy. In addition we discuss...... the technologies used to develop this system as well as our future goals in the area....

  1. Multiagent robotic systems' ambient light sensor

    Science.gov (United States)

    Iureva, Radda A.; Maslennikov, Oleg S.; Komarov, Igor I.

    2017-05-01

    Swarm robotics is one of the fastest growing areas of modern technology. Being subclass of multi-agent systems it inherits the main part of scientific-methodological apparatus of construction and functioning of practically useful complexes, which consist of rather autonomous independent agents. Ambient light sensors (ALS) are widely used in robotics. But speaking about swarm robotics, the technology which has great number of specific features and is developing, we can't help mentioning that its important to use sensors on each robot not only in order to help it to get directionally oriented, but also to follow light emitted by robot-chief or to help to find the goal easier. Key words: ambient light sensor, swarm system, multiagent system, robotic system, robotic complexes, simulation modelling

  2. Ontology-based multi-agent systems

    Energy Technology Data Exchange (ETDEWEB)

    Hadzic, Maja; Wongthongtham, Pornpit; Dillon, Tharam; Chang, Elizabeth [Digital Ecosystems and Business Intelligence Institute, Perth, WA (Australia)

    2009-07-01

    The Semantic web has given a great deal of impetus to the development of ontologies and multi-agent systems. Several books have appeared which discuss the development of ontologies or of multi-agent systems separately on their own. The growing interaction between agents and ontologies has highlighted the need for integrated development of these. This book is unique in being the first to provide an integrated treatment of the modeling, design and implementation of such combined ontology/multi-agent systems. It provides clear exposition of this integrated modeling and design methodology. It further illustrates this with two detailed case studies in (a) the biomedical area and (b) the software engineering area. The book is, therefore, of interest to researchers, graduate students and practitioners in the semantic web and web science area. (orig.)

  3. Multiagent-Based Model For ESCM

    Directory of Open Access Journals (Sweden)

    Delia MARINCAS

    2011-01-01

    Full Text Available Web based applications for Supply Chain Management (SCM are now a necessity for every company in order to meet the increasing customer demands, to face the global competition and to make profit. Multiagent-based approach is appropriate for eSCM because it shows many of the characteristics a SCM system should have. For this reason, we have proposed a multiagent-based eSCM model which configures a virtual SC, automates the SC activities: selling, purchasing, manufacturing, planning, inventory, etc. This model will allow a better coordination of the supply chain network and will increase the effectiveness of Web and intel-ligent technologies employed in eSCM software.

  4. Cooperative Sign Language Tutoring: A Multiagent Approach

    Science.gov (United States)

    Yıldırım, Ilker; Aran, Oya; Yolum, Pınar; Akarun, Lale

    Sign languages can be learned effectively only with frequent feedback from an expert in the field. The expert needs to watch a performed sign, and decide whether the sign has been performed well based on his/her previous knowledge about the sign. The expert's role can be imitated by an automatic system, which uses a training set as its knowledge base to train a classifier that can decide whether the performed sign is correct. However, when the system does not have enough previous knowledge about a given sign, the decision will not be accurate. Accordingly, we propose a multiagent architecture in which agents cooperate with each other to decide on the correct classification of performed signs. We apply different cooperation strategies and test their performances in varying environments. Further, through analysis of the multiagent system, we can discover inherent properties of sign languages, such as the existence of dialects.

  5. Multiagent pursuit-evasion games: Algorithms and experiments

    Science.gov (United States)

    Kim, Hyounjin

    Deployment of intelligent agents has been made possible through advances in control software, microprocessors, sensor/actuator technology, communication technology, and artificial intelligence. Intelligent agents now play important roles in many applications where human operation is too dangerous or inefficient. There is little doubt that the world of the future will be filled with intelligent robotic agents employed to autonomously perform tasks, or embedded in systems all around us, extending our capabilities to perceive, reason and act, and replacing human efforts. There are numerous real-world applications in which a single autonomous agent is not suitable and multiple agents are required. However, after years of active research in multi-agent systems, current technology is still far from achieving many of these real-world applications. Here, we consider the problem of deploying a team of unmanned ground vehicles (UGV) and unmanned aerial vehicles (UAV) to pursue a second team of UGV evaders while concurrently building a map in an unknown environment. This pursuit-evasion game encompasses many of the challenging issues that arise in operations using intelligent multi-agent systems. We cast the problem in a probabilistic game theoretic framework and consider two computationally feasible pursuit policies: greedy and global-max. We also formulate this probabilistic pursuit-evasion game as a partially observable Markov decision process and employ a policy search algorithm to obtain a good pursuit policy from a restricted class of policies. The estimated value of this policy is guaranteed to be uniformly close to the optimal value in the given policy class under mild conditions. To implement this scenario on real UAVs and UGVs, we propose a distributed hierarchical hybrid system architecture which emphasizes the autonomy of each agent yet allows for coordinated team efforts. We then describe our implementation on a fleet of UGVs and UAVs, detailing components such

  6. New Mechanism for Multiagent Extensible Negotiations

    OpenAIRE

    Aknine, Samir

    2014-01-01

    Multiagent negotiation mechanisms advise original solutions to several problems for which usual problem solving methods are inappropriate. Mainly negotiation models are based on agents' interactions through messages. Agents interact in order to reach an agreement for solving a specific problem. In this work, we study a new variant of negotiations, which has not yet been addressed in existing works. This negotiation form is denoted extensible negotiation. In contrast with current negotiation m...

  7. Guidance and Law Policies in Multiagent Systems

    Science.gov (United States)

    2007-03-17

    Lecture Notes in Computer Science , pages 128–147. Springer-Verlag, April 2004. [4] E. M. Clarke Jr., O. Grumberg, and D. A. Peled. Model...Artificial Intelligence: 15th Conference of the Canadian Society for Computational Studies of Intelligence (AI 2002), volume 2338 of Lecture Notes in Computer Science , pages...Engineering for Multi-Agent Systems IV, volume 3914 of Lecture Notes in Computer Science , pages 109–125.

  8. Multi-agent coordination algorithms for control of distributed energy resources in smart grids

    Science.gov (United States)

    Cortes, Andres

    Sustainable energy is a top-priority for researchers these days, since electricity and transportation are pillars of modern society. Integration of clean energy technologies such as wind, solar, and plug-in electric vehicles (PEVs), is a major engineering challenge in operation and management of power systems. This is due to the uncertain nature of renewable energy technologies and the large amount of extra load that PEVs would add to the power grid. Given the networked structure of a power system, multi-agent control and optimization strategies are natural approaches to address the various problems of interest for the safe and reliable operation of the power grid. The distributed computation in multi-agent algorithms addresses three problems at the same time: i) it allows for the handling of problems with millions of variables that a single processor cannot compute, ii) it allows certain independence and privacy to electricity customers by not requiring any usage information, and iii) it is robust to localized failures in the communication network, being able to solve problems by simply neglecting the failing section of the system. We propose various algorithms to coordinate storage, generation, and demand resources in a power grid using multi-agent computation and decentralized decision making. First, we introduce a hierarchical vehicle-one-grid (V1G) algorithm for coordination of PEVs under usage constraints, where energy only flows from the grid in to the batteries of PEVs. We then present a hierarchical vehicle-to-grid (V2G) algorithm for PEV coordination that takes into consideration line capacity constraints in the distribution grid, and where energy flows both ways, from the grid in to the batteries, and from the batteries to the grid. Next, we develop a greedy-like hierarchical algorithm for management of demand response events with on/off loads. Finally, we introduce distributed algorithms for the optimal control of distributed energy resources, i

  9. Coordination and composition in multi-agent systems

    NARCIS (Netherlands)

    Dastani, M.; Arbab, F.; Boer, F.S. de

    2005-01-01

    In this paper we describe a channel-based exogenous coordination language, called Reo, and discuss its application to multi-agent systems. Reo supports a specific notion of compositionality for multi-agent systems that enables the composition and coordination of both individual agents as well as mul

  10. A Dialogue Game Approach to Multi-Agent System Programming

    NARCIS (Netherlands)

    Lebbink, Henk-Jan; Witteman, Cilia; Meyer, John-Jules Ch.

    2005-01-01

    This paper approaches multi-agent system programming with dialogue games allowing the semantics of communicative acts to be a component in multi-agent architectures. We present a dialogue game for enquiry enabling agents to answer questions in a distributed fashion. In addition, we propose a reasoni

  11. Compositional verification of a multi-agent system for one-to-many negotiation

    NARCIS (Netherlands)

    Brazier, F.M.T.; Cornelissen, F.J.; Gustavsson, R.; Jonker, C.M.; Lindeberg, O.; Polak, B.; Treur, J.

    2004-01-01

    Verification of multi-agent systems hardly occurs in design practice. One of the difficulties is that required properties for a multi-agent system usually refer to multi-agent behaviour which has nontrivial dynamics. To constrain these multi-agent behavioural dynamics, often a form of organisational

  12. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    of different types of hierarchical networks. This is supplemented by a review of ring network design problems and a presentation of a model allowing for modeling most hierarchical networks. We use methods based on linear programming to design the hierarchical networks. Thus, a brief introduction to the various....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...... linear programming based methods is included. The thesis is thus suitable as a foundation for study of design of hierarchical networks. The major contribution of the thesis consists of seven papers which are included in the appendix. The papers address hierarchical network design and/or ring network...

  13. Multi-Agent Modeling in Managing Six Sigma Projects

    Directory of Open Access Journals (Sweden)

    K. Y. Chau

    2009-10-01

    Full Text Available In this paper, a multi-agent model is proposed for considering the human resources factor in decision making in relation to the six sigma project. The proposed multi-agent system is expected to increase the acccuracy of project prioritization and to stabilize the human resources service level. A simulation of the proposed multiagent model is conducted. The results show that a multi-agent model which takes into consideration human resources when making decisions about project selection and project team formation is important in enabling efficient and effective project management. The multi-agent modeling approach provides an alternative approach for improving communication and the autonomy of six sigma projects in business organizations.

  14. A review of norms and normative multiagent systems.

    Science.gov (United States)

    Mahmoud, Moamin A; Ahmad, Mohd Sharifuddin; Yusoff, Mohd Zaliman Mohd; Mustapha, Aida

    2014-01-01

    Norms and normative multiagent systems have become the subjects of interest for many researchers. Such interest is caused by the need for agents to exploit the norms in enhancing their performance in a community. The term norm is used to characterize the behaviours of community members. The concept of normative multiagent systems is used to facilitate collaboration and coordination among social groups of agents. Many researches have been conducted on norms that investigate the fundamental concepts, definitions, classification, and types of norms and normative multiagent systems including normative architectures and normative processes. However, very few researches have been found to comprehensively study and analyze the literature in advancing the current state of norms and normative multiagent systems. Consequently, this paper attempts to present the current state of research on norms and normative multiagent systems and propose a norm's life cycle model based on the review of the literature. Subsequently, this paper highlights the significant areas for future work.

  15. Accelerating Reinforcement Learning through Implicit Imitation

    CERN Document Server

    Boutilier, C; 10.1613/jair.898

    2011-01-01

    Imitation can be viewed as a means of enhancing learning in multiagent environments. It augments an agent's ability to learn useful behaviors by making intelligent use of the knowledge implicit in behaviors demonstrated by cooperative teachers or other more experienced agents. We propose and study a formal model of implicit imitation that can accelerate reinforcement learning dramatically in certain cases. Roughly, by observing a mentor, a reinforcement-learning agent can extract information about its own capabilities in, and the relative value of, unvisited parts of the state space. We study two specific instantiations of this model, one in which the learning agent and the mentor have identical abilities, and one designed to deal with agents and mentors with different action sets. We illustrate the benefits of implicit imitation by integrating it with prioritized sweeping, and demonstrating improved performance and convergence through observation of single and multiple mentors. Though we make some stringent ...

  16. The role of multi-agent systems in improving performance of manufacturing robotized cells

    Science.gov (United States)

    Sękala, A.; Ćwikła, G.; Kost, G.

    2015-11-01

    Present market conditions causes that modern control systems of robotized manufacturing cells should be characterized by the much greater degree of flexibility, selforganization and, above all, adaptability to emerging outer excitations. The phenomenon of information distribution is one of the most important features of modern control systems. In the paper is presented the approach, based on application of multi-agent systems, for supporting the operation of robotized manufacturing cells. The aim of this approach is to obtain the flexible response to outer excitations and preventing situations that might cause the delay of the production process. The presented paper includes description of the concept of an informatics system designed for controlling the work of production systems, including work cells. Such systems could operate independently if it would be equipped with the selforganization mechanism. It is possible in the case of the proposed multi-agent system. The implementation of the presented concept will follow the present analysis of the described concept. The advantage of the proposed concept is its hierarchical depiction that allows integrating different utilized informatics tools in one complex system. It allows preparing the final computer program.

  17. A multi-agent design for a pressurized water reactor (P.W.R.) control system; Modelisation multi-agents pour la conduite d'un reacteur a eau sous pression (REP)

    Energy Technology Data Exchange (ETDEWEB)

    Aimar-Lichtenberger, M. [Paris-11 Univ., 91 - Orsay (France)

    1999-01-01

    This PhD work is in keeping with the complex industrial process control. The starting point is the analysis of control principles in a Pressurized Water Reactor (P.W.R). In order to cope with the limits of the present control procedures, a new control organisation by objectives and means is defined. This functional organisation is based on the state approach and is characterized by the parallel management of control functions to ensure the continuous control of the installation essential variables. With regard to this complex system problematic, we search the most adapted computer modeling. We show that a multi-agent system approach brings an interesting answer to manage the distribution and parallelism of control decisions and tasks. We present a synthetic study of multi-agent systems and their application fields.The choice of a multi-agent approach proceeds with the design of an agent model. This model gains experiences from other applications. This model is implemented in a computer environment which combines the mechanisms of an object language with Prolog. We propose in this frame a multi-agent modeling of the control system where each function is represented by an agent. The agents are structured in a hierarchical organisation and deal with different abstraction levers of the problem. Following a prototype process, the validation is realized by an implementation and by a coupling to a reactor simulator. The essential contributions of an agent approach turn on the mastery of the system complexity, the openness, the robustness and the potentialities of human-machine cooperation. (author)

  18. Study and application of reinforcement learning based on DAI in cooperative strategy of robot soccer

    Institute of Scientific and Technical Information of China (English)

    GUO Qi; ZHANG Da-zhi; YANG Yong-tian

    2009-01-01

    A dynamic cooperation model of multi-agent is established by combining reinforcement learning with distributed artificial intelligence (DAI), in which the concept of individual optimization loses its meaning be-cause of the dependence of repayment on each agent itself and the choice of other agents. Utilizing the idea of DAI, the intellectual unit of each robot and the change of task and environment, each agent can make decisions independently and finish various complicated tasks by communication and reciprocation between each other. The method is superior to other reinforcement learning methods commonly used in the multi-agent system. It can im-prove the convergence velocity of reinforcement learning, decrease requirements of computer memory, and en-hance the capability of computing and logical ratiocinating for agent. The result of a simulated robot soccer match proves that the proposed cooperative strategy is valid.

  19. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...

  20. Multi-agents Based Modelling for Distribution Network Operation with Electric Vehicle Integration

    DEFF Research Database (Denmark)

    Hu, Junjie; Morais, Hugo; Zong, Yi

    2014-01-01

    Electric vehicles (EV) can become integral part of a smart grid because instead of just consuming power they are capable of providing valuable services to power systems. To integrate EVs smoothly into the power systems, a multi-agents system (MAS) with hierarchical organization structure...... is proposed in this paper. The proposed MAS system consists of three types of agents: distribution system operator agent (DSO agent), electric vehicle fleet operator agent (EV FO agent or alternatively called virtual power plant agent) and EV agent. A DSO agent belongs to the top level of the hierarchy...... and its role is to manage the distribution network safely by avoiding grid congestions and using congestion prices to coordinate the energy schedule of VPPs. VPP agents belong to the middle level and their roles are to manage the charge periods of the EVs. EV agents sit in the bottom level...

  1. A Supply Chain Architecture Based on Multi-agent Systems to Support Decentralized Collaborative Processes

    Science.gov (United States)

    Hernández, Jorge E.; Poler, Raúl; Mula, Josefa

    In a supply chain management context, the enterprise architecture concept to efficiently support the collaborative processes among the supply chain members involved has been evolving. Each supply chain has an organizational structure that describes the hierarchical relationships among its members, ranging from centralized to decentralized organizations. From a decentralized perspective, each supply chain member is able to identify collaborative and non collaborative partners and the kind of information to be exchanged to support negotiation processes. The same concepts of organizational structure and negotiation rules can be applied to a multi-agent system. This paper proposes a novel supply chain architecture to support decentralized collaborative processes in supply chains by considering a multi-agent-based system modeling approach.

  2. Modeling of a production system using the multi-agent approach

    Science.gov (United States)

    Gwiazda, A.; Sękala, A.; Banaś, W.

    2017-08-01

    The method that allows for the analysis of complex systems is a multi-agent simulation. The multi-agent simulation (Agent-based modeling and simulation - ABMS) is modeling of complex systems consisting of independent agents. In the case of the model of the production system agents may be manufactured pieces set apart from other types of agents like machine tools, conveyors or replacements stands. Agents are magazines and buffers. More generally speaking, the agents in the model can be single individuals, but you can also be defined as agents of collective entities. They are allowed hierarchical structures. It means that a single agent could belong to a certain class. Depending on the needs of the agent may also be a natural or physical resource. From a technical point of view, the agent is a bundle of data and rules describing its behavior in different situations. Agents can be autonomous or non-autonomous in making the decision about the types of classes of agents, class sizes and types of connections between elements of the system. Multi-agent modeling is a very flexible technique for modeling and model creating in the convention that could be adapted to any research problem analyzed from different points of views. One of the major problems associated with the organization of production is the spatial organization of the production process. Secondly, it is important to include the optimal scheduling. For this purpose use can approach multi-purposeful. In this regard, the model of the production process will refer to the design and scheduling of production space for four different elements. The program system was developed in the environment NetLogo. It was also used elements of artificial intelligence. The main agent represents the manufactured pieces that, according to previously assumed rules, generate the technological route and allow preprint the schedule of that line. Machine lines, reorientation stands, conveyors and transport devices also represent the

  3. Reinforcement Learning State-of-the-Art

    CERN Document Server

    Wiering, Marco

    2012-01-01

    Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade. The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together the...

  4. Verifying Multi-Agent Systems via Unbounded Model Checking

    Science.gov (United States)

    Kacprzak, M.; Lomuscio, A.; Lasica, T.; Penczek, W.; Szreter, M.

    2004-01-01

    We present an approach to the problem of verification of epistemic properties in multi-agent systems by means of symbolic model checking. In particular, it is shown how to extend the technique of unbounded model checking from a purely temporal setting to a temporal-epistemic one. In order to achieve this, we base our discussion on interpreted systems semantics, a popular semantics used in multi-agent systems literature. We give details of the technique and show how it can be applied to the well known train, gate and controller problem. Keywords: model checking, unbounded model checking, multi-agent systems

  5. Types and priorities of multi-agent system interactions

    Directory of Open Access Journals (Sweden)

    Martin Ngobye

    2010-07-01

    Full Text Available Multi-Agent Systems may be classified as containing No Direct Interactions, Simple Interactions or Complex, Conditional Interactions between agents. This paper argues and illustrates that models with simple interactions, even though possibly less fascinating for the Multi-agent system theorists than complex interaction models are, deserve more attention in the Multi-agent system community. Simple interaction models may contain social learning and reciprocal relationships. Maybe most importantly, Simple interaction models enable cross-scale connections by linking local to global actors in their local and global ‘life worlds’.

  6. Finite-time consensus of heterogeneous multi-agent systems

    Institute of Scientific and Technical Information of China (English)

    Zhu Ya-Kun; Guan Xin-Ping; Luo Xiao-Yuan

    2013-01-01

    We investigate the finite-time consensus problem for heterogeneous multi-agent systems composed of first-order and second-order agents.A novel continuous nonlinear distributed consensus protocol is constructed,and finite-time consensus criteria are obtained for the heterogeneous multi-agent systems.Compared with the existing results,the stationary and kinetic consensuses of the heterogeneous multi-agent systems can be achieved in a finite time respectively.Moreover,the leader can be a first-order or a second-order integrator agent.Finally,some simulation examples are employed to verify the efficiency of the theoretical results.

  7. Predictive Control of Networked Multiagent Systems via Cloud Computing.

    Science.gov (United States)

    Liu, Guo-Ping

    2017-01-18

    This paper studies the design and analysis of networked multiagent predictive control systems via cloud computing. A cloud predictive control scheme for networked multiagent systems (NMASs) is proposed to achieve consensus and stability simultaneously and to compensate for network delays actively. The design of the cloud predictive controller for NMASs is detailed. The analysis of the cloud predictive control scheme gives the necessary and sufficient conditions of stability and consensus of closed-loop networked multiagent control systems. The proposed scheme is verified to characterize the dynamical behavior and control performance of NMASs through simulations. The outcome provides a foundation for the development of cooperative and coordinative control of NMASs and its applications.

  8. Analysis of Bullying in Cooperative Multi-agent Systems’ Communications

    Directory of Open Access Journals (Sweden)

    Celia Gutiérrez

    2013-12-01

    Full Text Available Cooperative Multi-agent Systems frameworks do not include modules to test communications yet. The proposed framework incorporates robust analysis tools using IDKAnalysis2.0 to evaluate bullying effect in communications. The present work is based on ICARO-T. This platform follows the Adaptive Multi-agent Systems paradigm. Experimentation with ICARO-T includes two deployments: the equitative and the authoritative. Results confirm the usefulness of the analysis tools when exporting to Cooperative Multi-agent Systems that use different configurations. Besides, ICARO-T is provided with new functionality by a set of tools for communication analysis.

  9. Early childhood numeracy in a multiage setting

    Science.gov (United States)

    Wood, Karen; Frid, Sandra

    2005-10-01

    This research is a case study examining numeracy teaching and learning practices in an early childhood multiage setting with Pre-Primary to Year 2 children. Data were collected via running records, researcher reflection notes, and video and audio recordings. Video and audio transcripts were analysed using a mathematical discourse and social interactions coding system designed by MacMillan (1998), while the running records and reflection notes contributed to descriptions of the children's interactions with each other and with the teachers. Teachers used an `assisted performance' approach to instruction that supported problem solving and inquiry processes in mathematics activities, and this, combined with a child-centred pedagogy and specific values about community learning, created a learning environment designed to stimulate and foster learning. The mathematics discourse analysis showed a use of explanatory language in mathematics discourse, and this language supported scaffolding among children for new mathematics concepts. These and other interactions related to peer sharing, tutoring and regulation also emerged as key aspects of students' learning practices. However, the findings indicated that multiage grouping alone did not support learning. Rather, effective learning was dependent upon the teacher's capacities to develop productive discussion among children, as well as implement developmentally appropriate curricula that addressed the needs of the different children.

  10. Proposal for multi-agency facility : High Desert Interagency Partnership

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This is a proposal to construct a multi-agency facility to house the High Desert Interagency Partnership. The facility would be on federally owned land in Hines,...

  11. Interactions in multiagent systems fairness, social optimality and individual rationality

    CERN Document Server

    Hao, Jianye

    2016-01-01

    This book mainly aims at solving the problems in both cooperative and competitive multi-agent systems (MASs), exploring aspects such as how agents can effectively learn to achieve the shared optimal solution based on their local information and how they can learn to increase their individual utility by exploiting the weakness of their opponents. The book describes fundamental and advanced techniques of how multi-agent systems can be engineered towards the goal of ensuring fairness, social optimality, and individual rationality; a wide range of further relevant topics are also covered both theoretically and experimentally. The book will be beneficial to researchers in the fields of multi-agent systems, game theory and artificial intelligence in general, as well as practitioners developing practical multi-agent systems.

  12. Multi-Agent Information Classification Using Dynamic Acquaintance Lists.

    Science.gov (United States)

    Mukhopadhyay, Snehasis; Peng, Shengquan; Raje, Rajeev; Palakal, Mathew; Mostafa, Javed

    2003-01-01

    Discussion of automated information services focuses on information classification and collaborative agents, i.e. intelligent computer programs. Highlights include multi-agent systems; distributed artificial intelligence; thesauri; document representation and classification; agent modeling; acquaintances, or remote agents discovered through…

  13. Formalizing Theatrical Performances Using Multi-Agent Organizations

    DEFF Research Database (Denmark)

    Jensen, Andreas Schmidt; Spurkeland, Johannes Svante; Villadsen, Jørgen

    2013-01-01

    Theatrical performances usually follow strict scripts and actors are not allowed to deviate. A Danish theatrical group, Theater 770◦ Celsius, has invented a new method called In Real Life, in which only certain events in the storyline are specified and the actors are supposed to improvise to reac...... these events. The method bears a resemblance to multi-agent systems and we show how it can be formalized using the multi-agent organizational model OperA....

  14. A dialogue game approach to multi-agent system programming

    OpenAIRE

    Lebbink, Henk-Jan; Witteman, Cilia; Meyer, John-Jules Ch.

    2004-01-01

    This paper approaches multi-agent system programming with dialogue games allowing the semantics of communicative acts to be a component in multi-agent architectures. We present a dialogue game for enquiry enabling agents to answer questions in a distributed fashion. In addition, we propose a reasoning game that defines when agents are allowed to make decisions, in the current case, decisions to accept to believe propositions. These games are brought together in a deliberation cycle and are im...

  15. Integrating Ontologies into Distributed Multi-Agent System

    Directory of Open Access Journals (Sweden)

    Khaoula ADDAKIRI

    2013-10-01

    Full Text Available Multi-agent systems have proven to be a powerful technology because of their many advantages in distributed and complex environments however its disadvantage is that is lacks the interconnection with semantic web standards. In this paper we propose a new approach to enhance the interoperability and cooperation of Multi-Agent System (MAS using semantic web technology (such as RDF and OWL and we present a proposal for modeling agent based system using Unified Modeling Language.

  16. Integrating Ontologies into Distributed Multi-Agent System

    OpenAIRE

    Addakiri, Khaoula; Mohamed BAHAJ

    2013-01-01

    Multi-agent systems have proven to be a powerful technology because of their many advantages in distributed and complex environments however its disadvantage is that is lacks the interconnection with semantic web standards. In this paper we propose a new approach to enhance the interoperability and cooperation of Multi-Agent System (MAS) using semantic web technology (such as RDF and OWL) and we present a proposal for modeling agent based system using Unified Modeling Language.

  17. Dynamic optimization for multi-agent systems with external disturbances

    Institute of Scientific and Technical Information of China (English)

    Xinghu WANG; Peng YI; Yiguang HONG

    2014-01-01

    This paper studies the dynamic optimization problem for multi-agent systems in the presence of external disturbances. Different from the existing distributed optimization results, we formulate an optimization problem of continuous-time multi-agent systems with time-varying disturbance generated by an exosystem. Based on internal model and Lyapunov-based method, a distributed design is proposed to achieve the optimization. Finally, an example is given to illustrate the proposed optimization design.

  18. First Generation Multi-Agent Models and Their Upgrades

    OpenAIRE

    Andras Vag

    2004-01-01

    Multi-agent systems consist of interactive and independent agents of different kinds in a "world" of the computers. The key issue of multi-agent modelling is its ability to produce emergent phenomena at macro level from "micro-behaviour". For now this approach became a widely used methodology in socio-economics and ecology. This paper presents three famous first generation models and then drafts some of their upgrades, especially the agent-based computational economics, the spatial planning a...

  19. Research and Application of Multi-Agent Technology

    Institute of Scientific and Technical Information of China (English)

    Li Wei; Zhang Fengming

    2006-01-01

    This paper firstly introduces the background and conception of Agent and Multi-Agent technology and compares the frameworks of Agent system and MAS. Analyzing the framework of Agent secondly. Then explaining the communication language used in the Multi-Agent society where knowledge communication plays a key role among Agents. Finally, some applications are enumerated and the future direction of this technology is prospected.

  20. An approach to model based testing of multiagent systems.

    Science.gov (United States)

    Ur Rehman, Shafiq; Nadeem, Aamer

    2015-01-01

    Autonomous agents perform on behalf of the user to achieve defined goals or objectives. They are situated in dynamic environment and are able to operate autonomously to achieve their goals. In a multiagent system, agents cooperate with each other to achieve a common goal. Testing of multiagent systems is a challenging task due to the autonomous and proactive behavior of agents. However, testing is required to build confidence into the working of a multiagent system. Prometheus methodology is a commonly used approach to design multiagents systems. Systematic and thorough testing of each interaction is necessary. This paper proposes a novel approach to testing of multiagent systems based on Prometheus design artifacts. In the proposed approach, different interactions between the agent and actors are considered to test the multiagent system. These interactions include percepts and actions along with messages between the agents which can be modeled in a protocol diagram. The protocol diagram is converted into a protocol graph, on which different coverage criteria are applied to generate test paths that cover interactions between the agents. A prototype tool has been developed to generate test paths from protocol graph according to the specified coverage criterion.

  1. An Approach to Model Based Testing of Multiagent Systems

    Directory of Open Access Journals (Sweden)

    Shafiq Ur Rehman

    2015-01-01

    Full Text Available Autonomous agents perform on behalf of the user to achieve defined goals or objectives. They are situated in dynamic environment and are able to operate autonomously to achieve their goals. In a multiagent system, agents cooperate with each other to achieve a common goal. Testing of multiagent systems is a challenging task due to the autonomous and proactive behavior of agents. However, testing is required to build confidence into the working of a multiagent system. Prometheus methodology is a commonly used approach to design multiagents systems. Systematic and thorough testing of each interaction is necessary. This paper proposes a novel approach to testing of multiagent systems based on Prometheus design artifacts. In the proposed approach, different interactions between the agent and actors are considered to test the multiagent system. These interactions include percepts and actions along with messages between the agents which can be modeled in a protocol diagram. The protocol diagram is converted into a protocol graph, on which different coverage criteria are applied to generate test paths that cover interactions between the agents. A prototype tool has been developed to generate test paths from protocol graph according to the specified coverage criterion.

  2. Regulated open multi-agent systems (ROMAS) a multi-agent approach for designing normative open systems

    CERN Document Server

    Garcia, Emilia; Botti, Vicente

    2015-01-01

    Addressing the open problem of engineering normative open systems using the multi-agent paradigm, normative open systems are explained as systems in which heterogeneous and autonomous entities and institutions coexist in a complex social and legal framework that can evolve to address the different and often conflicting objectives of the many stakeholders involved. Presenting  a software engineering approach which covers both the analysis and design of these kinds of systems, and which deals with the open issues in the area, ROMAS (Regulated Open Multi-Agent Systems) defines a specific multi-agent architecture, meta-model, methodology and CASE tool. This CASE tool is based on Model-Driven technology and integrates the graphical design with the formal verification of some properties of these systems by means of model checking techniques. Utilizing tables to enhance reader insights into the most important requirements for designing normative open multi-agent systems, the book also provides a detailed and easy t...

  3. Planning of Autonomous Multi-agent Intersection

    Directory of Open Access Journals (Sweden)

    Viksnin Ilya I.

    2016-01-01

    Full Text Available In this paper, we propose a traffic management system with agents acting on behalf autonomous vehicle at the crossroads. Alternatively to existing solutions based on usage of semiautonomous control systems with the control unit, proposed in this paper algorithm apply the principles of decentralized multi-agent control. Agents during their collaboration generate intersection plan and determinate the optimal order of road intersection for a given criterion based on the exchange of information about them and their environment. The paper contains optimization criteria for possible routes selection and experiments that perform in order to estimate the proposed model. Experiment results show that this model can significantly reduce traffic density compared to the traditional traffic management systems. Moreover, the proposed algorithm efficiency increases with road traffic density. Furthermore, the availability of control unit in the system significantly reduces the negative impact of possible failures and hacker attacks.

  4. Bipartite flocking for multi-agent systems

    Science.gov (United States)

    Fan, Ming-Can; Zhang, Hai-Tao; Wang, Miaomiao

    2014-09-01

    This paper addresses the bipartite flock control problem where a multi-agent system splits into two clusters upon internal or external excitations. Using structurally balanced signed graph theory, LaSalle's invariance principle and Barbalat's Lemma, we prove that the proposed algorithm guarantees a bipartite flocking behavior. In each of the two disjoint clusters, all individuals move with the same direction. Meanwhile, every pair of agents in different clusters moves with opposite directions. Moreover, all agents in the two separated clusters approach a common velocity magnitude, and collision avoidance among all agents is ensured as well. Finally, the proposed bipartite flock control method is examined by numerical simulations. The bipartite flocking motion addressed by this paper has its references in both natural collective motions and human group behaviors such as predator-prey and panic escaping scenarios.

  5. Autonomic Management for Multi-agent Systems

    CERN Document Server

    Salih, Nadir K; Viju, PG K; Mohamed, Abdelmotalib A

    2011-01-01

    Autonomic computing is a computing system that can manage itself by self-configuration, self-healing, self-optimizing and self-protection. Researchers have been emphasizing the strong role that multi agent systems can play progressively towards the design and implementation of complex autonomic systems. The important of autonomic computing is to create computing systems capable of managing themselves to a far greater extent than they do today. With the nature of autonomy, reactivity, sociality and pro-activity, software agents are promising to make autonomic computing system a reality. This paper mixed multi-agent system with autonomic feature that completely hides its complexity from users/services. Mentioned Java Application Development Framework as platform example of this environment, could applied to web services as front end to users. With multi agent support it also provides adaptability, intelligence, collaboration, goal oriented interactions, flexibility, mobility and persistence in software systems

  6. Modeling Infection with Multi-agent Dynamics

    CERN Document Server

    Dong, Wen; Pentland, Alex "Sandy"

    2012-01-01

    Developing the ability to comprehensively study infections in small populations enables us to improve epidemic models and better advise individuals about potential risks to their health. We currently have a limited understanding of how infections spread within a small population because it has been difficult to closely track an infection within a complete community. The paper presents data closely tracking the spread of an infection centered on a student dormitory, collected by leveraging the residents' use of cellular phones. The data are based on daily symptom surveys taken over a period of four months and proximity tracking through cellular phones. We demonstrate that using a Bayesian, discrete-time multi-agent model of infection to model real-world symptom reports and proximity tracking records gives us important insights about infec-tions in small populations.

  7. WEB SERVICES COMPOSING BY MULTIAGENT NEGOTIATION

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Composing web services is gained daily attention in Service Oriented Computing.It includes the dynamic discovery,interaction and coordination of agent-based semantic web services.The authors first follow Function Ontology and Automated Mechanism Design for service agents aggregating.Then the problem is formulated but it is ineffective to solve it from the traditional global view.Because the complexity is NP-complete and it is difficult or even impossible to get some personal information.This paper provides a multi-agent negotiation idea in which each participant negotiates under the condition of its reservation payoff being satisfied.Numerical experiment is given and well evaluates the negotiation.

  8. Multi-agent sequential hypothesis testing

    KAUST Repository

    Kim, Kwang-Ki K.

    2014-12-15

    This paper considers multi-agent sequential hypothesis testing and presents a framework for strategic learning in sequential games with explicit consideration of both temporal and spatial coordination. The associated Bayes risk functions explicitly incorporate costs of taking private/public measurements, costs of time-difference and disagreement in actions of agents, and costs of false declaration/choices in the sequential hypothesis testing. The corresponding sequential decision processes have well-defined value functions with respect to (a) the belief states for the case of conditional independent private noisy measurements that are also assumed to be independent identically distributed over time, and (b) the information states for the case of correlated private noisy measurements. A sequential investment game of strategic coordination and delay is also discussed as an application of the proposed strategic learning rules.

  9. MAGMA: a multiagent architecture for metaheuristics.

    Science.gov (United States)

    Milano, Michela; Roli, Andrea

    2004-04-01

    In this work, we introduce a multiagent architecture called the MultiAGent Metaheuristic Architecture (MAGMA) conceived as a conceptual and practical framework for metaheuristic algorithms. Metaheuristics can be seen as the result of the interaction among different kinds of agents: The basic architecture contains three levels, each hosting one or more agents. Level-0 agents build solutions, level-1 agents improve solutions, and level-2 agents provide the high level strategy. In this framework, classical metaheuristic algorithms can be smoothly accommodated and extended. The basic three level architecture can be enhanced with the introduction of a fourth level of agents (level-3 agents) coordinating lower level agents. With this additional level, MAGMA can also describe, in a uniform way, cooperative search and, in general, any combination of metaheuristics. We describe the entire architecture, the structure of agents in each level in terms of tuples, and the structure of their coordination as a labeled transition system. We propose this perspective with the aim to achieve a better and clearer understanding of metaheuristics, obtain hybrid algorithms, suggest guidelines for a software engineering-oriented implementation and for didactic purposes. Some specializations of the general architecture will be provided in order to show that existing metaheuristics [e.g., greedy randomized adaptive procedure (GRASP), ant colony optimization (ACO), iterated local search (ILS), memetic algorithms (MAs)] can be easily described in our framework. We describe cooperative search and large neighborhood search (LNS) in the proposed framework exploiting level-3 agents. We show also that a simple hybrid algorithm, called guided restart ILS, can be easily conceived as a combination of existing components in our framework.

  10. A Class of Uncontrollable Diffusively Coupled Multiagent Systems with Multichain Topologies

    NARCIS (Netherlands)

    Cao, Ming; Zhang, Shuo; Camlibel, M. Kanat

    2013-01-01

    We construct systematically a class of uncontrollable diffusively coupled multiagent systems with a single leader and multichain topologies. For studying the controllability of diffusively coupled multiagent systems, such identified uncontrollable systems serve as counterexamples that prove the need

  11. A Class of Uncontrollable Diffusively Coupled Multiagent Systems with Multichain Topologies

    NARCIS (Netherlands)

    Cao, Ming; Zhang, Shuo; Camlibel, M. Kanat

    We construct systematically a class of uncontrollable diffusively coupled multiagent systems with a single leader and multichain topologies. For studying the controllability of diffusively coupled multiagent systems, such identified uncontrollable systems serve as counterexamples that prove the need

  12. Improving Multi agent Systems Based on Reinforcement Learning and Case Base Reasoning

    Directory of Open Access Journals (Sweden)

    Sara Esfandiari

    2012-01-01

    Full Text Available In this paper, a new algorithm based on case base reasoning and reinforcement learning is proposed to increase the rate convergence of the Selfish Q-Learning algorithms in multi-agent systems. In the propose method, we investigate how making improved action selection in reinforcement learning (RL algorithm. In the proposed method, the new combined model using case base reasoning systems and a new optimized function has been proposed to select the action, which has led to an increase in algorithms based on Selfish Q-learning. The algorithm mentioned has been used for solving the problem of cooperative Markovs games as one of the models of Markov based multi-agent systems. The results of experiments on two ground have shown that the proposed algorithm perform better than the existing algorithms in terms of speed and accuracy of reaching the optimal policy.

  13. Multi-agent coordination strategy estimation method based on control domain

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    For estimation group competition and multiagent coordination strategy, this paper introduces a notion based on multiagent group. According to the control domain, it analyzes the multiagent strategy during competi tion in the macroscopic. It has been adopted in robot soccer and result enunciates that our method does not de pend on competition result. It can objectively quantitatively estimate coordination strategy.

  14. From Teachers' Perspectives: The Social and Psychological Benefits of Multiage Elementary Classrooms.

    Science.gov (United States)

    Marshak, David

    This paper on multiage classrooms provides first steps toward a systemic understanding of the defining qualities of multiage classrooms and, from teachers' perspectives, the benefits of such classrooms for students, teachers, and parents. The multiage classroom movement in elementary schools is viewed as not just restructuring, but also as the…

  15. Norm regulation in collaborative virtual environments by normative multi-agent systems

    NARCIS (Netherlands)

    Stam, Sven

    2011-01-01

    Different types of research have been done on multi-agent systems regarding normative systems. This research addresses the enforcement of norms by a multi-agent system. More specifically this thesis investigates the question whether or not it is possible for a normative multi-agent system to regulat

  16. REINFORCED COMPOSITE PANEL

    DEFF Research Database (Denmark)

    2003-01-01

    A composite panel having front and back faces, the panel comprising facing reinforcement, backing reinforcement and matrix material binding to the facing and backing reinforcements, the facing and backing reinforcements each independently comprising one or more reinforcing sheets, the facing...... by matrix material, the facing and backing reinforcements being interconnected to resist out-of-plane relative movement. The reinforced composite panel is useful as a barrier element for shielding structures, equipment and personnel from blast and/or ballistic impact damage....

  17. REINFORCED COMPOSITE PANEL

    DEFF Research Database (Denmark)

    2003-01-01

    A composite panel having front and back faces, the panel comprising facing reinforcement, backing reinforcement and matrix material binding to the facing and backing reinforcements, the facing and backing reinforcements each independently comprising one or more reinforcing sheets, the facing rein...... by matrix material, the facing and backing reinforcements being interconnected to resist out-of-plane relative movement. The reinforced composite panel is useful as a barrier element for shielding structures, equipment and personnel from blast and/or ballistic impact damage....

  18. Reinforcement Learning for a New Piano Mover

    Directory of Open Access Journals (Sweden)

    Yuko Ishiwaka

    2005-08-01

    Full Text Available We attempt to achieve corporative behavior of autonomous decentralized agents constructed via Q-Learning, which is a type of reinforcement learning. As such, in the present paper, we examine the piano mover's problem. We propose a multi-agent architecture that has a training agent, learning agents and intermediate agent. Learning agents are heterogeneous and can communicate with each other. The movement of an object with three kinds of agent depends on the composition of the actions of the learning agents. By learning its own shape through the learning agents, avoidance of obstacles by the object is expected. We simulate the proposed method in a two-dimensional continuous world. Results obtained in the present investigation reveal the effectiveness of the proposed method.

  19. Reinforcement Learning for a New Piano Mover

    Directory of Open Access Journals (Sweden)

    Yuko Ishiwaka

    2005-08-01

    Full Text Available We attempt to achieve corporative behavior of autonomous decentralized agents constructed via Q-Learning, which is a type of reinforcement learning. As such, in the present paper, we examine the piano mover's problem. We propose a multi-agent architecture that has a training agent, learning agents and intermediate agent. Learning agents are heterogeneous and can communicate with each other. The movement of an object with three kinds of agent depends on the composition of the actions of the learning agents. By learning its own shape through the learning agents, avoidance of obstacles by the object is expected. We simulate the proposed method in a two-dimensional continuous world. Results obtained in the present investigation reveal the effectiveness of the proposed method.

  20. Hierarchical auxetic mechanical metamaterials.

    Science.gov (United States)

    Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I; Azzopardi, Keith M; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N

    2015-02-11

    Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.

  1. Introduction into Hierarchical Matrices

    KAUST Repository

    Litvinenko, Alexander

    2013-12-05

    Hierarchical matrices allow us to reduce computational storage and cost from cubic to almost linear. This technique can be applied for solving PDEs, integral equations, matrix equations and approximation of large covariance and precision matrices.

  2. Hierarchical Auxetic Mechanical Metamaterials

    Science.gov (United States)

    Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I.; Azzopardi, Keith M.; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N.

    2015-02-01

    Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.

  3. Applied Bayesian Hierarchical Methods

    CERN Document Server

    Congdon, Peter D

    2010-01-01

    Bayesian methods facilitate the analysis of complex models and data structures. Emphasizing data applications, alternative modeling specifications, and computer implementation, this book provides a practical overview of methods for Bayesian analysis of hierarchical models.

  4. Programming with Hierarchical Maps

    DEFF Research Database (Denmark)

    Ørbæk, Peter

    This report desribes the hierarchical maps used as a central data structure in the Corundum framework. We describe its most prominent features, ague for its usefulness and briefly describe some of the software prototypes implemented using the technology....

  5. Catalysis with hierarchical zeolites

    DEFF Research Database (Denmark)

    Holm, Martin Spangsberg; Taarning, Esben; Egeblad, Kresten

    2011-01-01

    Hierarchical (or mesoporous) zeolites have attracted significant attention during the first decade of the 21st century, and so far this interest continues to increase. There have already been several reviews giving detailed accounts of the developments emphasizing different aspects of this research...... topic. Until now, the main reason for developing hierarchical zeolites has been to achieve heterogeneous catalysts with improved performance but this particular facet has not yet been reviewed in detail. Thus, the present paper summaries and categorizes the catalytic studies utilizing hierarchical...... zeolites that have been reported hitherto. Prototypical examples from some of the different categories of catalytic reactions that have been studied using hierarchical zeolite catalysts are highlighted. This clearly illustrates the different ways that improved performance can be achieved with this family...

  6. Basal Reinforced Piled Embankments

    NARCIS (Netherlands)

    Van Eekelen, S.J.M.

    2015-01-01

    A basal reinforced piled embankment consists of a reinforced embankment on a pile foundation. The reinforcement consists of one or more horizontal layers of geosynthetic reinforcement (GR) installed at the base of the embankment. The design of the GR is the subject of this thesis. A basal reinforce

  7. Basal Reinforced Piled Embankments

    NARCIS (Netherlands)

    Van Eekelen, S.J.M.

    2015-01-01

    A basal reinforced piled embankment consists of a reinforced embankment on a pile foundation. The reinforcement consists of one or more horizontal layers of geosynthetic reinforcement (GR) installed at the base of the embankment. The design of the GR is the subject of this thesis. A basal reinforce

  8. Analysis of the Pricing Process in Electricity Market using Multi-Agent Model

    Science.gov (United States)

    Shimomura, Takahiro; Saisho, Yuichi; Fujii, Yasumasa; Yamaji, Kenji

    Many electric utilities world-wide have been forced to change their ways of doing business, from vertically integrated mechanisms to open market systems. We are facing urgent issues about how we design the structures of power market systems. In order to settle down these issues, many studies have been made with market models of various characteristics and regulations. The goal of modeling analysis is to enrich our understanding of fundamental process that may appear. However, there are many kinds of modeling methods. Each has drawback and advantage about validity and versatility. This paper presents two kinds of methods to construct multi-agent market models. One is based on game theory and another is based on reinforcement learning. By comparing the results of the two methods, they can advance in validity and help us figure out potential problems in electricity markets which have oligopolistic generators, demand fluctuation and inelastic demand. Moreover, this model based on reinforcement learning enables us to consider characteristics peculiar to electricity markets which have plant unit characteristics, seasonable and hourly demand fluctuation, real-time regulation market and operating reserve market. This model figures out importance of the share of peak-load-plants and the way of designing operating reserve market.

  9. Survey on Multi-Agent Collaborative Problem Solving%多Agent合作求解

    Institute of Scientific and Technical Information of China (English)

    张新良; 石纯一

    2003-01-01

    Multi-Agent Collaborative Problem Solving is one basic issue of the research of Multi-Agent Systen(MAS). In this paper we summarize some research work of Multi-Agent collaborative problem solving,expound thecharacteristic of Multi-Agnet collaborative problem solving,Model of Multi-Agent collaborative problem solving,pro-cess of solving、the application field of Multi-Agent collaborative problem solving and some challenge. Especially wediscuss the main models ,introduce the representative model including joint-intention,joint-commitment ,shared plan.

  10. Multiagent Work Practice Simulation: Progress and Challenges

    Science.gov (United States)

    Clancey, William J.; Sierhuis, Maarten; Shaffe, Michael G. (Technical Monitor)

    2001-01-01

    Modeling and simulating complex human-system interactions requires going beyond formal procedures and information flows to analyze how people interact with each other. Such work practices include conversations, modes of communication, informal assistance, impromptu meetings, workarounds, and so on. To make these social processes visible, we have developed a multiagent simulation tool, called Brahms, for modeling the activities of people belonging to multiple groups, situated in a physical environment (geographic regions, buildings, transport vehicles, etc.) consisting of tools, documents, and a computer system. We are finding many useful applications of Brahms for system requirements analysis, instruction, implementing software agents, and as a workbench for relating cognitive and social theories of human behavior. Many challenges remain for representing work practices, including modeling: memory over multiple days, scheduled activities combining physical objects, groups, and locations on a timeline (such as a Space Shuttle mission), habitat vehicles with trajectories (such as the Shuttle), agent movement in 3D space (e.g., inside the International Space Station), agent posture and line of sight, coupled movements (such as carrying objects), and learning (mimicry, forming habits, detecting repetition, etc.).

  11. Continuum deformation of multi-agent systems

    CERN Document Server

    Rastgoftar, Hossein

    2016-01-01

    This monograph presents new algorithms for formation control of multi-agent systems (MAS) based on principles of continuum mechanics. Beginning with an overview of traditional methods, the author then introduces an innovative new approach whereby agents of an MAS are considered as particles in a continuum evolving in ℝn whose desired configuration is required to satisfy an admissible deformation function. The necessary theory and its validation on a mobile-agent-based swarm test bed are considered for two primary tasks: homogeneous transformation of the MAS and deployment of a random distribution of agents on a desired configuration. The framework for this model is based on homogeneous transformations for the evolution of an MAS under no inter-agent communication, local inter-agent communication, and intelligent perception by agents. Different communication protocols for MAS evolution, the robustness of tracking of a desired motion by an MAS evolving in ℝn, and the effect of communication delays in an MAS...

  12. Control Prosody using Multi-Agent System

    Directory of Open Access Journals (Sweden)

    Kenji MATSUI

    2014-03-01

    Full Text Available Persons who have undergone a laryngectomy have a few options to partially restore speech but no completely satisfactory device. Even though the use of an electrolarynx (EL is the easiest way for a patient to produce speech, it does not produce a natural tone and appearance is far from normal. Because of that and the fact that none of them are hands-free, the feasibility of using a motion sensor to replace a conventional EL user interface has been explored. A mobile device motion sensor with multi-agent platform has been used to investigate on/off and pitch frequency control capability. A very small battery operated ARM-based control unit has also been developed to evaluate the motion sensor based user-interface. This control unit is placed on the wrist and the vibration device against the throat using support bandage. Two different conversion methods were used for the forearm tilt angle to pitch frequency conversion: linear mapping method and F0 template-based method A perceptual evaluation has been performed with two well-trained normal speakers and ten subjects. The results of the evaluation study showed that both methods are able to produce better speech quality in terms of the naturalness.

  13. Multi-Agent Only-Knowing Revisited

    CERN Document Server

    Belle, Vaishak

    2010-01-01

    Levesque introduced the notion of only-knowing to precisely capture the beliefs of a knowledge base. He also showed how only-knowing can be used to formalize non-monotonic behavior within a monotonic logic. Despite its appeal, all attempts to extend only-knowing to the many agent case have undesirable properties. A belief model by Halpern and Lakemeyer, for instance, appeals to proof-theoretic constructs in the semantics and needs to axiomatize validity as part of the logic. It is also not clear how to generalize their ideas to a first-order case. In this paper, we propose a new account of multi-agent only-knowing which, for the first time, has a natural possible-world semantics for a quantified language with equality. We then provide, for the propositional fragment, a sound and complete axiomatization that faithfully lifts Levesque’s proof theory to the many agent case. We also discuss comparisons to the earlier approach by Halpern and Lakemeyer.

  14. Applying Activity Theory in Multiagency Settings

    Directory of Open Access Journals (Sweden)

    Daniels H.,

    2016-12-01

    Full Text Available In this paper I explore the extent to which two approaches to the social formation of mind are compatible and may be used to enrich and extend each other. These are: Activity Theory (AT as derived from the work of the early Russian psychologists, Vygotsky and Leontiev, and the work of the sociologist Basil Bernstein. The purpose is to show how Bernstein provides a language of description which allows Vygotsky’s account of social formation of mind to be extended and enhanced through an understanding of the sociological processes which form specific modalities of pedagogic practice and their specialized scientific concepts. The two approaches engage with a common theme namely the social shaping of consciousness, from different perspectives and yet as Bernstein acknowledges both develop many of their core assumptions from the work of Marx and the French school of early twentieth century sociology. The work of the Russian linguist is also be used to further nuance the argument applied in multiagency settings.

  15. Epistemic planning for single- and multi-agent systems

    DEFF Research Database (Denmark)

    Bolander, Thomas; Andersen, Mikkel Birkegaard

    2011-01-01

    . In planning, partial observability gives rise to an uncertainty about the world. For single-agent domains, this uncertainty can come from incomplete knowledge of the starting situation and from the nondeterminism of actions. In multi-agent domains, an additional uncertainty arises from the fact that other...... the specification of a more complex class of planning domains, than those simply concerned with simple facts about the world. We show how to model multi-agent planning problems using Kripke-models for representing world states, and event models for representing actions. Our mechanism makes use of slight...... observability, nondeterminism, knowledge and multiple agents. Finally, we show epistemic planning to be decidable in the single-agent case, but only semi-decidable in the multi-agent case....

  16. Robust consensus of multi-agent systems with noise

    Institute of Scientific and Technical Information of China (English)

    WANG Lin; LIU ZhiXin

    2009-01-01

    The consensus problem of multi-agent systems has attracted wide attention from researchers in recent years, following the initial work of Jadbabaie et al. on the analysis of a simplified Vicsek model. While the original Vicsek model contains noise effects, almost all the existing theoretical results on consensus problem, however, do not take the noise effects into account. The purpose of this paper is to initiate a study of the consensus problems under noise disturbances. First, the class of multi-agent systems under study is transformed into a general time-varying system with noise. Then, for such a system, the equivalent relationships are established among (ⅰ) robust consensus, (ⅱ) the positivity of the second smallest eigenvalue of a weighted Laplacian matrix, and (ⅲ) the joint connectivity of the associated dynamical neighbor graphs. Finally, this basic equivalence result is shown to be applicable to several classes of concrete multi-agent models with noise.

  17. Bipartite Consensus Control of Multiagent Systems on Coopetition Networks

    Directory of Open Access Journals (Sweden)

    Jiangping Hu

    2014-01-01

    Full Text Available Cooperation and competition are two typical interactional relationships in natural and engineering networked systems. Some complex behaviors can emerge through local interactions within the networked systems. This paper focuses on the coexistence of competition and cooperation (i.e., coopetition at the network level and, simultaneously, the collective dynamics on such coopetition networks. The coopetition network is represented by a directed signed graph. The collective dynamics on the coopetition network is described by a multiagent system. We investigate two bipartite consensus strategies for multiagent systems such that all the agents converge to a final state characterized by identical modulus but opposite sign. Under a weak connectivity assumption that the coopetition network has a spanning tree, some sufficient conditions are derived for bipartite consensus of multiagent systems with the help of a structural balance theory. Finally, simulation results are provided to demonstrate the bipartite consensus formation.

  18. Review of Active and Reactive Power Sharing Strategies in Hierarchical Controlled Microgrids

    DEFF Research Database (Denmark)

    Han, Yang; Li, Hong; Shen, Pan

    2017-01-01

    Microgrids consist of multiple parallel-connected distributed generation (DG) units with coordinated control strategies, which are able to operate in both grid-connected and islanded mode. Microgrids are attracting more and more attention since they can alleviate the stress of main transmission...... strategies are utilized as supplements of the conventional droop controls and virtual impedance methods. The improved hierarchical control approaches such as the algorithms based on graph theory, multi-agent system, the gain scheduling method and predictive control have been proposed to achieve proper...

  19. Hierarchical robot control structure and Newton's divided difference approach to robot path planning

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A hierarchical robot control is proposed for robot soccer system. The Newton' s divided difference is utilized in robot path planning. This paper describes the problems encoutered, software design considerations, vision algorithm and controls of individual robots. The solutions.to the problems implemented are simple and di rect. It is observed that many of the ideas and solutions can be evolved based on simple theories and concepts. This paper focuses on software structure of multi-agent controls, vision algorithm and simple path planning method.

  20. Functional Integrity of Some Class of Multi-Agent Systems

    Directory of Open Access Journals (Sweden)

    Krzysztof Cetnarowicz

    1999-01-01

    Full Text Available Multi-agent systems have many advantages and give numerous new possibilities in creation of information systems. However many problems related to functioning of the systems are still unsolved. Functional integrity of multi-agents systems belongs to such problems. Functional integrity of multi-agent systems may be defined in general as preservation of basic functions of the system during its functioning. Functional integrity may be analyzed from the point of view of different functions of the system (the functions that should be preserved and also from the point of view of various factors that may influence the loss or preservation of functional integrity of the system. The paper deals with examination of functional integrity of multi-agent system depending upon number of agents (global and of particular types. During system work, agents generate agents of the same or different type that depend on their possibilities and system needs. The process performed without use of appropriate control mechanisms may lead to excessive (blocking of the system or too little number of agents and even lack of agents (disappearance of the functions of a system that are performed by agents of a certain type. A proposal of functional integrity phenomenon analysis of multi-agent systems that is related to the number of agents in their population and a proposal of mechanisms that enable maintenance of functional integrity, in particular a concept of the so-called ``free agents'' have been presented in the paper. Consideration has been carried out on the basis of simulation examination of some class of multi-agent systems. Results of simulation of proposed solutions have been included in the work.

  1. Multi-agent robotic cooperative assembly system

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Presents a multi-robot cooperative assembly systen (MRCAS) which is composed of an organizer computer, three industrial robots, PUMA 562 mounted on an onni-directional vehicle, PUMA 760 and Adept I and organized in to a hierarchical structure with the cooperation organization on the top and the coordination motion at the bottom to solve the main problem of coordination and cooperation among robots, and concludes with experimental results that MRCAS is reconfigurable and adaptable as the mission changes.

  2. Multiconsensus of Second-Order Multiagent Systems with Input Delays

    Directory of Open Access Journals (Sweden)

    Jie Chen

    2014-01-01

    Full Text Available The multiconsensus problem of double-integrator dynamic multiagent systems has been investigated. Firstly, the dynamic multiconsensus, the static multiconsensus, and the periodic multiconsensus are considered as three cases of multiconsensus, respectively, in which the final multiconsensus convergence states are established by using matrix analysis. Secondly, as for the multiagent system with input delays, the maximal allowable upper bound of the delays is obtained by employing Hopf bifurcation of delayed networks theory. Finally, simulation results are presented to verify the theoretical analysis.

  3. Cooperative Epistemic Multi-Agent Planning With Implicit Coordination

    DEFF Research Database (Denmark)

    Engesser, Thorsten; Bolander, Thomas; Mattmüller, Robert

    2015-01-01

    , meaning coordination is only allowed implicitly by means of the available epistemic actions. While this approach can be fruitfully applied to model reasoning in some simple social situations, we also provide some benchmark applications to show that the concept is useful for multi-agent systems in practice.......Epistemic Planning has been used to achieve ontic and epistemic control in multi-agent situations. We extend the formalism to include perspective shifts, allowing us to define a class of cooperative problems in which both action planning and execution is done in a purely distributed fashion...

  4. FIRST GENERATION MULTI-AGENT MODELS AND THEIR UPGRADES

    Directory of Open Access Journals (Sweden)

    Andras Vag

    2004-06-01

    Full Text Available Multi-agent systems consist of interactive and independent agents of different kinds in a "world" of the computers. The key issue of multi-agent modelling is its ability to produce emergent phenomena at macro level from "micro-behaviour". For now this approach became a widely used methodology in socio-economics and ecology. This paper presents three famous first generation models and then drafts some of their upgrades, especially the agent-based computational economics, the spatial planning approach and the ecological models. Finally some conceptual developments are presented and discussed.

  5. Teamwork in Multi-Agent Systems A Formal Approach

    CERN Document Server

    Dunin-Keplicz, Barbara Maria

    2010-01-01

    What makes teamwork tick?. Cooperation matters, in daily life and in complex applications. After all, many tasks need more than a single agent to be effectively performed. Therefore, teamwork rules!. Teams are social groups of agents dedicated to the fulfilment of particular persistent tasks. In modern multiagent environments, heterogeneous teams often consist of autonomous software agents, various types of robots and human beings. Teamwork in Multi-agent Systems: A Formal Approach explains teamwork rules in terms of agents' attitudes and their complex interplay. It provides the first comprehe

  6. A study of multiagent systems for resource allocation

    Science.gov (United States)

    Liu, Haixiao; Shao, Zhichao; Li, Shanfei; Tan, Xianglin

    2017-03-01

    The agent and multiagent system is one of the most active methods for solving complicated problems as to resource allocation recently. Here, an agent can be considered as a computer program who takes autonomous actions to obtain some units of resources for individual purposes and common goals. The environment can be referred to the place where scattered resources and agent behavior-restricted rules are stored. And a multiagent system is a type of computing system built upon multiple situated agents who interact with each other under mechanisms. This paper aims to overview the techniques regarding agents and the environment.

  7. The Cooperative Multi-agent Learning with Random Reward Values

    Institute of Scientific and Technical Information of China (English)

    ZHANG Hua-xiang; HUANG Shang-teng

    2005-01-01

    This paper investigated how to learn the optimal action policies in cooperative multiagent systems if the agents' rewards are random variables, and proposed a general two-stage learning algorithm for cooperative multiagent decision processes. The algorithm first calculates the averaged immediate rewards, and considers these learned rewards as the agents' immediate action rewards to learn the optimal action policies. It is proved that the learning algorithm can find the optimal policies in stochastic environment. Extending the algorithm to stochastic Markov decision processes was also discussed.

  8. A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence

    CERN Document Server

    Vlassis, Nikos

    2007-01-01

    Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introduction to the subject, covering the theoretical foundations as well as more recent developments in a coherent and readable manner. The text is centered on the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under uncertainty. Chapter 3 is a brief introductio

  9. Consensus protocol for multi-agent continuous systems

    Institute of Scientific and Technical Information of China (English)

    Tan Fu-Xiao; Guan Xin-Ping; Liu De-Rong

    2008-01-01

    Based on the algebraic graph theory,the networked multi-agent continuous systems are investigated.Firstly,the digraph(directed graph)represents the topology of a networked system,and then a consensus convergence criterion of system is proposed.Secondly,the issue of stability of multi-agent systems and the consensus convergence problem of information states are all analysed.Furthermore,the Consensus equilibrium point of system is proved to be global and asymptotically reach the convex combination of initial states.Finally,two examples are taken to show the effectiveness of the results obtained in this paper.

  10. Parallel hierarchical radiosity rendering

    Energy Technology Data Exchange (ETDEWEB)

    Carter, M.

    1993-07-01

    In this dissertation, the step-by-step development of a scalable parallel hierarchical radiosity renderer is documented. First, a new look is taken at the traditional radiosity equation, and a new form is presented in which the matrix of linear system coefficients is transformed into a symmetric matrix, thereby simplifying the problem and enabling a new solution technique to be applied. Next, the state-of-the-art hierarchical radiosity methods are examined for their suitability to parallel implementation, and scalability. Significant enhancements are also discovered which both improve their theoretical foundations and improve the images they generate. The resultant hierarchical radiosity algorithm is then examined for sources of parallelism, and for an architectural mapping. Several architectural mappings are discussed. A few key algorithmic changes are suggested during the process of making the algorithm parallel. Next, the performance, efficiency, and scalability of the algorithm are analyzed. The dissertation closes with a discussion of several ideas which have the potential to further enhance the hierarchical radiosity method, or provide an entirely new forum for the application of hierarchical methods.

  11. Multi-Agent System Based Special Protection and Emergency Control Scheme against Cascading Events in Power System

    DEFF Research Database (Denmark)

    Liu, Zhou

    for real time implementation. On the other hand, with the aim of executing the control methods timely and implementing the whole protection strategy suitably, multi-agent system (MAS) with hierarchical structure is designed here. The distributed relays and controllers, which work as device agents......This thesis concerns the development of wide area special protection and emergency control scheme that can provide effective countermeasures against long term voltage instability induced cascading events and blackouts in power system. Most past cascaded blackouts are caused by unexpected backup...... relay operations due to low voltage or overload state in the post stage of N-1 (or N-k) contingency. If such state could be sensed and adjusted appropriately before those relay actions, the system stability might be sustained. So it is of great significance to develop a suitable protection scheme...

  12. Neutrosophic Hierarchical Clustering Algoritms

    Directory of Open Access Journals (Sweden)

    Rıdvan Şahin

    2014-03-01

    Full Text Available Interval neutrosophic set (INS is a generalization of interval valued intuitionistic fuzzy set (IVIFS, whose the membership and non-membership values of elements consist of fuzzy range, while single valued neutrosophic set (SVNS is regarded as extension of intuitionistic fuzzy set (IFS. In this paper, we extend the hierarchical clustering techniques proposed for IFSs and IVIFSs to SVNSs and INSs respectively. Based on the traditional hierarchical clustering procedure, the single valued neutrosophic aggregation operator, and the basic distance measures between SVNSs, we define a single valued neutrosophic hierarchical clustering algorithm for clustering SVNSs. Then we extend the algorithm to classify an interval neutrosophic data. Finally, we present some numerical examples in order to show the effectiveness and availability of the developed clustering algorithms.

  13. Multiwall carbon nanotubes reinforced epoxy nanocomposites

    Science.gov (United States)

    Chen, Wei

    The emergence of carbon nanotubes (CNTs) has led to myriad possibilities for structural polymer composites with superior specific modulus, strength, and toughness. While the research activities in carbon nanotube reinforced polymer composites (NRPs) have made enormous progress towards fabricating next-generation advanced structural materials with added thermal, optical, and electrical advantages, questions concerning the filler dispersion, interface, and CNT alignment in these composites remain partially addressed. In this dissertation, the key technical challenges related to the synthesis, processing, and reinforcing mechanics governing the effective mechanical properties of NRPs were introduced and reviewed in the first two chapters. Subsequently, issues on the dispersion, interface control, hierarchical structure, and multi-functionality of NRPs were addressed based on functionalized multi-walled carbon nanotube reinforced DGEBA epoxy systems (NREs). In chapter 3, NREs with enhanced flexural properties were discussed in the context of improved dispersion and in-situ formation of covalent bonds at the interface. In chapter 4, NREs with controlled interface and tailored thermomechanical properties were demonstrated through the judicious choice of surface functionality and resin chemistry. In chapter 5, processing-condition-induced CNT organization in hierarchical epoxy nanocomposites was analyzed. In Chapter 6, possibilities were explored for multi-functional NREs for underwater acoustic structural applications. Finally, the findings of this dissertation were concluded and future research was proposed for ordered carbon nanotube array reinforced nanocomposites in the last chapter. Four journal publications resulted from this work are listed in Appendix.

  14. The Role of Reinforcement Sensitivity in the Development of Childhood Personality

    Science.gov (United States)

    Slobodskaya, Helena R.; Kuznetsova, Valeriya B.

    2013-01-01

    The study examined the contribution of reinforcement sensitivity to childhood personality at three levels of the hierarchical structure, mid-level traits, the Big Five and two higher-order factors, and the moderating role of sex and age in a sample of 3-18-year-olds. The canonical correlation analyses indicated that reinforcement sensitivity and…

  15. Learning in and for Multi-Agency Working

    Science.gov (United States)

    Daniels, Harry; Leadbetter, Jane; Warmington, Paul; Edwards, Anne; Martin, Deirdre; Popova, Anna; Apostolov, Apostol; Middleton, David; Brown, Steve

    2007-01-01

    This study addresses the challenges faced by organisations and individual professionals, as new practices are developed and learned in multi-agency work settings. The practices examined in the paper involve working responsively across professional boundaries with at-risk young people. The paper draws on evidence from the Learning in and for…

  16. Theories about architecture and performance of multi-agent systems

    NARCIS (Netherlands)

    Gazendam, Henk W.M.; Jorna, René J.

    1998-01-01

    Multi-agent systems are promising as models of organization because they are based on the idea that most work in human organizations is done based on intelligence, communication, cooperation, and massive parallel processing. They offer an alternative for system theories of organization, which are ra

  17. Engineering a Multi-Agent System in GOAL

    DEFF Research Database (Denmark)

    Villadsen, Jørgen; Jensen, Andreas Schmidt; Christensen, Nicolai Christian

    2013-01-01

    We provide a brief description of the GOAL-DTU system, including the overall design, the tools and the algorithms that we used in the Multi-Agent Programming Contest 2013. We focus on a description of the strategies and on an analysis of the matches. We also evaluate our experiences with the GOAL...

  18. Consensus of Multiagent Systems with Sampled Information and Noisy Measurements

    Directory of Open Access Journals (Sweden)

    Zhao-Jun Tang

    2013-01-01

    Full Text Available We consider consensus problems of first-order multiagent systems with sampled information and noisy measurements. A distributed stochastic approximation type algorithm is employed to attenuate the measurement noises. We provide conditions under which almost sure strong consensus is guaranteed for fixed and switching directed network topologies. Simulation results are provided to illustrate the theoretical results.

  19. Knowledge based support for multiagent control and automation

    DEFF Research Database (Denmark)

    Saleem, Arshad; Lind, Morten

    2011-01-01

    This paper presents a mechanism for developing knowledge based support in multiagent based control and diagnosis. In particular it presents a way for autonomous agents to utilize a qualitative means-ends based model for reasoning about control situations. The proposed mechanism have been used in ...

  20. Robust Synchronization of Uncertain Linear Multi-Agent Systems

    NARCIS (Netherlands)

    Trentelman, Harry L.; Takaba, Kiyotsugu; Monshizadeh Naini, Nima

    2013-01-01

    This paper deals with robust synchronization of uncertain multi-agent networks. Given a network with for each of the agents identical nominal linear dynamics, we allow uncertainty in the form of additive perturbations of the transfer matrices of the nominal dynamics. The perturbations are assumed to

  1. Nautical traffic simulation with multi-agent system

    NARCIS (Netherlands)

    Xiao, F.; Ligteringen, H.; Van Gulijk, C.; Ale, B.J.M.

    2013-01-01

    This paper describes a microscopic nautical traffic simulation model based on multi-agent system. The ship traffic is produced from the behavior of autonomous agents that represent ships. Especially, we look at the behaviors for collision avoidance in different encountering situations with different

  2. A multiagent system to assist elder people by TV communication

    Directory of Open Access Journals (Sweden)

    Víctor PARRA

    2015-03-01

    Full Text Available This paper presents a model that assist seniors requiring care. This system is based on a multiagent platform in order to facilitate the communication of the modules composing the model. The application allows independence for the elderly, as he is moving in a secure environment. Besides, it provides different facilities through a platform accessible to everyone, by using the TV.

  3. Multi-Agent Framework for Virtual Learning Spaces.

    Science.gov (United States)

    Sheremetov, Leonid; Nunez, Gustavo

    1999-01-01

    Discussion of computer-supported collaborative learning, distributed artificial intelligence, and intelligent tutoring systems focuses on the concept of agents, and describes a virtual learning environment that has a multi-agent system. Describes a model of interactions in collaborative learning and discusses agents for Web-based virtual…

  4. The norm implementation problem in normative multi-agent systems

    NARCIS (Netherlands)

    Grossi, D.; Gabbay, D.; van der Torre, L.; Dastani, M.; Hindriks, K.V.; Meyer, J-J.C.

    2010-01-01

    The norm implementation problem consists in how to see to it that the agents in a system comply with the norms specified for that system by the system designer. It is part of the more general problem of how to synthesize or create norms for multi-agent systems, by, for example, highlighting the choi

  5. A Multi-Agent Immunology Model for Security Computer

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper presents a computer immunology model for computersecurity , whose main components are defined as idea of Multi-Agent. It introduces the n at ural immune system on the principle, discusses the idea and characteristics of Mu lti-Agent. It gives a system model, and describes the structure and function of each agent. Also, the communication method between agents is described.

  6. Verifying Interlevel Relations within Multi-Agent Systems

    NARCIS (Netherlands)

    Sharpanskykh, A.; Treur, J.

    2006-01-01

    An approach to handle the complex dynamics of a multi-agent system is based on distinguishing aggregation levels by structuring the system into parts or components. The behavior of every aggregation level is specified by a set of dynamic properties for components and interactions at that level, expr

  7. A Multi-Agent System for Intelligent Online Education.

    Science.gov (United States)

    O'Riordan, Colm; Griffith, Josephine

    1999-01-01

    Describes the system architecture of an intelligent Web-based education system that includes user modeling agents, information filtering agents for automatic information gathering, and the multi-agent interaction. Discusses information management; user interaction; support for collaborative peer-peer learning; implementation; testing; and future…

  8. Nautical traffic simulation with multi-agent system

    NARCIS (Netherlands)

    Xiao, F.; Ligteringen, H.; Van Gulijk, C.; Ale, B.J.M.

    2013-01-01

    This paper describes a microscopic nautical traffic simulation model based on multi-agent system. The ship traffic is produced from the behavior of autonomous agents that represent ships. Especially, we look at the behaviors for collision avoidance in different encountering situations with different

  9. Consensus tracking for multiagent systems with nonlinear dynamics.

    Science.gov (United States)

    Dong, Runsha

    2014-01-01

    This paper concerns the problem of consensus tracking for multiagent systems with a dynamical leader. In particular, it proposes the corresponding explicit control laws for multiple first-order nonlinear systems, second-order nonlinear systems, and quite general nonlinear systems based on the leader-follower and the tree shaped network topologies. Several numerical simulations are given to verify the theoretical results.

  10. Multi-agent Model of Trust in a Human Game

    NARCIS (Netherlands)

    Jonker, C.M.; Meijer, S.A.; Tykhonov, D.; Verwaart, D.

    2006-01-01

    Individual-level trust is formalized within the context of a multi-agent system that models human behaviour with respect to trust in the Trust and Tracing Game. This is a trade game on commodity supply chains and networks, designed as a reserach tool and to be played by human players. The model of t

  11. Reimplementing a Multi-Agent System in Python

    DEFF Research Database (Denmark)

    Villadsen, Jørgen; Jensen, Andreas Schmidt; Ettienne, Mikko Berggren

    2013-01-01

    We provide a brief description of our Python-DTU system, including the overall design, the tools and the algorithms that we used in the Multi-Agent Programming Contest 2012, where the scenario was called Agents on Mars like in 2011. Our solution is an improvement of our Python-DTU system from last...

  12. Implementing a Multi-Agent System in Python

    DEFF Research Database (Denmark)

    Ettienne, Mikko Berggren; Vester, Steen; Villadsen, Jørgen

    2012-01-01

    We describe the solution used by the Python-DTU team in the Multi-Agent Programming Contest 2011, where the scenario was called Agents on Mars. We present our auction-based agreement, area controlling and pathfinding algorithms and discuss our chosen strategy and our choice of technology used...

  13. Collaboration of Metaheuristic Algorithms through a Multi-Agent System

    Science.gov (United States)

    Malek, Richard

    This paper introduces a framework based on multi-agent system for solving problems of combinatorial optimization. The framework allows running various metaheuristic algorithms simultaneously. By the collaboration of various metaheuristics, we can achieve better results in more classes of problems.

  14. Sarymsakov matrices and coordination tasks for multi-agent systems

    NARCIS (Netherlands)

    Xia, Weiguo; Cao, Ming

    2012-01-01

    The convergence of products of stochastic matrices has proven to be critical in establishing the effectiveness of distributed coordination algorithms for multi-agent systems. After reviewing some classic and recent results on infinite backward products of stochastic matrices, we provide a new

  15. Implementing a Multi-Agent System in Python

    DEFF Research Database (Denmark)

    Ettienne, Mikko Berggren; Vester, Steen; Villadsen, Jørgen

    2012-01-01

    We describe the solution used by the Python-DTU team in the Multi-Agent Programming Contest 2011, where the scenario was called Agents on Mars. We present our auction-based agreement, area controlling and pathfinding algorithms and discuss our chosen strategy and our choice of technology used...

  16. Multi-agent plan-execution health repair

    NARCIS (Netherlands)

    Jonge, Femke de; Roos, Nico; Herik, Jaap van den

    2006-01-01

    This paper presents a protocol for plan health repair in multi-agent plan execution. Plan health repair aims at avoiding conflicts that might arise due to disruptions in the execution of a plan. This can be achieved by adjusting the executions of tasks instead of replanning the tasks. For this

  17. A Plan Fusion Algorithm for Multi-Agent Systems

    NARCIS (Netherlands)

    De Weerdt, M.M.; Bos, A.; Tonino, J.F.M.; Witteveen, C.

    2000-01-01

    We introduce an algorithm for cooperative planning in multi-agent systems. The algorithm enables the agents to combine (fuse) their plans in order to increase their joint profits. A computational resources and skills framework is developed for representing the planned activities of an agent under ti

  18. Basal Reinforced Piled Embankments

    NARCIS (Netherlands)

    Van Eekelen, S.J.M.

    2015-01-01

    A basal reinforced piled embankment consists of a reinforced embankment on a pile foundation. The reinforcement consists of one or more horizontal layers of geosynthetic reinforcement (GR) installed at the base of the embankment. The design of the GR is the subject of this thesis. A basal

  19. The Reinforcement Hierarchy

    Science.gov (United States)

    Forness, Steven R.

    1973-01-01

    Reinforcement hierarchy implies movement along a continuum from top to bottom, from primitive levels of reinforcement to more sophisticated levels. Unless it is immediately obvious that a child cannot function without the use of lower-order reinforcers, we should approach him as though he responds to topmost reinforcers until he demonstrates…

  20. Hierarchical Porous Structures

    Energy Technology Data Exchange (ETDEWEB)

    Grote, Christopher John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-06-07

    Materials Design is often at the forefront of technological innovation. While there has always been a push to generate increasingly low density materials, such as aero or hydrogels, more recently the idea of bicontinuous structures has gone more into play. This review will cover some of the methods and applications for generating both porous, and hierarchically porous structures.

  1. Hybrid Multi-Agent Control in Microgrids: Framework, Models and Implementations Based on IEC 61850

    Directory of Open Access Journals (Sweden)

    Xiaobo Dou

    2014-12-01

    Full Text Available Operation control is a vital and complex issue for microgrids. The objective of this paper is to explore the practical means of applying decentralized control by using a multi agent system in actual microgrids and devices. This paper presents a hierarchical control framework (HCF consisting of local reaction control (LRC level, local decision control (LDC level, horizontal cooperation control (HCC level and vertical cooperation control (VCC level to meet different control requirements of a microgrid. Then, a hybrid multi-agent control model (HAM is proposed to implement HCF, and the properties, functionalities and operating rules of HAM are described. Furthermore, the paper elaborates on the implementation of HAM based on the IEC 61850 Standard, and proposes some new implementation methods, such as extended information models of IEC 61850 with agent communication language and bidirectional interaction mechanism of generic object oriented substation event (GOOSE communication. A hardware design and software system are proposed and the results of simulation and laboratory tests verify the effectiveness of the proposed strategies, models and implementations.

  2. Micromechanical design of hierarchical composites using global load sharing theory

    Science.gov (United States)

    Rajan, V. P.; Curtin, W. A.

    2016-05-01

    Hierarchical composites, embodied by natural materials ranging from bone to bamboo, may offer combinations of material properties inaccessible to conventional composites. Using global load sharing (GLS) theory, a well-established micromechanics model for composites, we develop accurate numerical and analytical predictions for the strength and toughness of hierarchical composites with arbitrary fiber geometries, fiber strengths, interface properties, and number of hierarchical levels, N. The model demonstrates that two key material properties at each hierarchical level-a characteristic strength and a characteristic fiber length-control the scalings of composite properties. One crucial finding is that short- and long-fiber composites behave radically differently. Long-fiber composites are significantly stronger than short-fiber composites, by a factor of 2N or more; they are also significantly tougher because their fiber breaks are bridged by smaller-scale fibers that dissipate additional energy. Indeed, an "infinite" fiber length appears to be optimal in hierarchical composites. However, at the highest level of the composite, long fibers localize on planes of pre-existing damage, and thus short fibers must be employed instead to achieve notch sensitivity and damage tolerance. We conclude by providing simple guidelines for microstructural design of hierarchical composites, including the selection of N, the fiber lengths, the ratio of length scales at successive hierarchical levels, the fiber volume fractions, and the desired properties of the smallest-scale reinforcement. Our model enables superior hierarchical composites to be designed in a rational way, without resorting either to numerical simulation or trial-and-error-based experimentation.

  3. Learning in engineered multi-agent systems

    Science.gov (United States)

    Menon, Anup

    Consider the problem of maximizing the total power produced by a wind farm. Due to aerodynamic interactions between wind turbines, each turbine maximizing its individual power---as is the case in present-day wind farms---does not lead to optimal farm-level power capture. Further, there are no good models to capture the said aerodynamic interactions, rendering model based optimization techniques ineffective. Thus, model-free distributed algorithms are needed that help turbines adapt their power production on-line so as to maximize farm-level power capture. Motivated by such problems, the main focus of this dissertation is a distributed model-free optimization problem in the context of multi-agent systems. The set-up comprises of a fixed number of agents, each of which can pick an action and observe the value of its individual utility function. An individual's utility function may depend on the collective action taken by all agents. The exact functional form (or model) of the agent utility functions, however, are unknown; an agent can only measure the numeric value of its utility. The objective of the multi-agent system is to optimize the welfare function (i.e. sum of the individual utility functions). Such a collaborative task requires communications between agents and we allow for the possibility of such inter-agent communications. We also pay attention to the role played by the pattern of such information exchange on certain aspects of performance. We develop two algorithms to solve this problem. The first one, engineered Interactive Trial and Error Learning (eITEL) algorithm, is based on a line of work in the Learning in Games literature and applies when agent actions are drawn from finite sets. While in a model-free setting, we introduce a novel qualitative graph-theoretic framework to encode known directed interactions of the form "which agents' action affect which others' payoff" (interaction graph). We encode explicit inter-agent communications in a directed

  4. Consensus of Heterogeneous Linear Multiagent Systems With Communication Time-Delays.

    Science.gov (United States)

    Xu, Xiang; Liu, Lu; Feng, Gang

    2017-05-23

    This paper studies the consensus problem of heterogeneous linear multiagent systems with arbitrarily large constant, time-varying, or distributed communication delays. Novel distributed dynamic controllers are proposed for such multiagent systems with fixed and switching directed communication topologies, respectively. It is shown that the controlled heterogeneous linear multiagent system can reach consensus for arbitrarily large constant, time-varying, and distributed communication delays under some sufficient conditions. Simulation examples are provided to demonstrate the effectiveness of the proposed controllers.

  5. Model of interaction in Smart Grid on the basis of multi-agent system

    Science.gov (United States)

    Engel, E. A.; Kovalev, I. V.; Engel, N. E.

    2016-11-01

    This paper presents model of interaction in Smart Grid on the basis of multi-agent system. The use of travelling waves in the multi-agent system describes the behavior of the Smart Grid from the local point, which is being the complement of the conventional approach. The simulation results show that the absorption of the wave in the distributed multi-agent systems is effectively simulated the interaction in Smart Grid.

  6. Collaborative Hierarchical Sparse Modeling

    CERN Document Server

    Sprechmann, Pablo; Sapiro, Guillermo; Eldar, Yonina C

    2010-01-01

    Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is done by solving an l_1-regularized linear regression problem, usually called Lasso. In this work we first combine the sparsity-inducing property of the Lasso model, at the individual feature level, with the block-sparsity property of the group Lasso model, where sparse groups of features are jointly encoded, obtaining a sparsity pattern hierarchically structured. This results in the hierarchical Lasso, which shows important practical modeling advantages. We then extend this approach to the collaborative case, where a set of simultaneously coded signals share the same sparsity pattern at the higher (group) level but not necessarily at the lower one. Signals then share the same active groups, or classes, but not necessarily the same active set. This is very well suited for applications such as source separation. An efficient optimization procedure, which guarantees convergence to the global opt...

  7. Hierarchical manifold learning.

    Science.gov (United States)

    Bhatia, Kanwal K; Rao, Anil; Price, Anthony N; Wolz, Robin; Hajnal, Jo; Rueckert, Daniel

    2012-01-01

    We present a novel method of hierarchical manifold learning which aims to automatically discover regional variations within images. This involves constructing manifolds in a hierarchy of image patches of increasing granularity, while ensuring consistency between hierarchy levels. We demonstrate its utility in two very different settings: (1) to learn the regional correlations in motion within a sequence of time-resolved images of the thoracic cavity; (2) to find discriminative regions of 3D brain images in the classification of neurodegenerative disease,

  8. Hierarchically Structured Electrospun Fibers

    Directory of Open Access Journals (Sweden)

    Nicole E. Zander

    2013-01-01

    Full Text Available Traditional electrospun nanofibers have a myriad of applications ranging from scaffolds for tissue engineering to components of biosensors and energy harvesting devices. The generally smooth one-dimensional structure of the fibers has stood as a limitation to several interesting novel applications. Control of fiber diameter, porosity and collector geometry will be briefly discussed, as will more traditional methods for controlling fiber morphology and fiber mat architecture. The remainder of the review will focus on new techniques to prepare hierarchically structured fibers. Fibers with hierarchical primary structures—including helical, buckled, and beads-on-a-string fibers, as well as fibers with secondary structures, such as nanopores, nanopillars, nanorods, and internally structured fibers and their applications—will be discussed. These new materials with helical/buckled morphology are expected to possess unique optical and mechanical properties with possible applications for negative refractive index materials, highly stretchable/high-tensile-strength materials, and components in microelectromechanical devices. Core-shell type fibers enable a much wider variety of materials to be electrospun and are expected to be widely applied in the sensing, drug delivery/controlled release fields, and in the encapsulation of live cells for biological applications. Materials with a hierarchical secondary structure are expected to provide new superhydrophobic and self-cleaning materials.

  9. HDS: Hierarchical Data System

    Science.gov (United States)

    Pearce, Dave; Walter, Anton; Lupton, W. F.; Warren-Smith, Rodney F.; Lawden, Mike; McIlwrath, Brian; Peden, J. C. M.; Jenness, Tim; Draper, Peter W.

    2015-02-01

    The Hierarchical Data System (HDS) is a file-based hierarchical data system designed for the storage of a wide variety of information. It is particularly suited to the storage of large multi-dimensional arrays (with their ancillary data) where efficient access is needed. It is a key component of the Starlink software collection (ascl:1110.012) and is used by the Starlink N-Dimensional Data Format (NDF) library (ascl:1411.023). HDS organizes data into hierarchies, broadly similar to the directory structure of a hierarchical filing system, but contained within a single HDS container file. The structures stored in these files are self-describing and flexible; HDS supports modification and extension of structures previously created, as well as functions such as deletion, copying, and renaming. All information stored in HDS files is portable between the machines on which HDS is implemented. Thus, there are no format conversion problems when moving between machines. HDS can write files in a private binary format (version 4), or be layered on top of HDF5 (version 5).

  10. Hierarchical video summarization

    Science.gov (United States)

    Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.

    1998-12-01

    We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.

  11. Distributed formation output regulation of switching heterogeneous multi-agent systems

    Science.gov (United States)

    Wang, Xiaoli

    2013-11-01

    In this article, the distributed formation output regulation problem of linear heterogeneous multi-agent systems with uncertainty under switching topology is considered. It is a generalised framework for multi-agent coordination problems, which contains or concerns a variety of important multi-agent problems in a quite unified way. Its background includes active leader following formation for the agents to maintain desired relative distances and orientations to the leader with a predefined trajectory, and multi-agent formation with environmental inputs. With the help of canonical internal model we design a distributed dynamic output feedback to handle the distributed formation output regulation problem.

  12. H∞ Consensus for Multiagent Systems with Heterogeneous Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Beibei Wang

    2013-01-01

    Full Text Available We apply the linear matrix inequality method to consensus and H∞ consensus problems of the single integrator multiagent system with heterogeneous delays in directed networks. To overcome the difficulty caused by heterogeneous time-varying delays, we rewrite the multiagent system into a partially reduced-order system and an integral system. As a result, a particular Lyapunov function is constructed to derive sufficient conditions for consensus of multiagent systems with fixed (switched topologies. We also apply this method to the H∞ consensus of multiagent systems with disturbances and heterogeneous delays. Numerical examples are given to illustrate the theoretical results.

  13. RESEARCH ON CAPP/SCHEDULING INTEGRATION MULTI-AGENT SYSTEM MODEL AND IMPLEMENTATION

    Institute of Scientific and Technical Information of China (English)

    Wang Yunli; Xiao Tianyuan; Duan Guanghong; Wang Xiankui

    2003-01-01

    A design methodology for multi-agent systems is proposed. The systemic framework of CAPP and scheduling integrated multi-agent system according to design methodology is researched.Agent model, composition model and cooperation model are discussed respectively in the multi-agent system. Static composition model and dynamic running model of CAPP and scheduling integrated system are presented in composition model. Communication model, language model and protocol model are discussed in corporation model. CSIMAS, CAPP and scheduling integrated multi-agent prototype system, is developed to illuminate system model. Multiple non-rotational parts are tested in distributed process planning and scheduling environment of CSIMAS.

  14. Multi-agent Water Resources Management

    Science.gov (United States)

    Castelletti, A.; Giuliani, M.

    2011-12-01

    Increasing environmental awareness and emerging trends such as water trading, energy market, deregulation and democratization of water-related services are challenging integrated water resources planning and management worldwide. The traditional approach to water management design based on sector-by-sector optimization has to be reshaped to account for multiple interrelated decision-makers and many stakeholders with increasing decision power. Centralized management, though interesting from a conceptual point of view, is unfeasible in most of the modern social and institutional contexts, and often economically inefficient. Coordinated management, where different actors interact within a full open trust exchange paradigm under some institutional supervision is a promising alternative to the ideal centralized solution and the actual uncoordinated practices. This is a significant issue in most of the Southern Alps regulated lakes, where upstream hydropower reservoirs maximize their benefit independently form downstream users; it becomes even more relevant in the case of transboundary systems, where water management upstream affects water availability downstream (e.g. the River Zambesi flowing through Zambia, Zimbabwe and Mozambique or the Red River flowing from South-Western China through Northern Vietnam. In this study we apply Multi-Agent Systems (MAS) theory to design an optimal management in a decentralized way, considering a set of multiple autonomous agents acting in the same environment and taking into account the pay-off of individual water users, which are inherently distributed along the river and need to coordinate to jointly reach their objectives. In this way each real-world actor, representing the decision-making entity (e.g. the operator of a reservoir or a diversion dam) can be represented one-to-one by a computer agent, defined as a computer system that is situated in some environment and that is capable of autonomous action in this environment in

  15. A Multi-Agents Architecture to Learn Vision Operators and their Parameters

    Directory of Open Access Journals (Sweden)

    Issam Qaffou

    2012-05-01

    Full Text Available In a vision system, every task needs that the operators to apply should be well chosen and their parameters should be also well adjusted . The diversity of operators and the multitude of their parameters constitute a big challenge for users. As it is very difficult to make the right choice, lack of a specific rule, many disadvantages appear and affect the computation time and especially the quality of results. In this paper we present a multi-agent architecture to learn the best operators to apply and their best parameters for a class of images. Our architecture consists of three types of agents: User Agent, Operator Agent and Parameter Agent. The User Agent determines the phases of treatment, a library of operators and the possible values of their parameters. The Operator Agent constructs all possible combinations of operators and the Parameter Agent, the core of the architecture, adjusts the parameters of each combination by treating a large number of images. Through the reinforcement learning mechanism, our architecture does not consider only the system opportunities but also the user preferences.

  16. Towards the Integration of Multiagent Applications and Data Mining

    Science.gov (United States)

    Ralha, Célia Ghedini

    This chapter has the objective to present research on combining two originally separated areas, agents including distributed multiagent systems and data mining, which are increasingly interrelated. Recent research has present that such interaction features are bilateral and complementary, since new approaches and techniques are developed to benefit from the synergetic enhancement of intelligence and infrastructure for information processing and systems. This chapter draws attention to illustrate agent-mining interaction with two different domain multiagent applications: BioAgents at the bioinformatics area and MADIK at the computer forensics area. The presented case studies are driving forces towards the integration of the agent-mining challenging area. As ongoing research works we discuss the prospects of both agent-mining projects.

  17. Cooperative epistemic multi-agent planning for implicit coordination

    DEFF Research Database (Denmark)

    Engesser, Thorsten; Bolander, Thomas; Mattmüller, Robert

    2017-01-01

    Epistemic planning can be used for decision making in multi-agent situations with distributed knowledge and capabilities. Recently, Dynamic Epistemic Logic (DEL) has been shown to provide a very natural and expressive framework for epistemic planning. We extend the DEL-based epistemic planning...... framework to include perspective shifts, allowing us to define new notions of sequential and conditional planning with implicit coordination. With these, it is possible to solve planning tasks with joint goals in a decentralized manner without the agents having to negotiate about and commit to a joint...... policy at plan time. First we define the central planning notions and sketch the implementation of a planning system built on those notions. Afterwards we provide some case studies in order to evaluate the planner empirically and to show that the concept is useful for multi-agent systems in practice....

  18. Multi-Agent System Interaction in Integrated SCM

    Directory of Open Access Journals (Sweden)

    G. N. Purohit

    2009-10-01

    Full Text Available Coordination between organizations on strategic, tactical and operation levels leads to more effective and efficient supply chains. Supply chain management is increasing day by day in modern enterprises. The environment is becoming competitive and many enterprises will find it difficult to survive if they do not make their sourcing, production and distribution more efficient. Multi-agent supply chain management has recognized as an effective methodology for supply chain management. Multi-agent systems (MAS offer new methods compared to conventional, centrally organized architectures in the scope of supply chain management (SCM. Since necessary data are not available within the whole supply chain, an integrated approach for production planning and control taking into account all the partners involved is not feasible. In this study we show how MAS architecture interacts in the integrated SCM architecture with the help of various intelligent agents to highlight the above problem.

  19. Distributed Research Project Scheduling Based on Multi-Agent Methods

    Directory of Open Access Journals (Sweden)

    Constanta Nicoleta Bodea

    2011-01-01

    Full Text Available Different project planning and scheduling approaches have been developed. The Operational Research (OR provides two major planning techniques: CPM (Critical Path Method and PERT (Program Evaluation and Review Technique. Due to projects complexity and difficulty to use classical methods, new approaches were developed. Artificial Intelligence (AI initially promoted the automatic planner concept, but model-based planning and scheduling methods emerged later on. The paper adresses the project scheduling optimization problem, when projects are seen as Complex Adaptive Systems (CAS. Taken into consideration two different approaches for project scheduling optimization: TCPSP (Time- Constrained Project Scheduling and RCPSP (Resource-Constrained Project Scheduling, the paper focuses on a multiagent implementation in MATLAB for TCSP. Using the research project as a case study, the paper includes a comparison between two multi-agent methods: Genetic Algorithm (GA and Ant Colony Algorithm (ACO.

  20. Multi-agent Based Modeling of Manufacturing Network

    Institute of Scientific and Technical Information of China (English)

    GUO Yuming; SUN Yanming; ZHENG Shixiong

    2006-01-01

    An intelligent manufacturing system is modeled currently from the viewpoint of manufacturing applications, and the network platform's influence to manufacturing applications is not considered adequately. However any bottleneck in service oriented architecture (SOA) for the manufacturing network can affect the agility of the IT environment. In this paper, to achieve a trade-off between manufacturing resources and network resources, the manufacturing network is modeled with multi-agent, in which two kinds of basic elements, the manufacturing application unit and the network carrier of manufacturing information, are presented. And their main characters are described by colored petri net. The manufacturing application model drives the network platform that inversely provides this application model technology supports. The proposed multi-agent system is demonstrated through an example integration scenario involving production plan, resources management and execution subsystems. And the result suggests that analyzing and designing the system architecture of networked manufacturing should give due attention to the operation system as well as manufacturing applications.

  1. A Multi-Agent Approach for Solving Traveling Salesman Problem

    Institute of Scientific and Technical Information of China (English)

    ZHOU Tiejun; TAN Yihong; XING Lining

    2006-01-01

    The traveling salesman problem (TSP) is a classical optimization problem and it is one of a class of NP-Problem. This paper presents a new method named multi-agent approach based genetic algorithm and ant colony system to solve the TSP. Three kinds of agents with different function were designed in the multi-agent architecture proposed by this paper. The first kind of agent is ant colony optimization agent and its function is generating the new solution continuously. The second kind of agent is selection agent, crossover agent and mutation agent, their function is optimizing the current solutions group. The third kind of agent is fast local searching agent and its function is optimizing the best solution from the beginning of the trial. At the end of this paper, the experimental results have shown that the proposed hybrid approach has good performance with respect to the quality of solution and the speed of computation.

  2. Towards the development of multilevel-multiagent diagnostic aids

    Energy Technology Data Exchange (ETDEWEB)

    Stratton, R.C.; Jarrell, D.B.

    1991-10-01

    Presented here is our methodology for developing automated aids for diagnosing faults in complex systems. We have designed these aids as multilevel-multiagent diagnostic aids based on principles that should be generally applicable to any complex system. In this methodology, multilevel'' refers to information models described at successful levels of abstraction that are tied together in such a way that reasoning is directed to the appropriate level as determined by the problem solving requirements. The concept of multiagent'' refers to the method of information processing within the multilevel model network; each model in the network is an independent information processor, i.e., an intelligent agent. 19 refs., 15 figs., 9 tabs.

  3. Multiagent based protection and control in decentralized electric power systems

    DEFF Research Database (Denmark)

    Saleem, Arshad; Lind, Morten; Veloso, Manuela

    2010-01-01

    created interesting possibilities for application of intelligent systems such as multiagent systems for control and automation in electric power systems. This paper describes work on designing a multiagent system for protection and control of electric power distribution networks.It demonstrates how......Electric power systems are going through a major change both in their physical and control structure. A large num- ber of small and geographically dispersed power generation units (e.g., wind turbines, solar cells, plug-in electric cars) are replacing big centralized power plants. This shift has...... explicit modeling of capabilities, states, roles and role transition in agents can capture the control and automation in electric power systems. We present illustrative results from using our proposed schema in realistic simulations....

  4. Integration of Heterogeneous Systems as Multi-Agent Systems

    Directory of Open Access Journals (Sweden)

    Ammar Lahlouhi

    2014-08-01

    Full Text Available Systems integration is a difficult matter particularly when its components are varied. The problem becomes even more difficult when such components are heterogeneous such as humans, robots and software systems. Currently, the humans are regarded as users of artificial systems (robots and software systems. This has several disadvantages such as: (1 incoherence of artificial systems exploitation where humans’ roles are not clear, and (2 vain research of a user’s universal model. In this paper, we adopted a cooperative approach where the system’s components are regarded as being of the same level and they cooperate for the service of the global system. We concretized such approach by considering humans, robots and software systems as autonomous agents assuming roles in an organization. The latter will be implemented as a multi-agent system developed using a multi-agent development methodology.

  5. Technology of structure damage monitoring based on multi-agent

    Institute of Scientific and Technical Information of China (English)

    Hongbing Sun; Shenfang Yuan; Xia Zhao; Hengbao Zhou; Dong Liang

    2010-01-01

    The health monitoring for large-scale structures need to resolve a large number of difficulties,such as the data transmission and distributing information handling.To solve these problems,the technology of multi-agent is a good candidate to be used in the field of structural health monitoring.A structural health monitoring system architecture based on multi-agent technology is proposed.The measurement system for aircraft airfoil is designed with FBG,strain gage,and corresponding signal processing circuit.The experiment to determine the location of the concentrate loading on the structure is carried on with the system combined with technologies of pattern recognition and multi-agent.The results show that the system can locate the concentrate loading of the aircraft airfoil at the accuracy of 91.2%.

  6. Hybrid BDI-POMDP Framework for Multiagent Teaming

    CERN Document Server

    Nair, R; 10.1613/jair.1549

    2011-01-01

    Many current large-scale multiagent team implementations can be characterized as following the belief-desire-intention (BDI) paradigm, with explicit representation of team plans. Despite their promise, current BDI team approaches lack tools for quantitative performance analysis under uncertainty. Distributed partially observable Markov decision problems (POMDPs) are well suited for such analysis, but the complexity of finding optimal policies in such models is highly intractable. The key contribution of this article is a hybrid BDI-POMDP approach, where BDI team plans are exploited to improve POMDP tractability and POMDP analysis improves BDI team plan performance. Concretely, we focus on role allocation, a fundamental problem in BDI teams: which agents to allocate to the different roles in the team. The article provides three key contributions. First, we describe a role allocation technique that takes into account future uncertainties in the domain; prior work in multiagent role allocation has failed to addr...

  7. Multiagent based protection and control in decentralized electric power systems

    DEFF Research Database (Denmark)

    Saleem, Arshad; Lind, Morten; Veloso, Manuela

    2010-01-01

    Electric power systems are going through a major change both in their physical and control structure. A large num- ber of small and geographically dispersed power generation units (e.g., wind turbines, solar cells, plug-in electric cars) are replacing big centralized power plants. This shift has...... created interesting possibilities for application of intelligent systems such as multiagent systems for control and automation in electric power systems. This paper describes work on designing a multiagent system for protection and control of electric power distribution networks.It demonstrates how...... explicit modeling of capabilities, states, roles and role transition in agents can capture the control and automation in electric power systems. We present illustrative results from using our proposed schema in realistic simulations....

  8. Multi-Agent System Interaction in Integrated SCM

    CERN Document Server

    Sindhu, Ritu; Purohit, G N

    2009-01-01

    Coordination between organizations on strategic, tactical and operation levels leads to more effective and efficient supply chains. Supply chain management is increasing day by day in modern enterprises. The environment is becoming competitive and many enterprises will find it difficult to survive if they do not make their sourcing, production and distribution more efficient. Multi-agent supply chain management has recognized as an effective methodology for supply chain management. Multi-agent systems (MAS) offer new methods compared to conventional, centrally organized architectures in the scope of supply chain management (SCM). Since necessary data are not available within the whole supply chain, an integrated approach for production planning and control taking into account all the partners involved is not feasible. In this study we show how MAS architecture interacts in the integrated SCM architecture with the help of various intelligent agents to highlight the above problem.

  9. EDM COLLABORATIVE MANUFACTURING SYSTEM BASED ON MULTI-AGENT TECHNIQUES

    Institute of Scientific and Technical Information of China (English)

    Zhao Wansheng; Zhao Jinzhi; Song Yinghui; Yang Xiaodong

    2003-01-01

    A framework for building EDM collaborative manufacturing system using multi-agent technology to support organizations characterized by physically distributed, enterprise-wide, heterogeneous intelligent manufacturing system over Internet is proposed. Expert system theory is introduced.Design, manufacturing and technological knowledge are shared using artificial intelligence and web techniques by EDM-CADagent, EDM-CAMagent and EDM-CAPPagent. System structure, design process, network conditions, realization methods and other key techniques are discussed. Instances are also introduced to testify feasibility.

  10. Cooperative Output Regulation of Singular Heterogeneous Multiagent Systems.

    Science.gov (United States)

    Ma, Qian; Xu, Shengyuan; Lewis, Frank L; Zhang, Baoyong; Zou, Yun

    2016-06-01

    This paper investigates the cooperative output regulation problem of singular heterogeneous multiagent systems. General distributed observers are proposed for every agent obtaining the estimated state of the exosystem. The feedforward control technique and reduced-order approach are used to design distributed singular output feedback controllers and distributed normal output feedback controllers. The proposed cooperative dynamic controller is dependent on the plant parameters and the interaction topologies. A simulation example is provided to demonstrate the effectiveness of the proposed design method.

  11. Negotiation and argumentation in multi-agent systems

    CERN Document Server

    Lopes, Fernando

    2014-01-01

    Multi-agent systems (MAS) composed of autonomous agents representing individuals or organizations and capable of reaching mutually beneficial agreements through negotiation and argumentation are becoming increasingly important and pervasive.Research on both automated negotiation and argumentation in MAS has a vigorous, exciting tradition. However, efforts to integrate both areas have received only selective attention in the academia and the practitioner literature. A symbiotic relationship could significantly strengthen each area's progress and trigger new R&D challenges and prospects toward t

  12. Consensus of Multiagent Networks with Intermittent Interaction and Directed Topology

    Directory of Open Access Journals (Sweden)

    Li Xiao

    2014-01-01

    Full Text Available Intermittent interaction control is introduced to solve the consensus problem for second-order multiagent networks due to the limited sensing abilities and environmental changes periodically. And, we get some sufficient conditions for the agents to reach consensus with linear protocol from the theoretical findings by using the Lyapunov control approach. Finally, the validity of the theoretical results is validated through the numerical example.

  13. Multiagent Task Coordination Using a Distributed Optimization Approach

    Science.gov (United States)

    2015-09-01

    kinematic mobile robots in formation along a time-parameterized path,” IEEE/ASME Transactions on Mechatronics , vol. 17, pp. 326–336, 2012. [2] M. Arcak...of engineered multiagent systems such as robotic networks, sensor networks, and computer networks, and they are important to both military and...uncertainties, and conduct computer simulation and experimental validation of the proposed designs using mobile robotic platforms. The project renders

  14. Biomorphic Multi-Agent Architecture for Persistent Computing

    Science.gov (United States)

    Lodding, Kenneth N.; Brewster, Paul

    2009-01-01

    A multi-agent software/hardware architecture, inspired by the multicellular nature of living organisms, has been proposed as the basis of design of a robust, reliable, persistent computing system. Just as a multicellular organism can adapt to changing environmental conditions and can survive despite the failure of individual cells, a multi-agent computing system, as envisioned, could adapt to changing hardware, software, and environmental conditions. In particular, the computing system could continue to function (perhaps at a reduced but still reasonable level of performance) if one or more component( s) of the system were to fail. One of the defining characteristics of a multicellular organism is unity of purpose. In biology, the purpose is survival of the organism. The purpose of the proposed multi-agent architecture is to provide a persistent computing environment in harsh conditions in which repair is difficult or impossible. A multi-agent, organism-like computing system would be a single entity built from agents or cells. Each agent or cell would be a discrete hardware processing unit that would include a data processor with local memory, an internal clock, and a suite of communication equipment capable of both local line-of-sight communications and global broadcast communications. Some cells, denoted specialist cells, could contain such additional hardware as sensors and emitters. Each cell would be independent in the sense that there would be no global clock, no global (shared) memory, no pre-assigned cell identifiers, no pre-defined network topology, and no centralized brain or control structure. Like each cell in a living organism, each agent or cell of the computing system would contain a full description of the system encoded as genes, but in this case, the genes would be components of a software genome.

  15. Modeling Ambiguity in a Multi-Agent System

    OpenAIRE

    Monz, Christof

    2000-01-01

    This paper investigates the formal pragmatics of ambiguous expressions by modeling ambiguity in a multi-agent system. Such a framework allows us to give a more refined notion of the kind of information that is conveyed by ambiguous expressions. We analyze how ambiguity affects the knowledge of the dialog participants and, especially, what they know about each other after an ambiguous sentence has been uttered. The agents communicate with each other by means of a TELL-function, whose applicati...

  16. Research on Cognitive Cooperation in Multi-Agent Systems

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The accomplishment of a complex problem usually involves cooperation between participators with different knowledge background concerned. This paper identifies inter-dependency between different sub problems (through problem decomposition) as the major factor that influences cooperative relations in multi-Agent systems, based on which we propose an efficient means to measure cooperation coefficient (degree) between different Agents. Then cognitive cooperation between Agents is analyzed which aims at collecting the wisdom of the cognitive community for a systematic solution to the overall problem.

  17. Multi-Agent System to Monitor Oceanic Environments

    OpenAIRE

    Bajo Pérez, Javier; Paz Santana, Juan Francisco de; Rodríguez, Sara; Angélica GONZÁLEZ ARRIETA

    2010-01-01

    [EN]The exchange of C02 between the atmosphere and the ocean surface is a problem that has become increasingly important due to its impact on climatic behavior. Given the large quantity of sources of information available for studying the C02 problem, it is necessary to provide innovative solutions that facilitate the automation of certain tasks and incorporate decís ion support systems to obtain a better understanding of this phenomenon. This paper presents a multiagent architecture ai...

  18. Consensus of Heterogeneous Multiagent Systems with Arbitrarily Bounded Communication Delay

    Directory of Open Access Journals (Sweden)

    Xue Li

    2017-01-01

    Full Text Available This paper focuses on the consensus problem of high-order heterogeneous multiagent systems with arbitrarily bounded communication delays. Through the method of nonnegative matrices, we get a sufficient consensus condition for the systems with dynamically changing topology. The results of this paper show, even when there are arbitrarily bounded communication delays in the systems, all agents can reach a consensus no matter whether there are spanning trees for the corresponding communication graphs at any time.

  19. Intrusion Correlation Using Ontologies and Multi-agent Systems

    Science.gov (United States)

    Isaza, Gustavo; Castillo, Andrés; López, Marcelo; Castillo, Luis; López, Manuel

    This paper proposes an ontology model for representing intrusion detection events and prevention rules, integrating multiagent systems based on unsupervised and supervised techniques for classification, correlation and pattern recognition. The semantic model describes attacks signatures, reaction tasks, axioms with alerts communication and correlation; nevertheless we have developed the prevention architecture integrated with another security tools. This article focuses on the approach to incorporate semantic operations that facilitate alerts correlation process and providing the inference and reasoning to the ontology model.

  20. Multi-Agent Active Interaction with Driving Assistance Systems

    OpenAIRE

    Barthès, Jean-Paul,; Bonnifait, Philippe

    2010-01-01

    7 pages; International audience; Intelligent vehicles refer currently to vehicles able to drive autonomously or able to provide pertinent information to the driver for safety, assistance and comfort. Cognitive cars are intelligent vehicles with additional capabilities like being able to collaborate with the driver in operating conditions. In this paper, a multi-agent system is used as a “digital butler” that does the interface between the driver and the machine. In order to test this approach...

  1. Robot soccer simulation competition platform based on multi-agent

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Presents the robot soccer software simulation platform to be firstly used at FIRA Robot World Cup China 2001, introduces the system's purpose and design plan; discusses the system core-server configuration and working principle; describes the operating method and how to develop competition strategy, and refers to the teams to take part in FIRA Robot World Cup China 2001 and investigators who are interested in the distribu ted multi-agent system.

  2. Hardware-Assisted Large-Scale Neuroevolution for Multiagent Learning

    Science.gov (United States)

    2014-12-30

    commercial, stackable full speed multi-FPGA based prototyping platform, in- tegrated with DAC/ ADC modules for mixed signal and digital communications ... communications , but also has high reusability, i.e., a new application needs not change a BCM’s hardware design, only new task graph processing and code...where the pipeline stages seldom exceed 10 due to data dependencies, in the proposed multiagent training platform, we pipeline each process- ing

  3. Multi-Agent System Interaction in Integrated SCM

    OpenAIRE

    G. N. Purohit; Abdul Wahid; Ritu Sindhu

    2009-01-01

    Coordination between organizations on strategic, tactical and operation levels leads to more effective and efficient supply chains. Supply chain management is increasing day by day in modern enterprises. The environment is becoming competitive and many enterprises will find it difficult to survive if they do not make their sourcing, production and distribution more efficient. Multi-agent supply chain management has recognized as an effective methodology for supply chain management. Multi-agen...

  4. Multi-agent systems and decentralized artificial superintelligence

    OpenAIRE

    Ponomarev, S.; Voronkov, A. E.

    2017-01-01

    Multi-agents systems communication is a technology, which provides a way for multiple interacting intelligent agents to communicate with each other and with environment. Multiple-agent systems are used to solve problems that are difficult for solving by individual agent. Multiple-agent communication technologies can be used for management and organization of computing fog and act as a global, distributed operating system. In present publication we suggest technology, which combines decentrali...

  5. Optimizing medical data quality based on multiagent web service framework.

    Science.gov (United States)

    Wu, Ching-Seh; Khoury, Ibrahim; Shah, Hemant

    2012-07-01

    One of the most important issues in e-healthcare information systems is to optimize the medical data quality extracted from distributed and heterogeneous environments, which can extremely improve diagnostic and treatment decision making. This paper proposes a multiagent web service framework based on service-oriented architecture for the optimization of medical data quality in the e-healthcare information system. Based on the design of the multiagent web service framework, an evolutionary algorithm (EA) for the dynamic optimization of the medical data quality is proposed. The framework consists of two main components; first, an EA will be used to dynamically optimize the composition of medical processes into optimal task sequence according to specific quality attributes. Second, a multiagent framework will be proposed to discover, monitor, and report any inconstancy between the optimized task sequence and the actual medical records. To demonstrate the proposed framework, experimental results for a breast cancer case study are provided. Furthermore, to show the unique performance of our algorithm, a comparison with other works in the literature review will be presented.

  6. An Intelligent Multiagent System for Autonomous Microgrid Operation

    Directory of Open Access Journals (Sweden)

    Tetsuo Kinoshita

    2012-09-01

    Full Text Available A microgrid is an eco-friendly power system because renewable sources such as solar and wind power are used as the main power sources. For this reason, much research, development, and demonstration projects have recently taken place in many countries. Operation is one of the important research topics for microgrids. For efficient and economical microgrid operation, a human operator is required as in other power systems, but it is difficult because there are some restrictions related to operation costs and privacy issues. To overcome the restriction, autonomous operation for microgrids is required. Recently, an intelligent agent system for autonomous microgrid operation has been studied as a potential solution. This paper proposes a multiagent system for autonomous microgrid operation. To build the multiagent system, the functionalities of agents, interactions among agents, and an effective agent protocol have been designed. The proposed system has been implemented by using an ADIPS/DASH framework as an agent platform. The intelligent multiagent system for microgrid operation based on the proposed scheme is tested to show the functionality and feasibility on a distributed environment through the Internet.

  7. Quicker Q-Learning in Multi-Agent Systems

    Science.gov (United States)

    Agogino, Adrian K.; Tumer, Kagan

    2005-01-01

    Multi-agent learning in Markov Decisions Problems is challenging because of the presence ot two credit assignment problems: 1) How to credit an action taken at time step t for rewards received at t' greater than t; and 2) How to credit an action taken by agent i considering the system reward is a function of the actions of all the agents. The first credit assignment problem is typically addressed with temporal difference methods such as Q-learning OK TD(lambda) The second credit assi,onment problem is typically addressed either by hand-crafting reward functions that assign proper credit to an agent, or by making certain independence assumptions about an agent's state-space and reward function. To address both credit assignment problems simultaneously, we propose the Q Updates with Immediate Counterfactual Rewards-learning (QUICR-learning) designed to improve both the convergence properties and performance of Q-learning in large multi-agent problems. Instead of assuming that an agent s value function can be made independent of other agents, this method suppresses the impact of other agents using counterfactual rewards. Results on multi-agent grid-world problems over multiple topologies show that QUICR-learning can achieve up to thirty fold improvements in performance over both conventional and local Q-learning in the largest tested systems.

  8. Management of Reinforcement Corrosion

    DEFF Research Database (Denmark)

    Küter, André; Geiker, Mette Rica; Møller, Per

    Reinforcement corrosion is the most important cause for deterioration of reinforced concrete structures, both with regard to costs and consequences. Thermodynamically consistent descriptions of corrosion mechanisms are expected to allow the development of innovative concepts for the management...... of reinforcement corrosion....

  9. Partial Planning Reinforcement Learning

    Science.gov (United States)

    2012-08-31

    This project explored several problems in the areas of reinforcement learning , probabilistic planning, and transfer learning. In particular, it...studied Bayesian Optimization for model-based and model-free reinforcement learning , transfer in the context of model-free reinforcement learning based on

  10. Variable Resolution Reinforcement Learning.

    Science.gov (United States)

    1995-04-01

    Can reinforcement learning ever become a practical method for real control problems? This paper begins by reviewing three reinforcement learning algorithms... reinforcement learning . In addition to exploring state space, and developing a control policy to achieve a task, partigame also learns a kd-tree partitioning of

  11. Detecting Hierarchical Structure in Networks

    DEFF Research Database (Denmark)

    Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard;

    2012-01-01

    a generative Bayesian model that is able to infer whether hierarchies are present or not from a hypothesis space encompassing all types of hierarchical tree structures. For efficient inference we propose a collapsed Gibbs sampling procedure that jointly infers a partition and its hierarchical structure......Many real-world networks exhibit hierarchical organization. Previous models of hierarchies within relational data has focused on binary trees; however, for many networks it is unknown whether there is hierarchical structure, and if there is, a binary tree might not account well for it. We propose....... On synthetic and real data we demonstrate that our model can detect hierarchical structure leading to better link-prediction than competing models. Our model can be used to detect if a network exhibits hierarchical structure, thereby leading to a better comprehension and statistical account the network....

  12. Output Synchronization of Nonidentical Linear Multiagent Systems.

    Science.gov (United States)

    Wu, Yuanqing; Su, Hongye; Shi, Peng; Lu, Renquan; Wu, Zheng-Guang

    2017-01-01

    In this paper, the problem of output synchronization is investigated for the heterogeneous network with an uncertain leader. It is assumed that parameter perturbations influence the nonidentical linear agents, whose outputs are controlled to track the output of an uncertain leader. Based on the hierarchical structure of the communication graph, a novel control scheme is proposed to guarantee the output synchronization. As there exist parameter uncertainties in the models of the agents, the internal model principle is used to gain robustness versus plant parameter uncertainties. Furthermore, as the precise model of the leader is also not available, the adaptive control principle is adopted to tune the parameters in the local controllers. The developed new technique is able to simultaneously handle uncertainties in the follower parameters as well as the leader parameters. The agents in the upper layers will be treated as the exosystems of the agents in the lower layers. The local controllers are constructed in a sequential order. It is shown that the output synchronization can be achieved globally asymptotically and locally exponentially. Finally, a simulation example is given to illustrate the effectiveness and potential of the theoretic results obtained.

  13. Context updates are hierarchical

    Directory of Open Access Journals (Sweden)

    Anton Karl Ingason

    2016-10-01

    Full Text Available This squib studies the order in which elements are added to the shared context of interlocutors in a conversation. It focuses on context updates within one hierarchical structure and argues that structurally higher elements are entered into the context before lower elements, even if the structurally higher elements are pronounced after the lower elements. The crucial data are drawn from a comparison of relative clauses in two head-initial languages, English and Icelandic, and two head-final languages, Korean and Japanese. The findings have consequences for any theory of a dynamic semantics.

  14. The Deontic Transaction Model in Multi-Agent Normative Systems

    Science.gov (United States)

    Huang, Yonghua; Esterline, Albert

    1998-01-01

    In the area of multi-agent systems, much research is devoted to the coordination of the agents. There exist several issues, two of which are summarized. The first is that, although agents are said to be autonomous, they always react in a predictable way to each message, and they cannot decide to violate the conventions that are hard-wired into the protocol. In fact, there might be circumstances in which the agent violates a convention in order to realize a private goal that it considers to be more important. Another issue is that, if the protocols that agents use to react to the environment are fixed, they have no way to respond to changes. However, an important characteristic of agents is that they eon react to a changing environment. Although transaction models ([BOH92], [GR93]) evolved from the database domain, they establish a general execution paradigm that ideally covers all the subsystems invoked in a sequence of transactions. So transaction models apply to multi-agent systems. Recently, some research has been devoted to overcoming the limitations of the traditional transaction models which are suitable for conventional systems and focus on system integrity, e,g., [SJ97]. Here we solve above issues by turning to a deontic concept: obligation. In multi-agent systems, agents interact with each other according to norms, We use deontic logic ([And58], [Aqv84], [B C96], [JS94], [MW93]) to model norms. Here the norms prescribe how the agents ought to behave, but-- and this is essential-- they do not exclude the possibility of "bad" behavior (i.e., the actual behavior may deviate from the ideal), and so they also prescribe what should be done in circumstances of norm violation. Thus, we propose a new approach --- a deontic transaction model for multi-agent normative systems. Our approach improves the protocol of "abort/commit" of traditional transaction models to a protocol of "abort/exception/commit". In multi-agent normative systems, we can see the violation of a

  15. Multiagent Simulation of the Hepatitis B Epidemic Process

    Science.gov (United States)

    Chumachenko, Tetyana; Chumachenko, Dmytro; Sokolov, Olexandr

    2013-01-01

    Objective To develop multiagent model of hepatitis B (HBV) infection spreading. Introduction The standard approaches to simulation include solving of differential equation systems. Such approach is good for obtaining general picture of epidemics (1, 2). When the detailed analysis of epidemics reasons is needed such model becomes insufficient. To overcome the limitations of standard approaches a new one has been offered. The multiagent approach has been offered to be used for representation of the society. Methods of event-driven programming give essential benefits of the processing time of the events (3). Methods For model development C# computing language has been used. We have used demographical data, the incidence rate of HBV infection of all population and different population groups (age, professional and other groups), coverage of hepatitis B vaccination, the proportion of HBV carriers in population, the prevalence rate of chronic HBV infection, percent of dominated transmission routes and factors and other rates in Kharkiv region. All parameters, expressed in the model were estimated using sero-surveys data and data of epidemiological surveillance of Kharkiv region sanitary-epidemiological station. Also the theoretical knowledge about HBV infection has been used. 26 conditions have been derived from the problem domain. The transition from one condition to another depends on stochastic value and time of the event change. All events are organized in priority queue which results in high rate of computation performance. The dependence on time and random value determines automata theory conceptions. Results The prototype of software system, which includes a subsystem of the multiagent simulation and specialized statistical and mathematical sub-system which can process the simulation results and perform a conditional optimization of the selected objective functions (morbidity, the effectiveness of specific preventive and control activities and their price, measure

  16. Soil Reinforcement Techniques

    Directory of Open Access Journals (Sweden)

    Prashant Patil

    2016-08-01

    Full Text Available In many activities concerned with the use of soil, the physical properties like Stiffness, Compressibility and Strength are some of the few important parameters to be considered. Of the many methods involved in improvement of soil properties, soil reinforcement is method concerned with increase of strength properties of soil. In soil reinforcement, the reinforcements or resisting element are of different materials and of various forms depending upon the intended use. The reinforcement can be provided permanently or temporarily to increase strength of adjacent structures. The present topic of discussion involves different materials, forms and applications of soil reinforcement

  17. Designing Agent Utilities for Coordinated, Scalable and Robust Multi-Agent Systems

    Science.gov (United States)

    Tumer, Kagan

    2005-01-01

    Coordinating the behavior of a large number of agents to achieve a system level goal poses unique design challenges. In particular, problems of scaling (number of agents in the thousands to tens of thousands), observability (agents have limited sensing capabilities), and robustness (the agents are unreliable) make it impossible to simply apply methods developed for small multi-agent systems composed of reliable agents. To address these problems, we present an approach based on deriving agent goals that are aligned with the overall system goal, and can be computed using information readily available to the agents. Then, each agent uses a simple reinforcement learning algorithm to pursue its own goals. Because of the way in which those goals are derived, there is no need to use difficult to scale external mechanisms to force collaboration or coordination among the agents, or to ensure that agents actively attempt to appropriate the tasks of agents that suffered failures. To present these results in a concrete setting, we focus on the problem of finding the sub-set of a set of imperfect devices that results in the best aggregate device. This is a large distributed agent coordination problem where each agent (e.g., device) needs to determine whether to be part of the aggregate device. Our results show that the approach proposed in this work provides improvements of over an order of magnitude over both traditional search methods and traditional multi-agent methods. Furthermore, the results show that even in extreme cases of agent failures (i.e., half the agents failed midway through the simulation) the system's performance degrades gracefully and still outperforms a failure-free and centralized search algorithm. The results also show that the gains increase as the size of the system (e.g., number of agents) increases. This latter result is particularly encouraging and suggests that this method is ideally suited for domains where the number of agents is currently in the

  18. Multiagent System-Based Distributed Coordinated Control for Radial DC Microgrid Considering Transmission Time Delays

    DEFF Research Database (Denmark)

    Dou, Chun-Xia; Yue, Dong; Guerrero, Josep M.

    2017-01-01

    This paper focuses on a multi-agent based distributed coordinated control for radial DC microgrid considering trans-mission time delays. Firstly, a two-level multi-agent system is constructed, where local control is formulated based on local states and executed by means of the first-level agent...

  19. Activity Theory: A Framework for Understanding Multi-Agency Working and Engaging Service Users in Change

    Science.gov (United States)

    Greenhouse, Paul Michael

    2013-01-01

    This article discusses the quality of professional relationships between educational psychologists (EPs) and other professionals who work around children, young people and their families as part of a multi-agency team (MAT). The perceived barriers to, and facilitators of, effective multi-agency working are explored in relation to their potential…

  20. Compositional Design and Verification of a Multi-Agent System for One-to-Many Negotiation

    NARCIS (Netherlands)

    Brazier, F.M.T.; Cornelissen, F.; Gustavsson, R.; Jonker, C.M.; Lindeberg, O.; Polak, B.; Treur, J.

    1998-01-01

    A compositional verification method for multi-agent systems is presented and applied to a multi-agent system for one-to-many negotiation in the domain of load balancing of electricity use. Advantages of the method are that the complexity of the

  1. Developing Multi-Agency Teams: Implications of a National Programme Evaluation

    Science.gov (United States)

    Simkins, Tim; Garrick, Ros

    2012-01-01

    This paper explores the factors which influence the effectiveness of formal development programmes targeted at multi-agency teams in children's services. It draws on two studies of the National College for School Leadership's Multi-Agency Teams Development programme, reporting key characteristics of the programme, short-term outcomes in terms of…

  2. Multi-agent robotic systems and applications for satellite missions

    Science.gov (United States)

    Nunes, Miguel A.

    A revolution in the space sector is happening. It is expected that in the next decade there will be more satellites launched than in the previous sixty years of space exploration. Major challenges are associated with this growth of space assets such as the autonomy and management of large groups of satellites, in particular with small satellites. There are two main objectives for this work. First, a flexible and distributed software architecture is presented to expand the possibilities of spacecraft autonomy and in particular autonomous motion in attitude and position. The approach taken is based on the concept of distributed software agents, also referred to as multi-agent robotic system. Agents are defined as software programs that are social, reactive and proactive to autonomously maximize the chances of achieving the set goals. Part of the work is to demonstrate that a multi-agent robotic system is a feasible approach for different problems of autonomy such as satellite attitude determination and control and autonomous rendezvous and docking. The second main objective is to develop a method to optimize multi-satellite configurations in space, also known as satellite constellations. This automated method generates new optimal mega-constellations designs for Earth observations and fast revisit times on large ground areas. The optimal satellite constellation can be used by researchers as the baseline for new missions. The first contribution of this work is the development of a new multi-agent robotic system for distributing the attitude determination and control subsystem for HiakaSat. The multi-agent robotic system is implemented and tested on the satellite hardware-in-the-loop testbed that simulates a representative space environment. The results show that the newly proposed system for this particular case achieves an equivalent control performance when compared to the monolithic implementation. In terms on computational efficiency it is found that the multi-agent

  3. Habituation of reinforcer effectiveness

    Directory of Open Access Journals (Sweden)

    David R Lloyd

    2014-01-01

    Full Text Available In this paper we propose an integrative model of habituation of reinforcer effectiveness (HRE that links behavioral and neural based explanations of reinforcement. We argue that habituation of reinforcer effectiveness (HRE is a fundamental property of reinforcing stimuli. Most reinforcement models implicitly suggest that the effectiveness of a reinforcer is stable across repeated presentations. In contrast, an HRE approach predicts decreased effectiveness due to repeated presentation. We argue that repeated presentation of reinforcing stimuli decreases their effectiveness and that these decreases are described by the behavioral characteristics of habituation (McSweeney and Murphy, 2009;Rankin et al., 2009. We describe a neural model that postulates a positive association between dopamine neurotransmission and HRE. We present evidence that stimulant drugs, which artificially increase dopamine neurotransmission, disrupt (slow normally occurring HRE and also provide evidence that stimulant drugs have differential effects on operant responding maintained by reinforcers with rapid vs. slow HRE rates. We hypothesize that abnormal HRE due to genetic and/or environmental factors may underlie some behavioral disorders. For example, recent research indicates that slow-HRE is predictive of obesity. In contrast ADHD may reflect ‘accelerated-HRE’. Consideration of HRE is important for the development of effective reinforcement based treatments. Finally, we point out that most of the reinforcing stimuli that regulate daily behavior are non-consumable environmental/social reinforcers which have rapid-HRE. The almost exclusive use of consumable reinforcers with slow-HRE in pre-clinical studies with animals may have caused the importance of HRE to be overlooked. Further study of reinforcing stimuli with rapid-HRE is needed in order to understand how habituation and reinforcement interact and regulate behavior.

  4. An Improved Reinforcement Learning System Using Affective Factors

    Directory of Open Access Journals (Sweden)

    Takashi Kuremoto

    2013-07-01

    Full Text Available As a powerful and intelligent machine learning method, reinforcement learning (RL has been widely used in many fields such as game theory, adaptive control, multi-agent system, nonlinear forecasting, and so on. The main contribution of this technique is its exploration and exploitation approaches to find the optimal solution or semi-optimal solution of goal-directed problems. However, when RL is applied to multi-agent systems (MASs, problems such as “curse of dimension”, “perceptual aliasing problem”, and uncertainty of the environment constitute high hurdles to RL. Meanwhile, although RL is inspired by behavioral psychology and reward/punishment from the environment is used, higher mental factors such as affects, emotions, and motivations are rarely adopted in the learning procedure of RL. In this paper, to challenge agents learning in MASs, we propose a computational motivation function, which adopts two principle affective factors “Arousal” and “Pleasure” of Russell’s circumplex model of affects, to improve the learning performance of a conventional RL algorithm named Q-learning (QL. Compared with the conventional QL, computer simulations of pursuit problems with static and dynamic preys were carried out, and the results showed that the proposed method results in agents having a faster and more stable learning performance.

  5. Multi-agent Optimal Control of Ball Balancing on a Mobile

    Directory of Open Access Journals (Sweden)

    Adel Akbarimajd

    2015-12-01

    Full Text Available Multi-agent systems have origin in computer engineering however, they have found applications in different field. One of the newly emerged problems in multi-agent systems is multi-agent control. In multi-agent control it is desired that the control is done in distributed manner. That is the controller of each agent should be implemented based on local feedback. In this a mechanism is introuded as a test bed for multi-agent control systems. The introduced mechanism is balancing of a ball on link located on a planar mobile robot. Dynamic equations of the mechanism is derived and the control task is distributed among two agents. For each agent a two loop controller designed wherein external loop is a LQR controller and inner loop is a simple proportional controller. Regulation and fault tolerance performance of controller scheme is evaluated by simulations.

  6. Role Based Multi-Agent System for E-Learning (MASeL

    Directory of Open Access Journals (Sweden)

    Mustafa Hameed

    2016-03-01

    Full Text Available Software agents are autonomous entities that can interact intelligently with other agents as well as their environment in order to carry out a specific task. We have proposed a role-based multi-agent system for e-learning. This multi-agent system is based on Agent-Group-Role (AGR method. As a multi-agent system is distributed, ensuring correctness is an important issue. We have formally modeled our role-based multi-agent system. The correctness properties of liveness and safety are specified as well as verified. Timed-automata based model checker UPPAAL is used for the specification as well as verification of the e-learning system. This results in a formally specified and verified model of the role-based multi-agent system.

  7. Graph-Theoretic Characterizations of Structural Controllability for Multi-Agent System with Switching Topology

    CERN Document Server

    Liu, Xiaomeng; Chen, Ben M

    2012-01-01

    This paper considers the controllability problem for multi-agent systems. In particular, the structural controllability of multi-agent systems under switching topologies is investigated. The structural controllability of multi-agent systems is a generalization of the traditional controllability concept for dynamical systems, and purely based on the communication topologies among agents. The main contributions of the paper are graph-theoretic characterizations of the structural controllability for multi-agent systems. It turns out that the multi-agent system with switching topology is structurally controllable if and only if the union graph G of the underlying communication topologies is connected (single leader) or leader-follower connected (multi-leader). Finally, the paper concludes with several illustrative examples and discussions of the results and future work.

  8. Trends in practical applications of heterogeneous multi-agent systems : the PAAMS collection

    CERN Document Server

    Rodríguez, Juan; Mathieu, Philippe; Campbell, Andrew; Ortega, Alfonso; Adam, Emmanuel; Navarro, Elena; Ahrndt, Sebastian; Moreno, María; Julián, Vicente

    2014-01-01

    PAAMS, the International Conference on Practical Applications of Agents and Multi-Agent Systems is an evolution of the International Workshop on Practical Applications of Agents and Multi-Agent Systems. PAAMS is an international yearly tribune to present, to discuss, and to disseminate the latest developments and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to exchange their experience in the development of Agents and Multi-Agent Systems. This volume presents the papers that have been accepted for the 2014 special sessions: Agents Behaviours and Artificial Markets (ABAM), Agents and Mobile Devices (AM), Bio-Inspired and Multi-Agents Systems: Applications to Languages (BioMAS), Multi-Agent Systems and Ambient Intelligence (MASMAI), Self-Explaining Agents (SEA), Web Mining and Recommender systems (WebMiRes) and Intelligent Educational Systems (SSIES).

  9. A Distributed Cooperative Dynamic Task Planning Algorithm for Multiple Satellites Based on Multi-agent Hybrid Learning

    Institute of Scientific and Technical Information of China (English)

    WANG Chong; LI Jun; JING Ning; WANG Jun; CHEN Hao

    2011-01-01

    Traditionally,heuristic re-planning algorithms are used to tackle the problem of dynamic task planning for multiple satellites.However,the traditional heuristic strategies depend on the concrete tasks,which often affect the result's optimality.Noticing that the historical information of cooperative task planning will impact the latter planning results,we propose a hybrid learning algorithrn for dynamic multi-satellite task planning,which is based on the multi-agent reinforcement learning of policy iteration and the transfer learning.The reinforcement learning strategy of each satellite is described with neural networks.The policy neural network individuals with the best topological structure and weights are found by applying co-evolutionary search iteratively.To avoid the failure of the historical learning caused by the randomly occurring observation requests,a novel approach is proposed to balance the quality and efficiency of the task planning,which converts the historical leaming strategy to the current initial learning strategy by applying the transfer learning algorithm.The simulations and analysis show the feasibility and adaptability of the proposed approach especially for the situation with randomly occurring observation requests.

  10. Deconstructing multi-agency working: an exploration of how the elicitation of 'tacit knowledge' amongst professionals working in a multi-agency team can inform future practice

    OpenAIRE

    Hymans, Michael

    2007-01-01

    The theory of organisational knowledge creation and conversion clarified the difference between explicit and tacit knowledge and highlighted the importance of tacit knowledge in the workplace. The key components of successful multi-agency working and accompanying group processes have been explained in terms of activity theory and the sharing of different forms of knowledge and practices. This research has illustrated how professionals in a multi-agency family support team construe their role ...

  11. Hierarchical partial order ranking.

    Science.gov (United States)

    Carlsen, Lars

    2008-09-01

    Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritization of polluted sites is given.

  12. Trees and Hierarchical Structures

    CERN Document Server

    Haeseler, Arndt

    1990-01-01

    The "raison d'etre" of hierarchical dustering theory stems from one basic phe­ nomenon: This is the notorious non-transitivity of similarity relations. In spite of the fact that very often two objects may be quite similar to a third without being that similar to each other, one still wants to dassify objects according to their similarity. This should be achieved by grouping them into a hierarchy of non-overlapping dusters such that any two objects in ~ne duster appear to be more related to each other than they are to objects outside this duster. In everyday life, as well as in essentially every field of scientific investigation, there is an urge to reduce complexity by recognizing and establishing reasonable das­ sification schemes. Unfortunately, this is counterbalanced by the experience of seemingly unavoidable deadlocks caused by the existence of sequences of objects, each comparatively similar to the next, but the last rather different from the first.

  13. Hierarchical Affinity Propagation

    CERN Document Server

    Givoni, Inmar; Frey, Brendan J

    2012-01-01

    Affinity propagation is an exemplar-based clustering algorithm that finds a set of data-points that best exemplify the data, and associates each datapoint with one exemplar. We extend affinity propagation in a principled way to solve the hierarchical clustering problem, which arises in a variety of domains including biology, sensor networks and decision making in operational research. We derive an inference algorithm that operates by propagating information up and down the hierarchy, and is efficient despite the high-order potentials required for the graphical model formulation. We demonstrate that our method outperforms greedy techniques that cluster one layer at a time. We show that on an artificial dataset designed to mimic the HIV-strain mutation dynamics, our method outperforms related methods. For real HIV sequences, where the ground truth is not available, we show our method achieves better results, in terms of the underlying objective function, and show the results correspond meaningfully to geographi...

  14. Optimisation by hierarchical search

    Science.gov (United States)

    Zintchenko, Ilia; Hastings, Matthew; Troyer, Matthias

    2015-03-01

    Finding optimal values for a set of variables relative to a cost function gives rise to some of the hardest problems in physics, computer science and applied mathematics. Although often very simple in their formulation, these problems have a complex cost function landscape which prevents currently known algorithms from efficiently finding the global optimum. Countless techniques have been proposed to partially circumvent this problem, but an efficient method is yet to be found. We present a heuristic, general purpose approach to potentially improve the performance of conventional algorithms or special purpose hardware devices by optimising groups of variables in a hierarchical way. We apply this approach to problems in combinatorial optimisation, machine learning and other fields.

  15. How hierarchical is language use?

    Science.gov (United States)

    Frank, Stefan L.; Bod, Rens; Christiansen, Morten H.

    2012-01-01

    It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science. PMID:22977157

  16. How hierarchical is language use?

    Science.gov (United States)

    Frank, Stefan L; Bod, Rens; Christiansen, Morten H

    2012-11-22

    It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science.

  17. Associative Hierarchical Random Fields.

    Science.gov (United States)

    Ladický, L'ubor; Russell, Chris; Kohli, Pushmeet; Torr, Philip H S

    2014-06-01

    This paper makes two contributions: the first is the proposal of a new model-The associative hierarchical random field (AHRF), and a novel algorithm for its optimization; the second is the application of this model to the problem of semantic segmentation. Most methods for semantic segmentation are formulated as a labeling problem for variables that might correspond to either pixels or segments such as super-pixels. It is well known that the generation of super pixel segmentations is not unique. This has motivated many researchers to use multiple super pixel segmentations for problems such as semantic segmentation or single view reconstruction. These super-pixels have not yet been combined in a principled manner, this is a difficult problem, as they may overlap, or be nested in such a way that the segmentations form a segmentation tree. Our new hierarchical random field model allows information from all of the multiple segmentations to contribute to a global energy. MAP inference in this model can be performed efficiently using powerful graph cut based move making algorithms. Our framework generalizes much of the previous work based on pixels or segments, and the resulting labelings can be viewed both as a detailed segmentation at the pixel level, or at the other extreme, as a segment selector that pieces together a solution like a jigsaw, selecting the best segments from different segmentations as pieces. We evaluate its performance on some of the most challenging data sets for object class segmentation, and show that this ability to perform inference using multiple overlapping segmentations leads to state-of-the-art results.

  18. Detecting DoS Attack in Web Services by Using an Adaptive Multiagent Solution

    Directory of Open Access Journals (Sweden)

    Chi Shun HONG

    2013-07-01

    Full Text Available Normal 0 21 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} One of the most frequent techniques of a DoS attack is to exhaust available resources (memory, CPU cycles, and bandwidth on the host server. A SOAP message can be affected by a DoS attack if the incoming message has been either created or modified maliciously. Resources available in the server (memory and CPU cycles of the provider can be drastically reduced or exhausted while a malicious SOAP message is being parsed. This article presents a solution based on an adaptive solution for dealing with DoS attacks in Web service environments. The solution proposes a multi-agent hierarchical architecture that implements a classification mechanism in two phases. Each phase incorporates a special type of CBR-BDI agent that functions as a classifier. In the first phase, a case-based reasoning (CBR engine utilizes a decision tree to carry out an initial filter, and in the second phase, a CBR engine incorporates a neural network to complete the classification mechanism. A prototype of the architecture was developed and the results obtained are presented in this study. 

  19. Detecting DoS Attack in Web Services by Using an Adaptive Multiagent Solution

    Directory of Open Access Journals (Sweden)

    Nicholas BELIZ

    2012-09-01

    Full Text Available Normal 0 21 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} One of the most frequent techniques of a DoS attack is to exhaust available resources (memory, CPU cycles, and bandwidth on the host server. A SOAP message can be affected by a DoS attack if the incoming message has been either created or modified maliciously. Resources available in the server (memory and CPU cycles of the provider can be drastically reduced or exhausted while a malicious SOAP message is being parsed. This article presents a solution based on an adaptive solution for dealing with DoS attacks in Web service environments. The solution proposes a multi-agent hierarchical architecture that implements a classification mechanism in two phases. Each phase incorporates a special type of CBR-BDI agent that functions as a classifier. In the first phase, a case-based reasoning (CBR engine utilizes a decision tree to carry out an initial filter, and in the second phase, a CBR engine incorporates a neural network to complete the classification mechanism. A prototype of the architecture was developed and the results obtained are presented in this study. 

  20. Model-based reinforcement learning for partially observable games with sampling-based state estimation.

    Science.gov (United States)

    Fujita, Hajime; Ishii, Shin

    2007-11-01

    Games constitute a challenging domain of reinforcement learning (RL) for acquiring strategies because many of them include multiple players and many unobservable variables in a large state space. The difficulty of solving such realistic multiagent problems with partial observability arises mainly from the fact that the computational cost for the estimation and prediction in the whole state space, including unobservable variables, is too heavy. To overcome this intractability and enable an agent to learn in an unknown environment, an effective approximation method is required with explicit learning of the environmental model. We present a model-based RL scheme for large-scale multiagent problems with partial observability and apply it to a card game, hearts. This game is a well-defined example of an imperfect information game and can be approximately formulated as a partially observable Markov decision process (POMDP) for a single learning agent. To reduce the computational cost, we use a sampling technique in which the heavy integration required for the estimation and prediction can be approximated by a plausible number of samples. Computer simulation results show that our method is effective in solving such a difficult, partially observable multiagent problem.

  1. Modeling hierarchical structures - Hierarchical Linear Modeling using MPlus

    CERN Document Server

    Jelonek, M

    2006-01-01

    The aim of this paper is to present the technique (and its linkage with physics) of overcoming problems connected to modeling social structures, which are typically hierarchical. Hierarchical Linear Models provide a conceptual and statistical mechanism for drawing conclusions regarding the influence of phenomena at different levels of analysis. In the social sciences it is used to analyze many problems such as educational, organizational or market dilemma. This paper introduces the logic of modeling hierarchical linear equations and estimation based on MPlus software. I present my own model to illustrate the impact of different factors on school acceptation level.

  2. Reinforcement Learning: A Tutorial.

    Science.gov (United States)

    1997-01-01

    The purpose of this tutorial is to provide an introduction to reinforcement learning (RL) at a level easily understood by students and researchers in...provides a simple example to develop intuition of the underlying dynamic programming mechanism. In Section (2) the parts of a reinforcement learning problem... reinforcement learning algorithms. These include TD(lambda) and both the residual and direct forms of value iteration, Q-learning, and advantage learning

  3. Mechanically reinforced glass beams

    DEFF Research Database (Denmark)

    Nielsen, Jens Henrik; Olesen, John Forbes

    2007-01-01

    to breakage without any warning or ductility, which can be catastrophic if no precautions are taken. One aspect of this issue is treated here by looking at the possibility of mechanically reinforcing glass beams in order to obtain ductile failure for such a structural component. A mechanically reinforced...... the mechanical behavior of the beam is explained. Finally, some design criterions for reinforced glass beams are discussed....

  4. Designing a multi-agent system for composition

    Directory of Open Access Journals (Sweden)

    K. Borna

    2014-10-01

    Full Text Available The main purpose of this paper is to design a collaborative multi-agent system for providing an XML output which is used in composition. Explaining the performance of rhythm and melody agents is the main part of the paper structure. In this research, systems analysis and design has been adopted as the methodology; and computational calculations have been used. An XML output that is a printable music note can be used by famous music software packages like Sibelius and Final. The novel method introduced in this paper is new and can help musicians make new music with better quality and more diverse content anywhere anytime.

  5. Reimplementing a Multi-Agent System in Python

    DEFF Research Database (Denmark)

    Villadsen, Jørgen; Jensen, Andreas Schmidt; Ettienne, Mikko Berggren

    2013-01-01

    We provide a brief description of our Python-DTU system, including the overall design, the tools and the algorithms that we used in the Multi-Agent Programming Contest 2012, where the scenario was called Agents on Mars like in 2011. Our solution is an improvement of our Python-DTU system from last...... year. Our team ended in second place after winning at least one match against every opponent and we only lost to the winner of the tournament. We briefly describe our experiments with the Moise organizational model. Finally we propose a few areas of improvement, both with regards to our system...

  6. Reimplementing a Multi-Agent System in Python

    DEFF Research Database (Denmark)

    Villadsen, Jørgen; Jensen, Andreas Schmidt; Ettienne, Mikko Berggren

    2012-01-01

    We provide a brief description of our Python-DTU system, including the overall design, the tools and the algorithms that we used in the Multi-Agent Programming Contest 2012, where the scenario was called Agents on Mars like in 2011. Our solution is an improvement of our Python-DTU system from last...... year. Our team ended in second place after winning at least one match against every opponent and we only lost to the winner of the tournament. We briefly describe our experiments with the Moise organizational model. Finally we propose a few areas of improvement, both with regards to our system...

  7. Formation and obstacle avoidance control for multiagent systems

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    This paper considers the problems of formation and obstacle avoidance for multiagent systems.The objective is to design a term of agents that can reach a desired formation while avoiding collision with obstacles.To reduce the amount of information interaction between agents and target,we adopt the leader-follower formation strategy.By using the receding horizon control (RHC),an optimal problem is formulated in terms of cost minimization under constraints.Information on obstacles is incorporated online as se...

  8. Multi-Agent Competition Simulation of Integrated Transportation System

    Directory of Open Access Journals (Sweden)

    Jiashun Zhang

    2013-01-01

    Full Text Available Transportation networks have been developed during the recent decades with the rapid growth of economy. At the same time, the conflicts between different transportation modes were getting more and more intense. To describe the competition relationship in integrated transportation system, a multi-agent competition model was presented. It is important to provide decision support for regulators to lead more reasonable distribution of resources for planning and operating the integrated transportation network. Thus, a simulation program was developed to implement the proposed model and provide computer-aid decision support. Finally, several experiments were conducted to illustrate the effectiveness of this technique.

  9. Innovating Multi-agent Systems Applied to Smart City

    Directory of Open Access Journals (Sweden)

    Michela Longo

    2014-05-01

    Full Text Available The aim of study is to talk about a generic model of Smart City with a multi-agents system and the aspects correlated to Internet. Smart cities are made by a high level of Information and Communication Technology (ICT structures able to transmit energy, information flows multidirectional and connect a different sector that include mobility, energy, social, economy. These components are very important to offer intelligence in a city, as basic infrastructure for a definition of a model repeatable and exportable, as well as supported by the European Community, that is allocating considerable funds (Horizon 2020 for the creation of Smart City.

  10. Space in multi-agent systems modelling spatial processes

    Directory of Open Access Journals (Sweden)

    Petr Rapant

    2007-06-01

    Full Text Available Need for modelling of spatial processes arise in the spehere of geoinformation systems in the last time. Some processes (espetially natural ones can be modeled by means of using external tools, e. g. for modelling of contaminant transport in the environment. But in the case of socio-economic processes suitable tools interconnected with GIS are still in quest of reserch and development. One of the candidate technologies are so called multi-agent systems. Their theory is developed quite well, but they lack suitable means for dealing with space. This article deals with this problem and proposes solution for the field of a road transport modelling.

  11. A Multi-agent player for Settlers of Catan

    OpenAIRE

    2008-01-01

    There are many games that have been a challenge to Research in Artificial Intelligence. One such game is Settlers of Catan (SoC). The purpose of this thesis is to develop a Multi-agent player for SoC. Although it is difficult to focus on all the dimensions of the game during implementation, therefore a good enough solution is proposed. An emphasis is placed on building a good trader for the player. Once a working solution had been built, the player was tested against other players which inclu...

  12. Flocking of multi-agent systems with multiple groups

    Science.gov (United States)

    Jing, Gangshan; Zheng, Yuanshi; Wang, Long

    2014-12-01

    In this paper, we consider the flocking problem of multi-agent systems with multiple groups. First, some algorithms using local information are designed to divide the agents into any pre-assigned number of groups in fixed and switching heterogeneous networks, respectively. Based on algebraic graph theory and Barbalat's lemma, convergence criteria are established to ensure velocity alignment and cohesion of each subgroup as well as collision avoidance between any agents in the whole group. Second, an algorithm for homogeneous networks is studied. Simulation examples are finally presented to verify the effectiveness of our theoretical results.

  13. An Multi-agent Agricultural DDSS Based on Ontology

    Institute of Scientific and Technical Information of China (English)

    JieShen; JianliLuo; YueqinHang; YouzhiXu

    2004-01-01

    This paper propos-nology in terms of the characters of agricultural decision support, and designs a model of DSS about production and sales of agricultural products. The model adopts decentralized+ centralized distributed network topology. In the distributed network, each node is a DSS.Every DSS is made up of multiple agents, which can enhance the interactivity and intel-lectuality among DSS. In the multi-agent system, we embed ontology in the agent system,which has the following advantages: enhancing the coordination and communication between agents, and strengthening the semantics of information and improving knowledge share and reuse.

  14. A Polymeric Bowl for Multi-Agent Delivery.

    Science.gov (United States)

    Hyun, Dong Choon

    2015-08-01

    This paper describes a simple system for multi-agent delivery. The system consists of a biodegradable polymer particle with a hollow interior, together with a hole on its surface that can be completely or partially sealed via thermal annealing. A hydrophobic dye, Nile-red, entrapped within the shell of hollow particles presents a sustained release behavior while methylene blue, a hydrophilic model agent, encapsulated in the hollow interior shows a fast release manner. The release profiles of the probes can be further independently controlled by encapsulating methylene blue-loaded polymer nanoparticles, instead of free dye, in the hollow particle with a small hole on its surface.

  15. A multi-agent system architecture for geographic information gathering.

    Science.gov (United States)

    Gao, Gang-Yi; Wang, Shen-Kang

    2004-11-01

    World Wide Web (WWW) is a vast repository of information, including a great deal of geographic information. But the location and retrieval of geographic information will require a significant amount of time and effort. In addition, different users usually have different views and interests in the same information. To resolve such problems, this paper first proposed a model of geographic information gathering based on multi-Agent (MA) architecture. Then based on this model, we construct a prototype system with GML (Geography Markup Language). This system consists of three tiers-Client, Web Server and Data Resource. Finally, we expatiate on the process of Web Server.

  16. Stabilization Methods for a Multiagent System with Complex Behaviours

    Science.gov (United States)

    Leon, Florin

    2015-01-01

    The main focus of the paper is the stability analysis of a class of multiagent systems based on an interaction protocol which can generate different types of overall behaviours, from asymptotically stable to chaotic. We present several interpretations of stability and suggest two methods to assess the stability of the system, based on the internal models of the agents and on the external, observed behaviour. Since it is very difficult to predict a priori whether a system will be stable or unstable, we propose three heuristic methods that can be used to stabilize such a system during its execution, with minimal changes to its state. PMID:26097491

  17. A multi-Agent system architecture for geographic information gathering

    Institute of Scientific and Technical Information of China (English)

    高刚毅; 王申康

    2004-01-01

    World Wide Web (WWW) is a vast repository of information, including a great deal of geographic information. But the location and retrieval of geographic information will require a significant amount of time and effort. In addition, different users usually have different views and interests in the same information. To resolve such problems, this paper first proposed a model of geographic information gathering based on multi-Agent (MA) architecture. Then based on this model, we construct a prototype system with GML (Geography Markup Language). This system consists of three tiers-Client, Web Server and Data Resource. Finally, we expatiate on the process of Web Server.

  18. Distributed Information Fusion through Advanced Multi-Agent Control

    Science.gov (United States)

    2016-09-09

    AFRL-AFOSR-JP-TR-2016-0080 Distributed Information Fusion through Advanced Multi-Agent Control Adrian Bishop NATIONAL ICT AUSTRALIA LIMITED Final...a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION. 1. REPORT DATE (DD-MM-YYYY)      17-10-2016 2. REPORT... Control 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA2386-14-1-4042 5c.  PROGRAM ELEMENT NUMBER 61102F 6. AUTHOR(S) Adrian Bishop 5d.  PROJECT NUMBER 5e

  19. Evolutionary multi-agent systems from inspirations to applications

    CERN Document Server

    Byrski, Aleksander

    2017-01-01

    This book addresses agent-based computing, concentrating in particular on evolutionary multi-agent systems (EMAS), which have been developed since 1996 at the AGH University of Science and Technology in Cracow, Poland. It provides the relevant background information on and a detailed description of this computing paradigm, along with key experimental results. Readers will benefit from the insightful discussion, which primarily concerns the efficient implementation of computing frameworks for developing EMAS and similar computing systems, as well as a detailed formal model. Theoretical deliberations demonstrating that computing with EMAS always helps to find the optimal solution are also included, rounding out the coverage.

  20. A Study of Applications of Multiagent System Specificaitons and the Key Techniques in Automatic Abstracts System

    Institute of Scientific and Technical Information of China (English)

    HUShun-geng; ZHONGYi-xin

    2001-01-01

    In this thesis, multiagent system specifications, multiagent system architectures, agent communica-tion languages and agent communication protocols, automatic abstracting based on multiagent technolo-gies are studied.Some concerned problems of de-signs and realization of automatic abstracting sys-tems based on multiagent technologies are strdied, too.Chapter 1 shows the significance and objectives of the thesis, its main contents are summarized, and innovations of the thesis are showed.Some basic concepts of agents and multiagent systems are stud-ied in Chapter2.The definitions of agents and mul-tiagent systems are given, and the theory, technolo-gies and applications of multiagent systems are sum-marized .Furthermore, some important studying trends of multiagent systems are set forward.Multi-agent system specifications are strdied in Chapter30MAS/KIB-a multiagent system specification is built using mental states such as K(Know), B(Be-lief), and I(Intention), its grammar and seman-teme are discussed, axioms and inference rules are given, and some properties are researched.We also compare MAS/KIB with other existing specifica-tions.MAS/KIB has the following characteristicsL1)each agent has its own world outlood;(2)no global data in the system;(3)processes of state changes are used as indexes to systems;(4)it has the characteristics of not only time series logic but also dynamic logic;and (5) interactive actions are included.The architectures of multiagent systems are studied in Chapter 4.First, we review some typical architecture of multiagent systems, agent network architecture, agent federated architecture, agent blackboard architenture ,and Foundation of Intelligent Physical Agent(FIPA) architecture.For the first time, we set forward and study the layering and partitioning models of the architectures of multi-agent systems,organizing architecture models, and interoperability architecture model of multiagent sys-tems .Chapter 5 studies agent communication lan

  1. Modeling hierarchical structures - Hierarchical Linear Modeling using MPlus

    OpenAIRE

    Jelonek, Magdalena

    2006-01-01

    The aim of this paper is to present the technique (and its linkage with physics) of overcoming problems connected to modeling social structures, which are typically hierarchical. Hierarchical Linear Models provide a conceptual and statistical mechanism for drawing conclusions regarding the influence of phenomena at different levels of analysis. In the social sciences it is used to analyze many problems such as educational, organizational or market dilemma. This paper introduces the logic of m...

  2. Hierarchical fringe tracking

    CERN Document Server

    Petrov, Romain G; Boskri, Abdelkarim; Folcher, Jean-Pierre; Lagarde, Stephane; Bresson, Yves; Benkhaldoum, Zouhair; Lazrek, Mohamed; Rakshit, Suvendu

    2014-01-01

    The limiting magnitude is a key issue for optical interferometry. Pairwise fringe trackers based on the integrated optics concepts used for example in GRAVITY seem limited to about K=10.5 with the 8m Unit Telescopes of the VLTI, and there is a general "common sense" statement that the efficiency of fringe tracking, and hence the sensitivity of optical interferometry, must decrease as the number of apertures increases, at least in the near infrared where we are still limited by detector readout noise. Here we present a Hierarchical Fringe Tracking (HFT) concept with sensitivity at least equal to this of a two apertures fringe trackers. HFT is based of the combination of the apertures in pairs, then in pairs of pairs then in pairs of groups. The key HFT module is a device that behaves like a spatial filter for two telescopes (2TSF) and transmits all or most of the flux of a cophased pair in a single mode beam. We give an example of such an achromatic 2TSF, based on very broadband dispersed fringes analyzed by g...

  3. Onboard hierarchical network

    Science.gov (United States)

    Tunesi, Luca; Armbruster, Philippe

    2004-02-01

    The objective of this paper is to demonstrate a suitable hierarchical networking solution to improve capabilities and performances of space systems, with significant recurrent costs saving and more efficient design & manufacturing flows. Classically, a satellite can be split in two functional sub-systems: the platform and the payload complement. The platform is in charge of providing power, attitude & orbit control and up/down-link services, whereas the payload represents the scientific and/or operational instruments/transponders and embodies the objectives of the mission. One major possibility to improve the performance of payloads, by limiting the data return to pertinent information, is to process data on board thanks to a proper implementation of the payload data system. In this way, it is possible to share non-recurring development costs by exploiting a system that can be adopted by the majority of space missions. It is believed that the Modular and Scalable Payload Data System, under development by ESA, provides a suitable solution to fulfil a large range of future mission requirements. The backbone of the system is the standardised high data rate SpaceWire network http://www.ecss.nl/. As complement, a lower speed command and control bus connecting peripherals is required. For instance, at instrument level, there is a need for a "local" low complexity bus, which gives the possibility to command and control sensors and actuators. Moreover, most of the connections at sub-system level are related to discrete signals management or simple telemetry acquisitions, which can easily and efficiently be handled by a local bus. An on-board hierarchical network can therefore be defined by interconnecting high-speed links and local buses. Additionally, it is worth stressing another important aspect of the design process: Agencies and ESA in particular are frequently confronted with a big consortium of geographically spread companies located in different countries, each one

  4. Hierarchical Reverberation Mapping

    CERN Document Server

    Brewer, Brendon J

    2013-01-01

    Reverberation mapping (RM) is an important technique in studies of active galactic nuclei (AGN). The key idea of RM is to measure the time lag $\\tau$ between variations in the continuum emission from the accretion disc and subsequent response of the broad line region (BLR). The measurement of $\\tau$ is typically used to estimate the physical size of the BLR and is combined with other measurements to estimate the black hole mass $M_{\\rm BH}$. A major difficulty with RM campaigns is the large amount of data needed to measure $\\tau$. Recently, Fine et al (2012) introduced a new approach to RM where the BLR light curve is sparsely sampled, but this is counteracted by observing a large sample of AGN, rather than a single system. The results are combined to infer properties of the sample of AGN. In this letter we implement this method using a hierarchical Bayesian model and contrast this with the results from the previous stacked cross-correlation technique. We find that our inferences are more precise and allow fo...

  5. Brahms An Agent-Oriented Language for Work Practice Simulation and Multi-Agent Systems Development

    Science.gov (United States)

    Sierhuis, Maarten; Clancey, William J.; van Hoof, Ron J. J.

    Brahms is a multi-agent modeling language for simulating human work practice that emerges from work processes in organizations. The same Brahms language can be used to implement and execute distributed multi-agent systems, based on models of work practice that were first simulated. Brahms demonstrates how a multi-agent belief-desire-intention language, symbolic cognitive modeling, traditional business process modeling, activity-and situated cognition theories are brought together in a coherent approach for analysis and design of organizations and human-centered systems.

  6. Ett Multi-Agent System som spelar brädspelet Risk

    OpenAIRE

    Olsson, Fredrik

    2005-01-01

    Risk is a game in which traditional Artificial-Intelligence methods such as for example iterative deepening and Alpha-Beta pruning can not successfully be applied due to the size of the search space. Distributed problem solving in the form of a multi-agent system might be the solution. This needs to be tested before it is possible to tell if a multi-agent system will be successful at playing Risk or not. In this thesis the development of a multi-agent system that plays Risk is explained. The ...

  7. An Interactive Tool for Creating Multi-Agent Systems and Interactive Agent-based Games

    DEFF Research Database (Denmark)

    Lund, Henrik Hautop; Pagliarini, Luigi

    2011-01-01

    Utilizing principles from parallel and distributed processing combined with inspiration from modular robotics, we developed the modular interactive tiles. As an educational tool, the modular interactive tiles facilitate the learning of multi-agent systems and interactive agent-based games....... The modular and physical property of the tiles provides students with hands-on experience in exploring the theoretical aspects underlying multi-agent systems which often appear as challenging to students. By changing the representation of the cognitive challenging aspects of multi-agent systems education...

  8. 多Agent信念修正研究%The Research of Multi-agent Belief Revision

    Institute of Scientific and Technical Information of China (English)

    孙召春; 高阳; 贾松茂; 陈世福

    2003-01-01

    Belief Revision is a theory that studies how to integrate new information into original belief set. Classical BR theory uses AGM frame, but it only resolves problems in single agent BR system. Multi-agent BR faces problems such as the collision of many information sources and how to maximize the logic consistence of multi-agent system. On the basis of game theory model, we form profit matrix under different BR strategies in multi-agent system and try to get the best strategy that satisfies logic consistence of the system through negotiation.

  9. Distributed Cooperative Control of Nonlinear and Non-identical Multi-agent Systems

    DEFF Research Database (Denmark)

    Bidram, Ali; Lewis, Frank; Davoudi, Ali

    2013-01-01

    to the synchronization problem for an identical linear multi-agent system. The controller for each agent is designed to be fully distributed, such that each agent only requires its own information and the information of its neighbors. The proposed control method is exploited to implement the secondary voltage control......This paper exploits input-output feedback linearization technique to implement distributed cooperative control of multi-agent systems with nonlinear and non-identical dynamics. Feedback linearization transforms the synchronization problem for a nonlinear and heterogeneous multi-agent system...... for electric power microgrids. The effectiveness of the proposed control is verified by simulating a microgrid test system....

  10. A multi-agent approach to the design of an e-health system.

    Science.gov (United States)

    Di Giacomo, Paola; Ricci, Fabrizio L

    2006-01-01

    E-medicine covers the whole range of medical process and service. Multi-agent approach is suitable for the development of e-medicine systems. In this paper, firstly the requirements of e-medicine are analyzed and taxonomy is proposed for e-medicine systems. Secondly multi-agent approach is introduced for developing e-medicine systems, and the design of agents and the design of multi-agent structure are presented for e-medicine systems. Finally a case study is presented on a telemedicine for diabetes to illustrate the development of e-medicine systems. Then, our future work is to implement the proposed system.

  11. Cooperative control of multi-agent systems a consensus region approach

    CERN Document Server

    Li, Zhongkui

    2014-01-01

    Distributed controller design is generally a challenging task, especially for multi-agent systems with complex dynamics, due to the interconnected effect of the agent dynamics, the interaction graph among agents, and the cooperative control laws. Cooperative Control of Multi-Agent Systems: A Consensus Region Approach offers a systematic framework for designing distributed controllers for multi-agent systems with general linear agent dynamics, linear agent dynamics with uncertainties, and Lipschitz nonlinear agent dynamics.Beginning with an introduction to cooperative control and graph theory,

  12. The Agent Modeling Language AML A Comprehensive Approach to Modeling Multi-agent Systems

    CERN Document Server

    Cervenka, Radovan

    2007-01-01

    Multi-agent systems are already a focus of studies for more than 25 years. Despite substantial effort of an active research community, modeling of multi-agent systems still lacks complete and proper definition, general acceptance, and practical application. Due to the vast potential of these systems e.g., to improve the practice in software and to extent the applications that can feasibly be tackled, this book tries to provide a comprehensive modeling language - the Agent Modeling Language (AML) - as an extension of UML 2.0, concentrating on multi-agent systems and applications.

  13. Discontinuous Observers Design for Finite-Time Consensus of Multiagent Systems With External Disturbances.

    Science.gov (United States)

    Liu, Xiaoyang; Ho, Daniel W C; Cao, Jinde; Xu, Wenying

    2016-08-24

    This brief investigates the problem of finite-time robust consensus (FTRC) for second-order nonlinear multiagent systems with external disturbances. Based on the global finite-time stability theory of discontinuous homogeneous systems, a novel finite-time convergent discontinuous disturbed observer (DDO) is proposed for the leader-following multiagent systems. The states of the designed DDO are then used to design the control inputs to achieve the FTRC of nonlinear multiagent systems in the presence of bounded disturbances. The simulation results are provided to validate the effectiveness of these theoretical results.

  14. Continuous Reinforced Concrete Beams

    DEFF Research Database (Denmark)

    Hoang, Cao Linh; Nielsen, Mogens Peter

    1996-01-01

    This report deals with stress and stiffness estimates of continuous reinforced concrete beams with different stiffnesses for negative and positive moments e.g. corresponding to different reinforcement areas in top and bottom. Such conditions are often met in practice.The moment distribution...

  15. Service orientation in holonic and multi-agent manufacturing

    CERN Document Server

    Thomas, André; Trentesaux, Damien

    2015-01-01

    This volume gathers the peer reviewed papers presented at the 4th edition of the International Workshop “Service Orientation in Holonic and Multi-agent Manufacturing – SOHOMA’14” organized and hosted on November 5-6, 2014 by the University of Lorraine, France in collaboration with the CIMR Research Centre of the University Politehnica of Bucharest and the TEMPO Laboratory of the University of Valenciennes and Hainaut-Cambrésis.   The book is structured in six parts, each one covering a specific research line which represents a trend in future manufacturing: (1) Holonic and Agent-based Industrial Automation Systems; (2) Service-oriented Management and Control of Manufacturing Systems; (3) Distributed Modelling for Safety and Security in Industrial Systems; (4) Complexity, Big Data and Virtualization in Computing-oriented Manufacturing; (5) Adaptive, Bio-inspired and Self-organizing Multi-Agent Systems for Manufacturing, and (6) Physical Internet Simulation, Modelling and Control.   There is a clear ...

  16. New Algorithm for FMS Scheduling Based on Multiagent System Architecture

    Institute of Scientific and Technical Information of China (English)

    Li Gaozheng; Huang Xiaoping; Ding Han

    2001-01-01

    Redefined benefit-driven function is used to study the dynamic scheduling of FMS based on multiagent architecture. Each agent is dedicated to a work center, i.e. a set of the manufacturing system. In one hand, each agent selects locally and dynamically the dispatching rule(DR) that seems to be most suited to the operating conditions, production objectives and current shop status. On the other hand, each task should bring certain amount of benefit for the manufacturer. So, it is reasonable to have the dynamic scheduling of FMS relying upon multiagent architecture using the benefit-driven function as a strategy. Well, today's manufacturing corporation, especially the high & new technology one and deep machining one, the cost of their products is mainly determined by how much the knowledge is input From this viewpoint, we redefined the benefit-driven function. In the end, this approach is compared with other existing DRs on a job-shop problem, already used in other research works.

  17. Vehicle-based interactive management with multi-agent approach

    Directory of Open Access Journals (Sweden)

    Yee Ming Chen

    2009-09-01

    Full Text Available Under the energy crisis and global warming, mass transportation becomes more important than before. The disadvantages of mass transportation, plus the high flexibility and efficiency of taxi and with the revolution of technology, electric-taxi is the better transportation choice for metropolis. On the other hand, among the many taxi service types, dial-a-ride (DAR service system is the better way for passenger and taxi. However the electricity replenishing of electric-taxi is the biggest shortage and constraint for DAR operation system. In order to more effectively manage the electric-taxi DAR operation system and the lots of disadvantages of physical system and observe the behaviors and interactions of simulation system, multi-agent simulation technique is the most suitable simulation technique. Finally, we use virtual data as the input of simulation system and analyze the simulation result. We successfully obtain two performance measures: average waiting time and service rate. Result shows the average waiting time is only 3.93 seconds and the service rate (total transport passenger number / total passenger number is 37.073%. So these two performance measures can support us to make management decisions. The multiagent oriented model put forward in this article is the subject of an application intended in the long term to supervise the user information system of an urban transport network.

  18. A theoretical model of multi-agent quantum computing

    Science.gov (United States)

    Mihelic, F. Matthew

    2011-05-01

    The best design for practical quantum computing is one that emulates the multi-agent quantum logic function of natural biological systems. Such systems are theorized to be based upon a quantum gate formed by a nucleic acid Szilard engine (NASE) that converts Shannon entropy of encountered molecules into useful work of nucleic acid geometric reconfiguration. This theoretical mechanism is logically and thermodynamically reversible in this special case because it is literally constructed out of the (nucleic acid) information necessary for its function, thereby allowing the nucleic acid Szilard engine to function reversibly because, since the information by which it functions exists on both sides of the theoretical mechanism simultaneously, there would be no build-up of information within the theoretical mechanism, and therefore no irreversible thermodynamic energy cost would be necessary to erase information inside the mechanism. This symmetry breaking Szilard engine function is associated with emission and/or absorption of entangled photons that can provide quantum synchronization of other nucleic acid segments within and between cells. In this manner nucleic acids can be considered as a natural model of topological quantum computing in which the nonabelian interaction of genes can be represented within quantum knot/braid theory as anyon crosses determined by entropic loss or gain that leads to changes in nucleic acid covalent bond angles. This naturally occurring biological form of topological quantum computing can serve as a model for workable man-made multi-agent quantum computing systems.

  19. Randomized Optimal Consensus of Multi-agent Systems

    CERN Document Server

    Shi, Guodong

    2011-01-01

    In this paper, we formulate and solve a randomized optimal consensus problem for multi-agent systems with stochastically time-varying interconnection topology. The considered multi-agent system with a simple randomized iterating rule achieves an almost sure consensus meanwhile solving the optimization problem $\\min_{z\\in \\mathds{R}^d}\\ \\sum_{i=1}^n f_i(z),$ in which the optimal solution set of objective function $f_i$ corresponding to agent $i$ can only be observed by agent $i$ itself. At each time step, each agent independently and randomly chooses either taking an average among its neighbor set, or projecting onto the optimal solution set of its own optimization component. Both directed and bidirectional communication graphs are studied. Connectivity conditions are proposed to guarantee an optimal consensus almost surely with proper convexity and intersection assumptions. The convergence analysis is carried out using convex analysis. The results illustrate that a group of autonomous agents can reach an opti...

  20. QUICR-learning for Multi-Agent Coordination

    Science.gov (United States)

    Agogino, Adrian K.; Tumer, Kagan

    2006-01-01

    Coordinating multiple agents that need to perform a sequence of actions to maximize a system level reward requires solving two distinct credit assignment problems. First, credit must be assigned for an action taken at time step t that results in a reward at time step t > t. Second, credit must be assigned for the contribution of agent i to the overall system performance. The first credit assignment problem is typically addressed with temporal difference methods such as Q-learning. The second credit assignment problem is typically addressed by creating custom reward functions. To address both credit assignment problems simultaneously, we propose the "Q Updates with Immediate Counterfactual Rewards-learning" (QUICR-learning) designed to improve both the convergence properties and performance of Q-learning in large multi-agent problems. QUICR-learning is based on previous work on single-time-step counterfactual rewards described by the collectives framework. Results on a traffic congestion problem shows that QUICR-learning is significantly better than a Q-learner using collectives-based (single-time-step counterfactual) rewards. In addition QUICR-learning provides significant gains over conventional and local Q-learning. Additional results on a multi-agent grid-world problem show that the improvements due to QUICR-learning are not domain specific and can provide up to a ten fold increase in performance over existing methods.

  1. Hierarchical materials: Background and perspectives

    DEFF Research Database (Denmark)

    2016-01-01

    Hierarchical design draws inspiration from analysis of biological materials and has opened new possibilities for enhancing performance and enabling new functionalities and extraordinary properties. With the development of nanotechnology, the necessary technological requirements for the manufactur...

  2. Hierarchical clustering for graph visualization

    CERN Document Server

    Clémençon, Stéphan; Rossi, Fabrice; Tran, Viet Chi

    2012-01-01

    This paper describes a graph visualization methodology based on hierarchical maximal modularity clustering, with interactive and significant coarsening and refining possibilities. An application of this method to HIV epidemic analysis in Cuba is outlined.

  3. Direct hierarchical assembly of nanoparticles

    Science.gov (United States)

    Xu, Ting; Zhao, Yue; Thorkelsson, Kari

    2014-07-22

    The present invention provides hierarchical assemblies of a block copolymer, a bifunctional linking compound and a nanoparticle. The block copolymers form one micro-domain and the nanoparticles another micro-domain.

  4. "Reinforcement" in behavior theory.

    Science.gov (United States)

    Schoenfeld, W N

    1978-01-01

    In its Pavlovian context, "reinforcement" was actually a descriptive term for the functional relation between an unconditional and a conditional stimulus. When it was adopted into operant conditioning, "reinforcement" became the central concept and the key operation, but with new qualifications, new referents, and new expectations. Some behavior theorists believed that "reinforcers" comprise a special and limited class of stimuli or events, and they speculated about what the essential "nature of reinforcement" might be. It is now known that any stimulus can serve a reinforcing function, with due recognition of such parameters as subject species characteristics, stimulus intensity, sensory modality, and schedule of application. This paper comments on these developments from the standpoint of reflex behavior theory.

  5. Functional annotation of hierarchical modularity.

    Directory of Open Access Journals (Sweden)

    Kanchana Padmanabhan

    Full Text Available In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function-hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology and the association of individual genes or proteins with these concepts (e.g., GO terms, our method will assign a Hierarchical Modularity Score (HMS to each node in the hierarchy of functional modules; the HMS score and its p-value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of "enriched" functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our

  6. Hierarchical architecture of active knits

    Science.gov (United States)

    Abel, Julianna; Luntz, Jonathan; Brei, Diann

    2013-12-01

    Nature eloquently utilizes hierarchical structures to form the world around us. Applying the hierarchical architecture paradigm to smart materials can provide a basis for a new genre of actuators which produce complex actuation motions. One promising example of cellular architecture—active knits—provides complex three-dimensional distributed actuation motions with expanded operational performance through a hierarchically organized structure. The hierarchical structure arranges a single fiber of active material, such as shape memory alloys (SMAs), into a cellular network of interlacing adjacent loops according to a knitting grid. This paper defines a four-level hierarchical classification of knit structures: the basic knit loop, knit patterns, grid patterns, and restructured grids. Each level of the hierarchy provides increased architectural complexity, resulting in expanded kinematic actuation motions of active knits. The range of kinematic actuation motions are displayed through experimental examples of different SMA active knits. The results from this paper illustrate and classify the ways in which each level of the hierarchical knit architecture leverages the performance of the base smart material to generate unique actuation motions, providing necessary insight to best exploit this new actuation paradigm.

  7. Agent交互层次模型%The Hierarchical Model on Agent Interaction

    Institute of Scientific and Technical Information of China (English)

    高波; 费奇; 陈学广

    2001-01-01

    The interaction problem is at the core position of researches on multi-agent systems. So the research on agent interaction mechanism is very important and fundamental. To this end ,the hierarchical model on agent interaction (HMAI) is proposed on the basis of studying the characteristics of agent interactive behaviors. There are four main layers in HMAI which contanis the layer of computer network protocol ,the layer of communication protocol ,the layer of interaction protocol and the layer of interactive strategy. The latter three layers are the emphases of this paper. Their concepts,theories and present status of research will be analyzed in detail. At the end of the paper ,some notes on comprehending HMAI and some work that should be carried on are discussed.

  8. Advanced hierarchical distance sampling

    Science.gov (United States)

    Royle, Andy

    2016-01-01

    In this chapter, we cover a number of important extensions of the basic hierarchical distance-sampling (HDS) framework from Chapter 8. First, we discuss the inclusion of “individual covariates,” such as group size, in the HDS model. This is important in many surveys where animals form natural groups that are the primary observation unit, with the size of the group expected to have some influence on detectability. We also discuss HDS integrated with time-removal and double-observer or capture-recapture sampling. These “combined protocols” can be formulated as HDS models with individual covariates, and thus they have a commonality with HDS models involving group structure (group size being just another individual covariate). We cover several varieties of open-population HDS models that accommodate population dynamics. On one end of the spectrum, we cover models that allow replicate distance sampling surveys within a year, which estimate abundance relative to availability and temporary emigration through time. We consider a robust design version of that model. We then consider models with explicit dynamics based on the Dail and Madsen (2011) model and the work of Sollmann et al. (2015). The final major theme of this chapter is relatively newly developed spatial distance sampling models that accommodate explicit models describing the spatial distribution of individuals known as Point Process models. We provide novel formulations of spatial DS and HDS models in this chapter, including implementations of those models in the unmarked package using a hack of the pcount function for N-mixture models.

  9. COLLISION AVOIDANCE DECISION- MAKING MODEL OF MULTI-AGENTS IN VIRTUAL DRIVING ENVIRONMENT WITH ANALYTIC HIERARCHY PROCESS

    Institute of Scientific and Technical Information of China (English)

    LU Hong; YI Guodong; TAN Jianrong; LIU Zhenyu

    2008-01-01

    Collision avoidance decision-making models of multiple agents in virtual driving environ- ment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making in real life driving, delphi approach and mathematical statistics method are introduced to construct pair-wise comparison judgment matrix of collision avoidance decision choices to each collision situation. Analytic hierarchy process (AHP) is adopted to establish the agents' collision avoidance decision-making model. To simulate drivers' characteristics, driver factors are added to categorize driving modes into impatient mode, normal mode, and the cautious mode. The results show that this model can simulate human's thinking process, and the agents in the virtual environment can deal with collision situations and make decisions to avoid collisions without intervention. The model can also reflect diversity and uncertainty of real life driving behaviors, and solves the multi-objective, multi-choice ranking priority problem in multi-vehicle collision scenarios. This collision avoidance model of multi-agents model is feasible and effective, and can provide richer and closer-to-life virtual scene for driving simulator, reflecting real-life traffic environment more truly, this model can also promote the practicality of driving simulator.

  10. 10th International Conference on Practical Applications of Agents and Multi-Agent Systems

    CERN Document Server

    Pérez, Javier; Golinska, Paulina; Giroux, Sylvain; Corchuelo, Rafael; Trends in Practical Applications of Agents and Multiagent Systems

    2012-01-01

    PAAMS, the International Conference on Practical Applications of Agents and Multi-Agent Systems is an evolution of the International Workshop on Practical Applications of Agents and Multi-Agent Systems. PAAMS is an international yearly tribune to present, to discuss, and to disseminate the latest developments and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to exchange their experience in the development of Agents and Multi-Agent Systems.   This volume presents the papers that have been accepted for the 2012 in the workshops: Workshop on Agents for Ambient Assisted Living, Workshop on Agent-Based Solutions for Manufacturing and Supply Chain and Workshop on Agents and Multi-agent systems for Enterprise Integration.

  11. Multi-agents modelling of EV purchase willingness based on questionaires

    DEFF Research Database (Denmark)

    Xue, Yusheng; Wu, Juai; Xie, Dongliang

    2015-01-01

    , multi-layer correlation information is extracted from a limited number of questionnaires. Multiagents mimicking the inquired potential customers are modelled through matching the probabilistic distributions of their willingness embedded in the questionnaires. The authenticity of both the model...

  12. Collaboration Control of Fractional-Order Multiagent Systems with Sampling Delay

    Directory of Open Access Journals (Sweden)

    Hong-yong Yang

    2013-01-01

    Full Text Available Because of the complexity of the practical environments, many distributed multiagent systems cannot be illustrated with the integer-order dynamics and can only be described with the fractional-order dynamics. In this paper, collaboration control problems of continuous-time networked fractional-order multiagent systems via sampled control and sampling delay are investigated. Firstly, the sampled-data control of multiagent systems with fractional-order derivative operator is analyzed in a directed weighted network ignoring sampling delay. Then, the collaborative control of fractional-order multiagent systems with sampled data and sampling delay is studied in a directed and symmetrical network. Many sufficient conditions for reaching consensus with sampled data and sampling delay are obtained. Some numerical simulations are presented to illustrate the utility of our theoretical results.

  13. PERILAKU PROSOSIAL (PROSOCIAL BEHAVIOR ANAK USIA DINI DAN PENGELOLAAN KELAS MELALUI PENGELOMPOKAN USIA RANGKAP (MULTIAGE GROUPING

    Directory of Open Access Journals (Sweden)

    Elvrida Sandra Matondang

    2017-02-01

    Full Text Available Abstract: The aspect of moral development is of great concern of early childhood caregivers. Moral development, which is now better known as prosocial behaviors include behaviors such as empathy, generosity, cooperation, caring, and many more. Various attempts to build prosocial behavior has been carried out in kindergarten, including in one of international preschools  in Bandung that management class is using the multiage grouping.  According to this phenomenon which needed to be achieved, such as the form of prosocial behavior of the child at the multiage grouping, factors that affect the incidence of prosocial behavior in multiage grouping, teachers intervention to any problems relate to prosocial behavior in the multiage grouping, the efforts of teachers to develop prosocial behavior in multiage grouping, the efforts of teachers to manage classes with the concept of multiage grouping. The purpose of doing this research on the grounds of how the management class that uses multiage grouping can increase prosocial behavior of children between the age range of 3-6 years.  The method used in this study is a qualitative approach using case studies, data collection is done by observation, interview and documentation. The findings of this study represent children’s prosocial behavior in the form of cooperative behavior, friendship, helping, sharing, and caring. Children prosocial behavior should practically continually place in their environment and if the foundation is strong enough, they will easily adjust to school environment, especially in a school where the class management is using multiage grouping. Keywords: Early Childhood, Multiage Grouping, Pro-social Behavior   Abstrak: Aspek perkembangan moral adalah perhatian besar dari pengasuh anak usia dini. perkembangan moral, yang sekarang lebih dikenal sebagai perilaku prososial mencakup perilaku seperti empati, kedermawanan, kerjasama, peduli, dan banyak lagi. Berbagai upaya untuk

  14. Multi-agent search for source localization in a turbulent medium

    Science.gov (United States)

    Hajieghrary, Hadi; Hsieh, M. Ani; Schwartz, Ira B.

    2016-04-01

    We extend the gradient-less search strategy referred to as "infotaxis" to a distributed multi-agent system. "Infotaxis" is a search strategy that uses sporadic sensor measurements to determine the source location of materials dispersed in a turbulent medium. In this work, we leverage the spatio-temporal sensing capabilities of a mobile sensing agents to optimize the time spent finding and localizing the position of the source using a multi-agent collaborative search strategy. Our results suggest that the proposed multi-agent collaborative search strategy leverages the team's ability to obtain simultaneous measurements at different locations to speed up the search process. We present a multi-agent collaborative "infotaxis" strategy that uses the relative entropy of the system to synthesize a suitable search strategy for the team. The result is a collaborative information theoretic search strategy that results in control actions that maximize the information gained by the team, and improves estimates of the source position.

  15. The Communicative Multiagent Team Decision Problem: Analyzing Teamwork Theories and Models

    CERN Document Server

    Pynadath, D V; 10.1613/jair.1024

    2011-01-01

    Despite the significant progress in multiagent teamwork, existing research does not address the optimality of its prescriptions nor the complexity of the teamwork problem. Without a characterization of the optimality-complexity tradeoffs, it is impossible to determine whether the assumptions and approximations made by a particular theory gain enough efficiency to justify the losses in overall performance. To provide a tool for use by multiagent researchers in evaluating this tradeoff, we present a unified framework, the COMmunicative Multiagent Team Decision Problem (COM-MTDP). The COM-MTDP model combines and extends existing multiagent theories, such as decentralized partially observable Markov decision processes and economic team theory. In addition to their generality of representation, COM-MTDPs also support the analysis of both the optimality of team performance and the computational complexity of the agents' decision problem. In analyzing complexity, we present a breakdown of the computational complexit...

  16. Multi-Agent Based Agile (XP) Software Development Process Scheduling Model

    National Research Council Canada - National Science Library

    Y M Malgwi; N V Blamah

    2015-01-01

    .... In such changing environment agile development methodology is suited. In this paper, a multi-agent based approach to process scheduling was adopted, where each activity is viewed as an autonomous and flexible agent process...

  17. A comparative study of marketing channel multiagent Stackelberg model based on perfect rationality and fairness preference

    National Research Council Canada - National Science Library

    Wang, Kaihong; Yang, Xu; Sun, Yiwan; Ding, Chuan

    2014-01-01

    ... through multiple retailers; a number of retailers work as sales agents of manufacturers' products, so in this paper we define this channel structure as multiagent; scholars had done substantial...

  18. Fault-Tolerant Consensus of Multi-Agent System With Distributed Adaptive Protocol.

    Science.gov (United States)

    Chen, Shun; Ho, Daniel W C; Li, Lulu; Liu, Ming

    2015-10-01

    In this paper, fault-tolerant consensus in multi-agent system using distributed adaptive protocol is investigated. Firstly, distributed adaptive online updating strategies for some parameters are proposed based on local information of the network structure. Then, under the online updating parameters, a distributed adaptive protocol is developed to compensate the fault effects and the uncertainty effects in the leaderless multi-agent system. Based on the local state information of neighboring agents, a distributed updating protocol gain is developed which leads to a fully distributed continuous adaptive fault-tolerant consensus protocol design for the leaderless multi-agent system. Furthermore, a distributed fault-tolerant leader-follower consensus protocol for multi-agent system is constructed by the proposed adaptive method. Finally, a simulation example is given to illustrate the effectiveness of the theoretical analysis.

  19. Velocity synchronization of multi-agent systems with mismatched parameters via sampled position data.

    Science.gov (United States)

    Sun, Wen; Huang, Chunli; Lü, Jinhu; Li, Xiong; Chen, Shihua

    2016-02-01

    Power systems are special multi-agent systems with nonlinear coupling function and symmetric structures. This paper extends these systems to a class of multi-agent systems with mismatched parameters, linear coupling function, and asymmetric structures and investigates their velocity synchronization via sampled position data. The dynamics of the agents is adopted as that of generators with mismatched parameters, while the system structures are supposed to be complex. Two distributed linear consensus protocols are designed, respectively, for multi-agent systems without or with communication delay. Necessary and sufficient conditions based on the sampling period, the mismatched parameters, the delay, and the nonzero eigenvalues of the Laplacian matrix are established. It is shown that velocity synchronization of multi-agent systems with mismatched parameters can be achieved if the sampled period is chosen appropriately. Simulations are given to illustrate the effectiveness of the theoretical results.

  20. Tableau-based decision procedures for logics of strategic ability in multi-agent systems

    CERN Document Server

    Goranko, Valentin

    2008-01-01

    We develop decision procedures based on sound, complete, and terminating incremental tableaux for the satisfiability problem of the Alternating-time temporal logic ATL and related modal logics for reasoning about abilities of agents in multiagent systems.

  1. 14th International Conference on Practical Applications of Agents and Multi-Agent Systems : Special Sessions

    CERN Document Server

    Escalona, María; Corchuelo, Rafael; Mathieu, Philippe; Vale, Zita; Campbell, Andrew; Rossi, Silvia; Adam, Emmanuel; Jiménez-López, María; Navarro, Elena; Moreno, María

    2016-01-01

    PAAMS, the International Conference on Practical Applications of Agents and Multi-Agent Systems is an evolution of the International Workshop on Practical Applications of Agents and Multi-Agent Systems. PAAMS is an international yearly tribune to present, to discuss, and to disseminate the latest developments and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to exchange their experience in the development of Agents and Multi-Agent Systems. This volume presents the papers that have been accepted for the 2016 in the special sessions: Agents Behaviours and Artificial Markets (ABAM); Advances on Demand Response and Renewable Energy Sources in Agent Based Smart Grids (ADRESS); Agents and Mobile Devices (AM); Agent Methodologies for Intelligent Robotics Applications (AMIRA); Learning, Agents and Formal Languages (LAFLang); Multi-Agent Systems and Ambient Intelligence (MASMAI); Web Mining and ...

  2. Leader-Following Consensus for Linear and Lipschitz Nonlinear Multiagent Systems With Quantized Communication.

    Science.gov (United States)

    Zhang, Zhiqiang; Zhang, Lin; Hao, Fei; Wang, Long

    2016-06-21

    This paper studies the leader-following consensus problem for linear and Lipschitz nonlinear multiagent systems where the communication topology has a directed spanning tree with the leader as the root. Due to the constraints of communication bandwidth and storage space, agents can only receive uniform quantized information. We first consider the leader-following consensus problem for linear multiagent systems via quantized control. Then, in order to reduce the communication load, an event-triggered control strategy is investigated to solve the consensus problem for linear multiagent systems with uniform quantization. It is shown that leader-following practical consensus can be achieved and no Zeno behavior occurs in this case. Furthermore, the proposed control strategies are extended to investigate the leader-following consensus problem for multiagent systems with Lipschitz nonlinear dynamics. Simulation results are given to demonstrate the feasibility and effectiveness of the theoretical analysis.

  3. Modeling and Simulation of Complex Network Attributes on Coordinating Large Multiagent System

    Science.gov (United States)

    Li, Xiang; Liu, Ming

    2014-01-01

    With the expansion of distributed multiagent systems, traditional coordination strategy becomes a severe bottleneck when the system scales up to hundreds of agents. The key challenge is that in typical large multiagent systems, sparsely distributed agents can only communicate directly with very few others and the network is typically modeled as an adaptive complex network. In this paper, we present simulation testbed CoordSim built to model the coordination of network centric multiagent systems. Based on the token-based strategy, the coordination can be built as a communication decision problem that agents make decisions to target communications and pass them over to the capable agents who will potentially benefit the team most. We have theoretically analyzed that the characters of complex network make a significant difference with both random and intelligent coordination strategies, which may contribute to future multiagent algorithm design. PMID:24955399

  4. Sampled-Data-Based Consensus and $L_{2}$ -Gain Analysis for Heterogeneous Multiagent Systems.

    Science.gov (United States)

    Du, Sheng-Li; Xia, Weiguo; Sun, Xi-Ming; Wang, Wei

    2017-06-01

    This paper is concerned with the sampled-data-based consensus problem of heterogeneous multiagent systems under directed graph topology with communication failure. The heterogeneous multiagent system consists of first-order and second-order integrators. Consensus of the heterogeneous multiagent system may not be guaranteed if the communication failure always happens. However, if the frequency and the length of the communication failure satisfy certain conditions, consensus of the considered system can be reached. In particular, we introduce the concepts of communication failure frequency and communication failure length. Then, with the help of the switching technique and the Lyapunov stability theory, sufficient conditions are derived in terms of linear matrix inequalities, which guarantees that the heterogeneous multiagent system not only achieves consensus but also maintains a desired L2 -gain performance. A simulation example is given to show the effectiveness of the proposed method in this paper.

  5. Cooperative control of multi-agent systems optimal and adaptive design approaches

    CERN Document Server

    Lewis, Frank L; Hengster-Movric, Kristian; Das, Abhijit

    2014-01-01

    Task complexity, communication constraints, flexibility and energy-saving concerns are all factors that may require a group of autonomous agents to work together in a cooperative manner. Applications involving such complications include mobile robots, wireless sensor networks, unmanned aerial vehicles (UAVs), spacecraft, and so on. In such networked multi-agent scenarios, the restrictions imposed by the communication graph topology can pose severe problems in the design of cooperative feedback control systems.  Cooperative control of multi-agent systems is a challenging topic for both control theorists and practitioners and has been the subject of significant recent research. Cooperative Control of Multi-Agent Systems extends optimal control and adaptive control design methods to multi-agent systems on communication graphs.  It develops Riccati design techniques for general linear dynamics for cooperative state feedback design, cooperative observer design, and cooperative dynamic output feedback design.  B...

  6. Towards a multi-agent system for regulated information exchange in crime investigations

    NARCIS (Netherlands)

    Dijkstra, Pieter; Prakken, H.; Vey Mestdagh, C.N.J. de

    2005-01-01

    This paper outlines a multi-agent architecture for regulated information exchange of crime investigation data between police forces. Interactions between police officers about information exchange are analysed as negotiation dialogues with embedded persuasion dialogues. An architecture is then propo

  7. A theoretical framework for negotiating the path of emergency management multi-agency coordination.

    Science.gov (United States)

    Curnin, Steven; Owen, Christine; Paton, Douglas; Brooks, Benjamin

    2015-03-01

    Multi-agency coordination represents a significant challenge in emergency management. The need for liaison officers working in strategic level emergency operations centres to play organizational boundary spanning roles within multi-agency coordination arrangements that are enacted in complex and dynamic emergency response scenarios creates significant research and practical challenges. The aim of the paper is to address a gap in the literature regarding the concept of multi-agency coordination from a human-environment interaction perspective. We present a theoretical framework for facilitating multi-agency coordination in emergency management that is grounded in human factors and ergonomics using the methodology of core-task analysis. As a result we believe the framework will enable liaison officers to cope more efficiently within the work domain. In addition, we provide suggestions for extending the theory of core-task analysis to an alternate high reliability environment.

  8. Continuous Reinforced Concrete Beams

    DEFF Research Database (Denmark)

    Hoang, Cao Linh; Nielsen, Mogens Peter

    1996-01-01

    This report deals with stress and stiffness estimates of continuous reinforced concrete beams with different stiffnesses for negative and positive moments e.g. corresponding to different reinforcement areas in top and bottom. Such conditions are often met in practice.The moment distribution...... at the limit state of serviceability is in some simple cases determined by setting up the statical and the compatibility conditions.With these moment distributions, the maximum deflection and the reinforcement stresses at the span middle and at a support are calculated.The results are compared with results...

  9. Algorithms for Reinforcement Learning

    CERN Document Server

    Szepesvari, Csaba

    2010-01-01

    Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms'

  10. Reinforcing the mineral layer

    Energy Technology Data Exchange (ETDEWEB)

    Pishchulin, V.V.; Kuntsevich, V.I.; Seryy, A.M.; Shirokov, A.P.

    1980-05-15

    A way of reinforcing the mineral layer includes drilling holes and putting in anchors that are longer than the width of the layer strip being extracted. It also includes shortening the anchors as the strip is mined and reinforcing the remaining part of the anchor in the mouth of the hole. To increase the productivity and safety of the work, the anchors are shortened by cutting them as the strip is mined and are reinforced through wedging. The device for doing this has auxilliary lengthwise grooves in the shaft located along its length at an interval equal to the width of the band being extracted.

  11. A meta-ontological framework for multi-agent systems design

    OpenAIRE

    Sokolova, Marina; Fernández Caballero, Antonio

    2007-01-01

    The paper introduces an approach to using a meta-ontology framework for complex multi-agent systems design, and illustrates it in an application related to ecological-medical issues. The described shared ontology is pooled from private sub-ontologies, which represent a problem area ontology, an agent ontology, a task ontology, an ontology of interactions, and the multi-agent system architecture ontology.

  12. A meta-ontological framework for multi-agent systems design

    OpenAIRE

    Sokolova, Marina; Fernández Caballero, Antonio

    2007-01-01

    The paper introduces an approach to using a meta-ontology framework for complex multi-agent systems design, and illustrates it in an application related to ecological-medical issues. The described shared ontology is pooled from private sub-ontologies, which represent a problem area ontology, an agent ontology, a task ontology, an ontology of interactions, and the multi-agent system architecture ontology.

  13. Supply Chain Management System Model of Virtual Enterprises Based on Multi-Agent

    Institute of Scientific and Technical Information of China (English)

    LI Zhen; ZHANG Pei-pei

    2008-01-01

    Based on the analysis of a virtual enterprise and the development of supply chain management, their integration is proposed. Then, the difference between multi-agent system modeling method and the traditional modeling method is analyzed, and a method based on Java agent framework for multi-agent systems(JAFMAS) is proposed. By using this method the virtual enterprise's supply chain management system model is established.

  14. Group Behavior Learning in Multi-Agent Systems Based on Social Interaction Among Agents

    OpenAIRE

    Zhang, Kun; Maeda, Yoichiro; Takahashi, Yasutake

    2011-01-01

    Research on multi-agent systems, in which autonomous agents are able to learn cooperative behavior, has been the subject of rising expectations in recent years. We have aimed at the group behavior generation of the multi-agents who have high levelsof autonomous learning ability, like that of human beings, through social interaction between agents to acquire cooperative behavior. The sharing of environmentstates can improve cooperative ability, andthe changing state of the environment in the i...

  15. Knowledge based support for real time application of multiagent control and automation in electric power systems

    DEFF Research Database (Denmark)

    Saleem, Arshad; Nordstrom, Lars; Lind, Morten

    2011-01-01

    This paper presents a mechanism for developing knowledge based support for real time application of multiagent systems (MAS) in control, automation and diagnosis of electric power systems. In particular it presents a way for autonomous agents to utilize a qualitative means-ends based model...... and choose an appropriate control action. The paper also elaborates on real time interfacing between multi-agent systems and industry standard distribution automation and control system....

  16. Robust Fault Diagnosis Design for Linear Multiagent Systems with Incipient Faults

    Directory of Open Access Journals (Sweden)

    Jingping Xia

    2015-01-01

    Full Text Available The design of a robust fault estimation observer is studied for linear multiagent systems subject to incipient faults. By considering the fact that incipient faults are in low-frequency domain, the fault estimation of such faults is proposed for discrete-time multiagent systems based on finite-frequency technique. Moreover, using the decomposition design, an equivalent conclusion is given. Simulation results of a numerical example are presented to demonstrate the effectiveness of the proposed techniques.

  17. A Study of an Intelligent Battlefield Damage Assessment System Based on a Multi-agent System

    Institute of Scientific and Technical Information of China (English)

    LIU Xiang-kai; DAI Wan-jun; TANG Yan-feng; WANG Jia-ning

    2008-01-01

    Battlefield damage assessment is the key to Battlefield Damage Assessment and Repair (BDAR).We present an Intelligent Battlefield Damage Assessment System (IBDAS) based on multi-agent system technology. We first establish the system framework, and then study the interior structure and workflow of a problem allocation agent. The result shows that, there are many advantages to resolve the problem of battlefield damage assessment by applying multi-agent system technology, and it will bring significant military benefit.

  18. Dynamical Consensus Algorithm for Second-Order Multi-Agent Systems Subjected to Communication Delay

    Institute of Scientific and Technical Information of China (English)

    LIU Cheng-Lin; LIU Fei

    2013-01-01

    To solve the dynamical consensus problem of second-order multi-agent systems with communication delay,delay-dependent compensations are added into the normal asynchronously-coupled consensus algorithm so as to make the agents achieve a dynamical consensus.Based on frequency-domain analysis,sufficient conditions are gained for second-order multi-agent systems with communication delay under leaderless and leader-following consensus algorithms respectively.Simulation illustrates the correctness of the results.

  19. Distributed Optimization Design of Continuous-Time Multiagent Systems With Unknown-Frequency Disturbances.

    Science.gov (United States)

    Wang, Xinghu; Hong, Yiguang; Yi, Peng; Ji, Haibo; Kang, Yu

    2017-05-24

    In this paper, a distributed optimization problem is studied for continuous-time multiagent systems with unknown-frequency disturbances. A distributed gradient-based control is proposed for the agents to achieve the optimal consensus with estimating unknown frequencies and rejecting the bounded disturbance in the semi-global sense. Based on convex optimization analysis and adaptive internal model approach, the exact optimization solution can be obtained for the multiagent system disturbed by exogenous disturbances with uncertain parameters.

  20. Adaptive Control and Multi-agent Interface for Infotelecommunication Systems of New Generation

    OpenAIRE

    Timofeev, Adil

    2004-01-01

    Problems for intellectualisation for man-machine interface and methods of self-organization for network control in multi-agent infotelecommunication systems have been discussed. Architecture and principles for construction of network and neural agents for telecommunication systems of new generation have been suggested. Methods for adaptive and multi-agent routing for information flows by requests of external agents- users of global telecommunication systems and computer network...

  1. Hierarchical topic modeling with nested hierarchical Dirichlet process

    Institute of Scientific and Technical Information of China (English)

    Yi-qun DING; Shan-ping LI; Zhen ZHANG; Bin SHEN

    2009-01-01

    This paper deals with the statistical modeling of latent topic hierarchies in text corpora. The height of the topic tree is assumed as fixed, while the number of topics on each level as unknown a priori and to be inferred from data. Taking a nonparametric Bayesian approach to this problem, we propose a new probabilistic generative model based on the nested hierarchical Dirichlet process (nHDP) and present a Markov chain Monte Carlo sampling algorithm for the inference of the topic tree structure as welt as the word distribution of each topic and topic distribution of each document. Our theoretical analysis and experiment results show that this model can produce a more compact hierarchical topic structure and captures more free-grained topic relationships compared to the hierarchical latent Dirichlet allocation model.

  2. Highlights on Practical Applications of Agents and Multi-Agent Systems 10th International Conference on Practical Applications of Agents and Multi-Agent Systems

    CERN Document Server

    Sánchez, Miguel; Mathieu, Philippe; Rodríguez, Juan; Adam, Emmanuel; Ortega, Alfonso; Moreno, María; Navarro, Elena; Hirsch, Benjamin; Lopes-Cardoso, Henrique; Julián, Vicente

    2012-01-01

    Research on Agents and Multi-Agent Systems has matured during the last decade and many effective applications of this technology are now deployed. PAAMS provides an international forum to present and discuss the latest scientific developments and their effective applications, to assess the impact of the approach, and to facilitate technology transfer. PAAMS started as a local initiative, but has since grown to become THE international yearly platform to present, to discuss, and to disseminate the latest developments and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to exchange their experience in the development and deployment of Agents and Multi-Agent Systems. PAAMS intends to bring together researchers and developers from industry and the academic world to report on the latest scientific and technical advances on the application of multi-agent systems, to discuss and debate the major ...

  3. Advances on Practical Applications of Agents and Multi-Agent Systems 10th International Conference on Practical Applications of Agents and Multi-Agent Systems

    CERN Document Server

    Müller, Jörg; Rodríguez, Juan; Pérez, Javier

    2012-01-01

    Research on Agents and Multi-Agent Systems has matured during the last decade and many effective applications of this technology are now deployed. PAAMS provides an international forum to present and discuss the latest scientific developments and their effective applications, to assess the impact of the approach, and to facilitate technology transfer. PAAMS started as a local initiative, but has since grown to become THE international yearly platform to present, to discuss, and to disseminate the latest developments and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to exchange their experience in the development and deployment of Agents and Multi-Agent Systems. PAAMS intends to bring together researchers and developers from industry and the academic world to report on the latest scientific and technical advances on the application of multi-agent systems, to discuss and debate the major ...

  4. EXPERT DISCOVERY AND KNOWLEDGE MINING IN COMPLEX MULTI-AGENT SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    Minjie ZHANG; Xijin TANG; Quan BAI; Jifa GU

    2007-01-01

    Complex problem solving requires diverse expertise and multiple techniques. In order to solve such problems, complex multi-agent systems that include both of human experts and autonomous agents are required in many application domains. Most complex multi-agent systems work in open domains and include various heterogeneous agents. Due to the heterogeneity of agents and dynamic features of working environments, expertise and capabilities of agents might not be well estimated and presented in these systems. Therefore, how to discover useful knowledge from human and autonomous experts,make more accurate estimation for experts' capabilities and find out suitable expert(s) to solve incoming problems ("Expert Mining") are important research issues in the area of multi-agent system.In this paper, we introduce an ontology-based approach for knowledge and expert mining in hybrid multi-agent systems. In this research, ontologies are hired to describe knowledge of the system.Knowledge and expert mining processes are executed as the system handles incoming problems. In this approach, we embed more self-learning and self-adjusting abilities in multi-agent systems, so as to help in discovering knowledge of heterogeneous experts of multi-agent systems.

  5. Discovering the influences of complex network effects on recovering large scale multiagent systems.

    Science.gov (United States)

    Xu, Yang; Liu, Pengfei; Li, Xiang; Ren, Wei

    2014-01-01

    Building efficient distributed coordination algorithms is critical for the large scale multiagent system design, and the communication network has been shown as a key factor to influence system performance even under the same coordination protocol. Although many distributed algorithm designs have been proved to be feasible to build their functions in the large scale multiagent systems as claimed, the performances may not be stable if the multiagent networks were organized with different complex network topologies. For example, if the network was recovered from the broken links or disfunction nodes, the network topology might have been shifted. Therefore, their influences on the overall multiagent system performance are unknown. In this paper, we have made an initial effort to find how a standard network recovery policy, MPLS algorithm, may change the network topology of the multiagent system in terms of network congestion. We have established that when the multiagent system is organized as different network topologies according to different complex network attributes, the network shifts in different ways. Those interesting discoveries are helpful to predict how complex network attributes influence on system performance and in turn are useful for new algorithm designs that make a good use of those attributes.

  6. Fiber-reinforced ceramics

    Energy Technology Data Exchange (ETDEWEB)

    Belcheva, D. [Technological University `Prof. A. Zlatarov`, Bourgas (Bulgaria); Lubchev, L.; Jelezkov, G.; Georgiev, W.

    1995-03-01

    The possibilities for preparation of reinforced composite materials were studied. Test specimens based on different types of alumina matrices, plasticized with formaldehyde oligomer and polyvinyl alcohol, and reinforced with carbon and mullite fibers were prepared and investigated. The results confirmed that reinforced composite materials with valuable properties such as high thermal shock resistance, chemical resistance and mechanical strength can be produced. The density of technical alumina materials is lower, compared with that of pure alumina. The density can also be influenced by the type and quantity of the plasticizers used. By increasing the fiber content, the density of the material decreases. The shrinkage is influcenced by the type and the quantity of the reinforcing material. (orig.)

  7. Relativized hierarchical decomposition of Markov decision processes.

    Science.gov (United States)

    Ravindran, B

    2013-01-01

    Reinforcement Learning (RL) is a popular paradigm for sequential decision making under uncertainty. A typical RL algorithm operates with only limited knowledge of the environment and with limited feedback on the quality of the decisions. To operate effectively in complex environments, learning agents require the ability to form useful abstractions, that is, the ability to selectively ignore irrelevant details. It is difficult to derive a single representation that is useful for a large problem setting. In this chapter, we describe a hierarchical RL framework that incorporates an algebraic framework for modeling task-specific abstraction. The basic notion that we will explore is that of a homomorphism of a Markov Decision Process (MDP). We mention various extensions of the basic MDP homomorphism framework in order to accommodate different commonly understood notions of abstraction, namely, aspects of selective attention. Parts of the work described in this chapter have been reported earlier in several papers (Narayanmurthy and Ravindran, 2007, 2008; Ravindran and Barto, 2002, 2003a,b; Ravindran et al., 2007).

  8. Reinforcement Lernen mit Regularisierungsnetzwerken

    OpenAIRE

    Jung, Tobias

    2007-01-01

    Die Arbeit behandelt das Problem der Skalierbarkeit von Reinforcement Lernen auf hochdimensionale und komplexe Aufgabenstellungen. Unter Reinforcement Lernen versteht man dabei eine auf approximativem Dynamischen Programmieren basierende Klasse von Lernverfahren, die speziell Anwendung in der Künstlichen Intelligenz findet und zur autonomen Steuerung simulierter Agenten oder realer Hardwareroboter in dynamischen und unwägbaren Umwelten genutzt werden kann. Dazu wird mittels Regression aus Sti...

  9. Reinforcement learning in scheduling

    Science.gov (United States)

    Dietterich, Tom G.; Ok, Dokyeong; Zhang, Wei; Tadepalli, Prasad

    1994-01-01

    The goal of this research is to apply reinforcement learning methods to real-world problems like scheduling. In this preliminary paper, we show that learning to solve scheduling problems such as the Space Shuttle Payload Processing and the Automatic Guided Vehicle (AGV) scheduling can be usefully studied in the reinforcement learning framework. We discuss some of the special challenges posed by the scheduling domain to these methods and propose some possible solutions we plan to implement.

  10. A Nonlinear Consensus Protocol of Multiagent Systems Considering Measuring Errors

    Directory of Open Access Journals (Sweden)

    Xiaochu Wang

    2013-01-01

    Full Text Available In order to avoid a potential waste of energy during consensus controls in the case where there exist measurement uncertainties, a nonlinear protocol is proposed for multiagent systems under a fixed connected undirected communication topology and extended to both the cases with full and partial access a reference. Distributed estimators are utilized to help all agents agree on the understandings of the reference, even though there may be some agents which cannot access to the reference directly. An additional condition is also considered, where self-known configuration offsets are desired. Theoretical analyses of stability are given. Finally, simulations are performed, and results show that the proposed protocols can lead agents to achieve loose consensus and work effectively with less energy cost to keep the formation, which have illustrated the theoretical results.

  11. Cooperative Output Regulation of Multiagent Linear Parameter-Varying Systems

    Directory of Open Access Journals (Sweden)

    Afshin Mesbahi

    2017-01-01

    Full Text Available The output regulation problem is examined in this paper for a class of heterogeneous multiagent systems whose dynamics are governed by polytopic linear parameter-varying (LPV models. The dynamics of the agents are decoupled from each other but the agents’ controllers are assumed to communicate. To design the cooperative LPV controllers, analysis conditions for closed-loop system are first established to ensure stability and reference tracking. Then, the LPV control synthesis problem is addressed, where the offline solution to a time-varying Sylvester equation will be used to determine and update in real time the controller state-space matrices. Two numerical examples will be finally given to demonstrate the efficacy of the proposed cooperative design method.

  12. Multi-agent simulation of generation expansion in electricity markets.

    Energy Technology Data Exchange (ETDEWEB)

    Botterud, A; Mahalik, M. R.; Veselka, T. D.; Ryu, H.-S.; Sohn, K.-W.; Decision and Information Sciences; Korea Power Exchange

    2007-06-01

    We present a new multi-agent model of generation expansion in electricity markets. The model simulates generation investment decisions of decentralized generating companies (GenCos) interacting in a complex, multidimensional environment. A probabilistic dispatch algorithm calculates prices and profits for new candidate units in different future states of the system. Uncertainties in future load, hydropower conditions, and competitors actions are represented in a scenario tree, and decision analysis is used to identify the optimal expansion decision for each individual GenCo. We test the model using real data for the Korea power system under different assumptions about market design, market concentration, and GenCo's assumed expectations about their competitors investment decisions.

  13. Multi-Agent simulation of generation capacity expansion decisions.

    Energy Technology Data Exchange (ETDEWEB)

    Botterud, A.; Mahalik, M.; Conzelmann, G.; Silva, R.; Vilela, S.; Pereira, R. (Decision and Information Sciences); (Energias de Portugal); (Rede Electrica Nacional)

    2008-01-01

    In this paper, we use a multi-agent simulation model, EMCAS, to analyze generation expansion in the Iberian electricity market. The expansion model simulates generation investment decisions of decentralized generating companies (GenCos) interacting in a complex, multidimensional environment. A probabilistic dispatch algorithm calculates prices and profits for new candidate units in different future states of the system. Uncertainties in future load, hydropower conditions, and competitorspsila actions are represented in a scenario tree, and decision analysis is used to identify the optimal expansion decision for each individual GenCo. We run the model using detailed data for the Iberian market. In a scenario analysis, we look at the impact of market design variables, such as the energy price cap and carbon emission prices. We also analyze how market concentration and GenCospsila risk preferences influence the timing and choice of new generating capacity.

  14. Multi-agent immune recognition of water mine model

    Institute of Scientific and Technical Information of China (English)

    LIU Hai-bo; GU Guo-chang; SHEN Jing; FU Yan

    2005-01-01

    It is necessary for mine countermeasure systems to recognise the model of a water mine before destroying because the destroying measures to be taken must be determined according to mine model. In this paper, an immune neural network (INN) along with water mine model recognition system based on multi-agent system is proposed. A modified clonal selection algorithm for constructing such an INN is presented based on clonal selection principle. The INN is a two-layer Boolean network whose number of outputs is adaptable according to the task and the affinity threshold. Adjusting the affinity threshold can easily control different recognition precision, and the affinity threshold also can control the capability of noise tolerance.

  15. Multi-Agent Framework in Visual Sensor Networks

    Directory of Open Access Journals (Sweden)

    J. M. Molina

    2007-01-01

    Full Text Available The recent interest in the surveillance of public, military, and commercial scenarios is increasing the need to develop and deploy intelligent and/or automated distributed visual surveillance systems. Many applications based on distributed resources use the so-called software agent technology. In this paper, a multi-agent framework is applied to coordinate videocamera-based surveillance. The ability to coordinate agents improves the global image and task distribution efficiency. In our proposal, a software agent is embedded in each camera and controls the capture parameters. Then coordination is based on the exchange of high-level messages among agents. Agents use an internal symbolic model to interpret the current situation from the messages from all other agents to improve global coordination.

  16. Power Restoration in Medium Voltage Network Using Multiagent System

    Directory of Open Access Journals (Sweden)

    Miroslav Kovac

    2013-01-01

    Full Text Available The article describes a novel approach to a power restoration in medium voltage power distribution network. It focuses primary at searching of a new network configuration enabling to minimalize the size of faulted area and to restore the power for the highest possible number of loads. It describes characteristic features of medium voltage power distribution network and discusses the implementation of the presented approach in existing networks. A software tool, developed by the authors, including physical simulation of model network and its autonomous control system is described. An example of fault situation in a virtual distribution network is presented. Afterwards, the solution of restoration problem by proposed multiagent system is simulated using the software tool described in the paper.

  17. A competitive multi-agent model of interbank payment systems

    CERN Document Server

    Galbiati, Marco

    2007-01-01

    We develop a dynamic multi-agent model of an interbank payment system where banks choose their level of available funds on the basis of private payoff maximisation. The model consists of the repetition of a simultaneous move stage game with incomplete information, incomplete monitoring, and stochastic payoffs. Adaptation takes place with bayesian updating, with banks maximizing immediate payoffs. We carry out numerical simulations to solve the model and investigate two special scenarios: an operational incident and exogenous throughput guidelines for payment submission. We find that the demand for intraday credit is an S-shaped function of the cost ratio between intraday credit costs and the costs associated with delaying payments. We also find that the demand for liquidity is increased both under operational incidents and in the presence of effective throughput guidelines.

  18. An Analysis Architecture for Communications in Multi-agent Systems

    Directory of Open Access Journals (Sweden)

    Celia Gutiérrez

    2013-03-01

    Full Text Available Evaluation tools are significant from the Agent Oriented Software Engineering (AOSE point of view. Defective designs of communications in Multi-agent Systems (MAS may overload one or several agents, causing a bullying effect on them. Bullying communications have avoidable consequences, as high response times and low quality of service (QoS. Architectures that perform evaluation functionality must include features to measure the bullying activity and QoS, but it is also recommendable that they have reusability and scalability features. Evaluation tools with these features can be applied to a wide range of MAS, while minimizing designer’s effort. This work describes the design of an architecture for communication analysis, and its evolution to a modular version, that can be applied to different types of MAS. Experimentation of both versions shows differences between its executions.

  19. Intercell scheduling: A negotiation approach using multi-agent coalitions

    Science.gov (United States)

    Tian, Yunna; Li, Dongni; Zheng, Dan; Jia, Yunde

    2016-10-01

    Intercell scheduling problems arise as a result of intercell transfers in cellular manufacturing systems. Flexible intercell routes are considered in this article, and a coalition-based scheduling (CBS) approach using distributed multi-agent negotiation is developed. Taking advantage of the extended vision of the coalition agents, the global optimization is improved and the communication cost is reduced. The objective of the addressed problem is to minimize mean tardiness. Computational results show that, compared with the widely used combinatorial rules, CBS provides better performance not only in minimizing the objective, i.e. mean tardiness, but also in minimizing auxiliary measures such as maximum completion time, mean flow time and the ratio of tardy parts. Moreover, CBS is better than the existing intercell scheduling approach for the same problem with respect to the solution quality and computational costs.

  20. Sample efficient multiagent learning in the presence of Markovian agents

    CERN Document Server

    Chakraborty, Doran

    2014-01-01

    The problem of Multiagent Learning (or MAL) is concerned with the study of how intelligent entities can learn and adapt in the presence of other such entities that are simultaneously adapting. The problem is often studied in the stylized settings provided by repeated matrix games (a.k.a. normal form games). The goal of this book is to develop MAL algorithms for such a setting that achieve a new set of objectives which have not been previously achieved. In particular this book deals with learning in the presence of a new class of agent behavior that has not been studied or modeled before in a MAL context: Markovian agent behavior. Several new challenges arise when interacting with this particular class of agents. The book takes a series of steps towards building completely autonomous learning algorithms that maximize utility while interacting with such agents. Each algorithm is meticulously specified with a thorough formal treatment that elucidates its key theoretical properties.

  1. MARS: An Educational Environment for Multiagent Robot Simulations

    Directory of Open Access Journals (Sweden)

    Marco Casini

    2016-01-01

    Full Text Available Undergraduate robotics students often find it difficult to design and validate control algorithms for teams of mobile robots. This is mainly due to two reasons. First, very rarely, educational laboratories are equipped with large teams of robots, which are usually expensive, bulky, and difficult to manage and maintain. Second, robotics simulators often require students to spend much time to learn their use and functionalities. For this purpose, a simulator of multiagent mobile robots named MARS has been developed within the Matlab environment, with the aim of helping students to simulate a wide variety of control algorithms in an easy way and without spending time for understanding a new language. Through this facility, the user is able to simulate multirobot teams performing different tasks, from cooperative to competitive ones, by using both centralized and distributed controllers. Virtual sensors are provided to simulate real devices. A graphical user interface allows students to monitor the robots behaviour through an online animation.

  2. Iterative learning control for multi-agent systems coordination

    CERN Document Server

    Yang, Shiping; Li, Xuefang; Shen, Dong

    2016-01-01

    A timely guide using iterative learning control (ILC) as a solution for multi-agent systems (MAS) challenges, this book showcases recent advances and industrially relevant applications. Readers are first given a comprehensive overview of the intersection between ILC and MAS, then introduced to a range of topics that include both basic and advanced theoretical discussions, rigorous mathematics, engineering practice, and both linear and nonlinear systems. Through systematic discussion of network theory and intelligent control, the authors explore future research possibilities, develop new tools, and provide numerous applications such as power grids, communication and sensor networks, intelligent transportation systems, and formation control. Readers will gain a roadmap of the latest advances in the fields and can use their newfound knowledge to design their own algorithms.

  3. Adaptive Fuzzy Containment Control for Uncertain Nonlinear Multiagent Systems

    Directory of Open Access Journals (Sweden)

    Yang Yu

    2014-01-01

    Full Text Available This paper considers the containment control problem for uncertain nonlinear multiagent systems under directed graphs. The followers are governed by nonlinear systems with unknown dynamics while the multiple leaders are neighbors of a subset of the followers. Fuzzy logic systems (FLSs are used to identify the unknown dynamics and a distributed state feedback containment control protocol is proposed. This result is extended to the output feedback case, where observers are designed to estimate the unmeasurable states. Then, an output feedback containment control scheme is presented. The developed state feedback and output feedback containment controllers guarantee that the states of all followers converge to the convex hull spanned by the dynamic leaders. Based on Lyapunov stability theory, it is proved that the containment control errors are uniformly ultimately bounded (UUB. An example is provided to show the effectiveness of the proposed control method.

  4. Cooperative Control for Uncertain Multiagent Systems via Distributed Output Regulation

    Directory of Open Access Journals (Sweden)

    Lu Yu

    2013-01-01

    Full Text Available The distributed robust output regulation problem for multiagent systems is considered. For heterogeneous uncertain linear systems and a linear exosystem, the controlling aim is to stabilize the closed-loop system and meanwhile let the regulated outputs converge to the origin asymptotically, by the help of local interaction. The communication topology considered is directed acyclic graphs, which means directed graphs without loops. With distributed dynamic state feedback controller and output feedback controller, respectively, the solvability of the problem and the algorithm of controller design are both investigated. The solvability conditions are given in terms of linear matrix inequalities (LMIs. It is shown that, for polytopic uncertainties, the distributed controllers constructed by solving LMIs can satisfy the requirements of output regulation property.

  5. Team Formation in Partially Observable Multi-Agent Systems

    Science.gov (United States)

    Agogino, Adrian K.; Tumer, Kagan

    2004-01-01

    Sets of multi-agent teams often need to maximize a global utility rating the performance of the entire system where a team cannot fully observe other teams agents. Such limited observability hinders team-members trying to pursue their team utilities to take actions that also help maximize the global utility. In this article, we show how team utilities can be used in partially observable systems. Furthermore, we show how team sizes can be manipulated to provide the best compromise between having easy to learn team utilities and having them aligned with the global utility, The results show that optimally sized teams in a partially observable environments outperform one team in a fully observable environment, by up to 30%.

  6. Rigidity-Preserving Team Partitions in Multiagent Networks.

    Science.gov (United States)

    Carboni, Daniela; Williams, Ryan K; Gasparri, Andrea; Ulivi, Giovanni; Sukhatme, Gaurav S

    2015-12-01

    Motivated by the strong influence network rigidity has on collaborative systems, in this paper, we consider the problem of partitioning a multiagent network into two sub-teams, a bipartition, such that the resulting sub-teams are topologically rigid. In this direction, we determine the existence conditions for rigidity-preserving bipartitions, and provide an iterative algorithm that identifies such partitions in polynomial time. In particular, the relationship between rigid graph partitions and the previously identified Z-link edge structure is given, yielding a feasible direction for graph search. Adapting a supergraph search mechanism, we then detail a methodology for discerning graphs cuts that represent valid rigid bipartitions. Next, we extend our methods to a decentralized context by exploiting leader election and an improved graph search to evaluate feasible cuts using only local agent-to-agent communication. Finally, full algorithm details and pseudocode are provided, together with simulation results that verify correctness and demonstrate complexity.

  7. How Corruption Blunts Counternarcotic Policies in Afghanistan: A Multiagent Investigation

    Science.gov (United States)

    Geller, Armando; Mussavi Rizi, Seyed M.; Łatek, Maciej M.

    We report the results of multiagent modeling experiments on interactions between the drug industry and corruption in Afghanistan. The model formalizes assumptions on the motivations of players in the Afghan drug industry, quantifies the tradeoffs among various choices players face and enables inspection of the time, space and level of supply chain in which one can expect positive and negative impacts of counternarcotic policies. If reducing opium exports is one measure of effectiveness for NATO operations in Afghanistan, grasping the links between corruption and the drug industry should provide a better picture of the second-order interactions between corruption and investment in improving the governance quality, in deploying security forces tasked with eradication and interdiction and in programs to enhance rural livelihoods.

  8. Swarming behaviors in multi-agent systems with nonlinear dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Wenwu, E-mail: wenwuyu@gmail.com [Department of Mathematics, Southeast University, Nanjing 210096 (China); School of Electrical and Computer Engineering, RMIT University, Melbourne VIC 3001 (Australia); Chen, Guanrong [Department of Electronic Engineering, City University of Hong Kong, Hong Kong (China); Cao, Ming [Faculty of Mathematics and Natural Sciences, ITM, University of Groningen (Netherlands); Lü, Jinhu [Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190 (China); Zhang, Hai-Tao [Department of Control Science and Engineering, State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China)

    2013-12-15

    The dynamic analysis of a continuous-time multi-agent swarm model with nonlinear profiles is investigated in this paper. It is shown that, under mild conditions, all agents in a swarm can reach cohesion within a finite time, where the upper bounds of the cohesion are derived in terms of the parameters of the swarm model. The results are then generalized by considering stochastic noise and switching between nonlinear profiles. Furthermore, swarm models with limited sensing range inducing changing communication topologies and unbounded repulsive interactions between agents are studied by switching system and nonsmooth analysis. Here, the sensing range of each agent is limited and the possibility of collision among nearby agents is high. Finally, simulation results are presented to demonstrate the validity of the theoretical analysis.

  9. Flocking shape analysis of multi-agent systems

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    In this paper,we consider the shape control in flocking behavior of a multi-agent system with a virtual leader.Besides the traditional flocking control terms,which include a gradient-based term,a velocity consensus term and a navigational feed-back in general,a new piecewise smooth neighbor-based local controller is added to regulate the configuration to the desired flocking shape.All agent velocities approach the desired velocity asymptotically,while collisions among agents can be avoided.Furthermore,based on the proved stability,we obtain three kinds of flocking shapes,such as those in a single line,vee shape or corner shape.Some numerical simulation results are provided to demonstrate theoretical issues.

  10. Towards Time Automata and Multi-Agent Systems

    Science.gov (United States)

    Hutzler, G.; Klaudel, H.; Wang, D. Y.

    2004-01-01

    The design of reactive systems must comply with logical correctness (the system does what it is supposed to do) and timeliness (the system has to satisfy a set of temporal constraints) criteria. In this paper, we propose a global approach for the design of adaptive reactive systems, i.e., systems that dynamically adapt their architecture depending on the context. We use the timed automata formalism for the design of the agents' behavior. This allows evaluating beforehand the properties of the system (regarding logical correctness and timeliness), thanks to model-checking and simulation techniques. This model is enhanced with tools that we developed for the automatic generation of code, allowing to produce very quickly a running multi-agent prototype satisfying the properties of the model.

  11. Multi-Agent Flight Simulation with Robust Situation Generation

    Science.gov (United States)

    Johnson, Eric N.; Hansman, R. John, Jr.

    1994-01-01

    A robust situation generation architecture has been developed that generates multi-agent situations for human subjects. An implementation of this architecture was developed to support flight simulation tests of air transport cockpit systems. This system maneuvers pseudo-aircraft relative to the human subject's aircraft, generating specific situations for the subject to respond to. These pseudo-aircraft maneuver within reasonable performance constraints, interact in a realistic manner, and make pre-recorded voice radio communications. Use of this system minimizes the need for human experimenters to control the pseudo-agents and provides consistent interactions between the subject and the pseudo-agents. The achieved robustness of this system to typical variations in the subject's flight path was explored. It was found to successfully generate specific situations within the performance limitations of the subject-aircraft, pseudo-aircraft, and the script used.

  12. A new approach of designing Multi-Agent Systems

    CERN Document Server

    Maalal, Sara

    2012-01-01

    Agent technology is a software paradigm that permits to implement large and complex distributed applications. In order to assist analyzing, conception and development or implementation phases of multi-agent systems, we've tried to present a practical application of a generic and scalable method of a MAS with a component-oriented architecture and agent-based approach that allows MDA to generate source code from a given model. We've designed on AUML the class diagrams as a class meta-model of different agents of a MAS. Then we generated the source code of the models developed using an open source tool called AndroMDA. This agent-based and evolutive approach enhances the modularity and genericity developments and promotes their reusability in future developments. This property distinguishes our design methodology of existing methodologies in that it is constrained by any particular agent-based model while providing a library of generic models

  13. Selection of Structures with Grid Optimization, in Multiagent Data Warehouse

    Science.gov (United States)

    Gorawski, Marcin; Bańkowski, Sławomir; Gorawski, Michał

    The query optimization problem in data base and data warehouse management systems is quite similar. Changes to Joins sequences, projections and selections, usage of indexes, and aggregations are all decided during the analysis of an execution schedule. The main goal of these changes is to decrease the query response time. The optimization operation is often dedicated to a single node. This paper proposes optimization to grid or cluster data warehouses / databases. Tests were conducted in a multi-agent environment, and the optimization focused not only on a single node but on the whole system as well. A new idea is proposed here with multi-criteria optimization that is based on user-given parameters. Depending on query time, result admissible errors, and the level of system usage, task results were obtained along with grid optimization.

  14. A Multiagent Recommender System with Task-Based Agent Specialization

    Science.gov (United States)

    Lorenzi, Fabiana; Correa, Fabio Arreguy Camargo; Bazzan, Ana L. C.; Abel, Mara; Ricci, Francesco

    This paper describes a multiagent recommender system where agents maintain local knowledge bases and, when requested to support a travel planning task, they collaborate exchanging information stored in their local bases. A request for a travel recommendation is decomposed by the system into sub tasks, corresponding to travel services. Agents select tasks autonomously, and accomplish them with the help of the knowledge derived from previous solutions. In the proposed architecture, agents become experts in some task types, and this makes the recommendation generation more efficient. In this paper, we validate the model via simulations where agents collaborate to recommend a travel package to the user. The experiments show that specialization is useful hence providing a validation of the proposed model.

  15. Network-Based Practical Consensus of Heterogeneous Nonlinear Multiagent Systems.

    Science.gov (United States)

    Ding, Lei; Zheng, Wei Xing

    2016-09-07

    This paper studies network-based practical leader-following consensus problem of heterogeneous multiagent systems with Lipschitz nonlinear dynamics under both fixed and switching topologies. Considering the effect of network-induced delay, a network-based leader-following consensus protocol with heterogeneous gain matrix is proposed for each follower agent. By employing Lyapunov-Krasovskii method, a sufficient condition for designing the network-based consensus controller gain is derived such that the leader-following consensus error exponentially converges to a bounded region under a fixed topology. Correspondingly, the proposed design approach is then extended to the case of switching topology. Two numerical examples with networked Chua's circuits are given to show the efficiency of the design method proposed in this paper.

  16. Distributed Secure Coordinated Control for Multiagent Systems Under Strategic Attacks.

    Science.gov (United States)

    Feng, Zhi; Wen, Guanghui; Hu, Guoqiang

    2017-05-01

    This paper studies a distributed secure consensus tracking control problem for multiagent systems subject to strategic cyber attacks modeled by a random Markov process. A hybrid stochastic secure control framework is established for designing a distributed secure control law such that mean-square exponential consensus tracking is achieved. A connectivity restoration mechanism is considered and the properties on attack frequency and attack length rate are investigated, respectively. Based on the solutions of an algebraic Riccati equation and an algebraic Riccati inequality, a procedure to select the control gains is provided and stability analysis is studied by using Lyapunov's method.. The effect of strategic attacks on discrete-time systems is also investigated. Finally, numerical examples are provided to illustrate the effectiveness of theoretical analysis.

  17. Distributed Synchronization Control of Multiagent Systems With Unknown Nonlinearities.

    Science.gov (United States)

    Su, Shize; Lin, Zongli; Garcia, Alfredo

    2016-01-01

    This paper revisits the distributed adaptive control problem for synchronization of multiagent systems where the dynamics of the agents are nonlinear, nonidentical, unknown, and subject to external disturbances. Two communication topologies, represented, respectively, by a fixed strongly-connected directed graph and by a switching connected undirected graph, are considered. Under both of these communication topologies, we use distributed neural networks to approximate the uncertain dynamics. Decentralized adaptive control protocols are then constructed to solve the cooperative tracker problem, the problem of synchronization of all follower agents to a leader agent. In particular, we show that, under the proposed decentralized control protocols, the synchronization errors are ultimately bounded, and their ultimate bounds can be reduced arbitrarily by choosing the control parameter appropriately. Simulation study verifies the effectiveness of our proposed protocols.

  18. Distributed Adaptive Neural Control for Stochastic Nonlinear Multiagent Systems.

    Science.gov (United States)

    Wang, Fang; Chen, Bing; Lin, Chong; Li, Xuehua

    2016-11-14

    In this paper, a consensus tracking problem of nonlinear multiagent systems is investigated under a directed communication topology. All the followers are modeled by stochastic nonlinear systems in nonstrict feedback form, where nonlinearities and stochastic disturbance terms are totally unknown. Based on the structural characteristic of neural networks (in Lemma 4), a novel distributed adaptive neural control scheme is put forward. The raised control method not only effectively handles unknown nonlinearities in nonstrict feedback systems, but also copes with the interactions among agents and coupling terms. Based on the stochastic Lyapunov functional method, it is indicated that all the signals of the closed-loop system are bounded in probability and all followers' outputs are convergent to a neighborhood of the output of leader. At last, the efficiency of the control method is testified by a numerical example.

  19. Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms

    Science.gov (United States)

    Knudson, Matthew D.; Colby, Mitchell; Tumer, Kagan

    2014-01-01

    Dynamic flight environments in which objectives and environmental features change with respect to time pose a difficult problem with regards to planning optimal flight paths. Path planning methods are typically computationally expensive, and are often difficult to implement in real time if system objectives are changed. This computational problem is compounded when multiple agents are present in the system, as the state and action space grows exponentially. In this work, we use cooperative coevolutionary algorithms in order to develop policies which control agent motion in a dynamic multiagent unmanned aerial system environment such that goals and perceptions change, while ensuring safety constraints are not violated. Rather than replanning new paths when the environment changes, we develop a policy which can map the new environmental features to a trajectory for the agent while ensuring safe and reliable operation, while providing 92% of the theoretically optimal performance

  20. Tracking control for first-order multi-agent systems

    Institute of Scientific and Technical Information of China (English)

    Yang LIU; Yingmin JIA

    2008-01-01

    In this paper,the conventional tracking control problem is expanded to first-order multi-agent systerns,which can be solved by directly guiding any agent in the group.The following three kinds of desired motions are considered for all agents to track:1)stillness in space,2)variable motion with known acceleration,3) variable motion with partly unknown acceleration.Specifically,fixed networks with time delays and switching networks without delays are both considered in case 1).Switching networks with and without time delays are both studied in case 2),while for 3),switching networks without delays are mainly investigated.A numerical simulation example is included to illustrate the results.

  1. Cooperative peer-to-peer multiagent based systems

    CERN Document Server

    Caram, L F; Ausloos, M; Proto, A N

    2015-01-01

    A multiagent based model for a system of cooperative agents aiming at growth is proposed. This is based on a set of generalized Verhulst-Lotka-Volterra differential equations. In this study, strong cooperation is allowed among agents having similar sizes, and weak cooperation if agent have markedly different "sizes", thus establishing a peer-to-peer modulated interaction scheme. A rigorous analysis of the stable configurations is presented first examining the fixed points of the system, next determining their stability as a function of the model parameters. It is found that the agents are self-organizing into clusters. Furthermore, it is demonstrated that, depending on parameter values, multiple stable configurations can coexist. It occurs that only one of them always emerges with probability close to one, because its associated attractor dominates over the rest. This is shown through numerical integrations and simulations,after analytic developments. In contrast to the competitive case, agents are able to in...

  2. U-Learning Within A Context-Aware Multiagent Environment

    CERN Document Server

    Vladoiu, Monica

    2011-01-01

    New technological developments have made it possible to interact with computer systems and applications anywhere and anytime. It is vital that these applications are able to adapt to the user, as a person, and to its current situation, whatever that is. Therefore, the premises for evolution towards a learning society and a knowledge economy are present. Hence, there is a stringent demand for new learner-centred frameworks that allow active participation of learners in knowledge creation within communities, organizations, territories and society, at large. This paper presents the multi-agent architecture of our context-aware system and the learning scenarios within ubiquitous learning environments that the system provides support for. This architecture is the outcome of our endeavour to develop ePH, a system for sharing public interest information and knowledge, which is accessible through always-on, context-aware services.

  3. Multi-agent cooperative intrusion response in mobile adhoc networks

    Institute of Scientific and Technical Information of China (English)

    Yi Ping; Zou Futai; Jiang Xinghao; Li Jianhua

    2007-01-01

    The nature of adhoc networks makes them vulnerable to security attacks. Many security technologies such as intrusion prevention and intrusion detection are passive in response to intrusions in that their countermeasures are only to protect the networks, and there is no automated network-wide counteraction against detected intrusions. the architecture of cooperation intrusion response based multi-agent is propose. The architecture is composed of mobile agents. Monitor agent resides on every node and monitors its neighbor nodes. Decision agent collects information from monitor nodes and detects an intrusion by security policies. When an intruder is found in the architecture, the block agents will get to the neighbor nodes of the intruder and form the mobile firewall to isolate the intruder. In the end, we evaluate it by simulation.

  4. Multiagent Systems and Applications Volume 1Practice and Experience

    CERN Document Server

    Jain, Lakhmi

    2013-01-01

    The focus of the book is on completed implementations of agent-based software systems. Here, agent technology is considered broadly, starting from development of agent platforms, all the way through systems actually implemented. The covered topics also include lessons learned during implementation of agent platforms and the reflection on the process of development and application of agent-based systems.   The book includes 10 chapters where interested reader can find discussion of important issues encountered during development of well-known agent platforms such as JADE and Jadex as well as some interesting experiences in developing a new platform that combines software agent and Web Services. Furthermore, the book shows readers several valuable examples of applications based on multi-agent systems including simulations, agents in autonomous negotiations and agents in public administration modelling. We believe that the book will prove useful to the researchers, professors and the practitioners in all discip...

  5. Swarming behaviors in multi-agent systems with nonlinear dynamics.

    Science.gov (United States)

    Yu, Wenwu; Chen, Guanrong; Cao, Ming; Lü, Jinhu; Zhang, Hai-Tao

    2013-12-01

    The dynamic analysis of a continuous-time multi-agent swarm model with nonlinear profiles is investigated in this paper. It is shown that, under mild conditions, all agents in a swarm can reach cohesion within a finite time, where the upper bounds of the cohesion are derived in terms of the parameters of the swarm model. The results are then generalized by considering stochastic noise and switching between nonlinear profiles. Furthermore, swarm models with limited sensing range inducing changing communication topologies and unbounded repulsive interactions between agents are studied by switching system and nonsmooth analysis. Here, the sensing range of each agent is limited and the possibility of collision among nearby agents is high. Finally, simulation results are presented to demonstrate the validity of the theoretical analysis.

  6. Covert Reinforcement: A Partial Replication.

    Science.gov (United States)

    Ripstra, Constance C.; And Others

    A partial replication of an investigation of the effect of covert reinforcement on a perceptual estimation task is described. The study was extended to include an extinction phase. There were five treatment groups: covert reinforcement, neutral scene reinforcement, noncontingent covert reinforcement, and two control groups. Each subject estimated…

  7. Deliberate change without hierarchical influence?

    DEFF Research Database (Denmark)

    Nørskov, Sladjana; Kesting, Peter; Ulhøi, John Parm

    2017-01-01

    Purpose This paper aims to present that deliberate change is strongly associated with formal structures and top-down influence. Hierarchical configurations have been used to structure processes, overcome resistance and get things done. But is deliberate change also possible without formal...... reveals that deliberate change is indeed achievable in a non-hierarchical collaborative OSS community context. However, it presupposes the presence and active involvement of informal change agents. The paper identifies and specifies four key drivers for change agents’ influence. Originality....../value The findings contribute to organisational analysis by providing a deeper understanding of the importance of leadership in making deliberate change possible in non-hierarchical settings. It points to the importance of “change-by-conviction”, essentially based on voluntary behaviour. This can open the door...

  8. Static Correctness of Hierarchical Procedures

    DEFF Research Database (Denmark)

    Schwartzbach, Michael Ignatieff

    1990-01-01

    A system of hierarchical, fully recursive types in a truly imperative language allows program fragments written for small types to be reused for all larger types. To exploit this property to enable type-safe hierarchical procedures, it is necessary to impose a static requirement on procedure calls....... We introduce an example language and prove the existence of a sound requirement which preserves static correctness while allowing hierarchical procedures. This requirement is further shown to be optimal, in the sense that it imposes as few restrictions as possible. This establishes the theoretical...... basis for a general type hierarchy with static type checking, which enables first-order polymorphism combined with multiple inheritance and specialization in a language with assignments. We extend the results to include opaque types. An opaque version of a type is different from the original but has...

  9. A hierarchical instrumental decision theory of nicotine dependence.

    Science.gov (United States)

    Hogarth, Lee; Troisi, Joseph R

    2015-01-01

    It is important to characterize the learning processes governing tobacco-seeking in order to understand how best to treat this behavior. Most drug learning theories have adopted a Pavlovian framework wherein the conditioned response is the main motivational process. We favor instead a hierarchical instrumental decision account, wherein expectations about the instrumental contingency between voluntary tobacco-seeking and the receipt of nicotine reward determines the probability of executing this behavior. To support this view, we review titration and nicotine discrimination research showing that internal signals for deprivation/satiation modulate expectations about the current incentive value of smoking, thereby modulating the propensity of this behavior. We also review research on cue-reactivity which has shown that external smoking cues modulate expectations about the probability of the tobacco-seeking response being effective, thereby modulating the propensity of this behavior. Economic decision theory is then considered to elucidate how expectations about the value and probability of response-nicotine contingency are integrated to form an overall utility estimate for that option for comparison with qualitatively different, nonsubstitute reinforcers, to determine response selection. As an applied test for this hierarchical instrumental decision framework, we consider how well it accounts for individual liability to smoking uptake and perseveration, pharmacotherapy, cue-extinction therapies, and plain packaging. We conclude that the hierarchical instrumental account is successful in reconciling this broad range of phenomenon precisely because it accepts that multiple diverse sources of internal and external information must be integrated to shape the decision to smoke.

  10. Structural integrity of hierarchical composites

    Directory of Open Access Journals (Sweden)

    Marco Paggi

    2012-01-01

    Full Text Available Interface mechanical problems are of paramount importance in engineering and materials science. Traditionally, due to the complexity of modelling their mechanical behaviour, interfaces are often treated as defects and their features are not explored. In this study, a different approach is illustrated, where the interfaces play an active role in the design of innovative hierarchical composites and are fundamental for their structural integrity. Numerical examples regarding cutting tools made of hierarchical cellular polycrystalline materials are proposed, showing that tailoring of interface properties at the different scales is the way to achieve superior mechanical responses that cannot be obtained using standard materials

  11. VISUAL REINFORCEMENT IN FIGHTING COCKS.

    Science.gov (United States)

    THOMPSON, T I

    1964-01-01

    Fighting cocks were conditioned to emit a key-pecking response on a fixed ratio reinforcement schedule leading to the visual image of another fighting cock. In addition, the relative reinforcing properties of the visual reinforcer were compared with food and water reinforcers in a three-choice, non-reversible option situation. The relative reinforcing effects of mirror presentation and another rooster visually presented through a window, were compared. The mirror maintained a relatively lower response output.

  12. Reinforcement learning agents providing advice in complex video games

    Science.gov (United States)

    Taylor, Matthew E.; Carboni, Nicholas; Fachantidis, Anestis; Vlahavas, Ioannis; Torrey, Lisa

    2014-01-01

    This article introduces a teacher-student framework for reinforcement learning, synthesising and extending material that appeared in conference proceedings [Torrey, L., & Taylor, M. E. (2013)]. Teaching on a budget: Agents advising agents in reinforcement learning. {Proceedings of the international conference on autonomous agents and multiagent systems}] and in a non-archival workshop paper [Carboni, N., &Taylor, M. E. (2013, May)]. Preliminary results for 1 vs. 1 tactics in StarCraft. {Proceedings of the adaptive and learning agents workshop (at AAMAS-13)}]. In this framework, a teacher agent instructs a student agent by suggesting actions the student should take as it learns. However, the teacher may only give such advice a limited number of times. We present several novel algorithms that teachers can use to budget their advice effectively, and we evaluate them in two complex video games: StarCraft and Pac-Man. Our results show that the same amount of advice, given at different moments, can have different effects on student learning, and that teachers can significantly affect student learning even when students use different learning methods and state representations.

  13. Behavior of reinforced concrete beams reinforced with GFRP bars

    Directory of Open Access Journals (Sweden)

    D. H. Tavares

    Full Text Available The use of fiber reinforced polymer (FRP bars is one of the alternatives presented in recent studies to prevent the drawbacks related to the steel reinforcement in specific reinforced concrete members. In this work, six reinforced concrete beams were submitted to four point bending tests. One beam was reinforced with CA-50 steel bars and five with glass fiber reinforced polymer (GFRP bars. The tests were carried out in the Department of Structural Engineering in São Carlos Engineering School, São Paulo University. The objective of the test program was to compare strength, reinforcement deformation, displacement, and some anchorage aspects between the GFRP-reinforced concrete beams and the steel-reinforced concrete beam. The results show that, even though four GFRP-reinforced concrete beams were designed with the same internal tension force as that with steel reinforcement, their capacity was lower than that of the steel-reinforced beam. The results also show that similar flexural capacity can be achieved for the steel- and for the GFRP-reinforced concrete beams by controlling the stiffness (reinforcement modulus of elasticity multiplied by the bar cross-sectional area - EA and the tension force of the GFRP bars.

  14. Preference for 50% reinforcement over 75% reinforcement by pigeons.

    Science.gov (United States)

    Gipson, Cassandra D; Alessandri, Jérôme J D; Miller, Holly C; Zentall, Thomas R

    2009-11-01

    When pigeons are given a choice between an initial-link alternative that results in either a terminal-link stimulus correlated with 100% reinforcement or a stimulus correlated with 0% reinforcement (overall 50% reinforcement) and another initial-link alternative that always results in a terminal-link stimulus correlated with 100% reinforcement, some pigeons show a preference for the initial-link alternative correlated with 50% reinforcement. Using this procedure, in Experiment 1, we found a relatively modest preference for 100% over 50% reinforcement. In Experiment 2, we decreased the reinforcement density for the second initial-link alternative to 75% and found a significant preference for the 50% reinforcement initial-link alternative. It may be that this "maladaptive" behavior results from a positive contrast between the expectation of reinforcement correlated with the 50% reinforcement initial-link alternative and the terminal-link stimulus correlated with 100% reinforcement. But apparently, the complementary negative contrast does not develop between the expectation of reinforcement correlated with the 50% reinforcement initial-link alternative and the terminal-link stimulus correlated with 0% reinforcement that often follow. Such paradoxical choice may account for certain human appetitive risk-taking behavior (e.g., gambling) as well.

  15. Sensory Hierarchical Organization and Reading.

    Science.gov (United States)

    Skapof, Jerome

    The purpose of this study was to judge the viability of an operational approach aimed at assessing response styles in reading using the hypothesis of sensory hierarchical organization. A sample of 103 middle-class children from a New York City public school, between the ages of five and seven, took part in a three phase experiment. Phase one…

  16. Memory Stacking in Hierarchical Networks.

    Science.gov (United States)

    Westö, Johan; May, Patrick J C; Tiitinen, Hannu

    2016-02-01

    Robust representations of sounds with a complex spectrotemporal structure are thought to emerge in hierarchically organized auditory cortex, but the computational advantage of this hierarchy remains unknown. Here, we used computational models to study how such hierarchical structures affect temporal binding in neural networks. We equipped individual units in different types of feedforward networks with local memory mechanisms storing recent inputs and observed how this affected the ability of the networks to process stimuli context dependently. Our findings illustrate that these local memories stack up in hierarchical structures and hence allow network units to exhibit selectivity to spectral sequences longer than the time spans of the local memories. We also illustrate that short-term synaptic plasticity is a potential local memory mechanism within the auditory cortex, and we show that it can bring robustness to context dependence against variation in the temporal rate of stimuli, while introducing nonlinearities to response profiles that are not well captured by standard linear spectrotemporal receptive field models. The results therefore indicate that short-term synaptic plasticity might provide hierarchically structured auditory cortex with computational capabilities important for robust representations of spectrotemporal patterns.

  17. Modelling reinforcement corrosion in concrete

    DEFF Research Database (Denmark)

    Michel, Alexander; Geiker, Mette Rica; Stang, Henrik

    2012-01-01

    A physio-chemical model for the simulation of reinforcement corrosion in concrete struc-tures was developed. The model allows for simulation of initiation and subsequent propaga-tion of reinforcement corrosion. Corrosion is assumed to be initiated once a defined critical chloride threshold...... is reached causing the formation of anodic and cathodic regions along the reinforcement. Critical chloride thresholds, randomly distributed along the reinforcement sur-face, link the initiation and propagation phase of reinforcement corrosion. To demonstrate the potential use of the developed model......, a numerical example is pre-sented, that illustrates the formation of corrosion cells as well as propagation of corrosion in a reinforced concrete structure....

  18. 基于多代理系统的多微网能量协调控制%Energy coordination control of multi-microgrid based on multi-agent system

    Institute of Scientific and Technical Information of China (English)

    丁明; 马凯; 毕锐

    2013-01-01

    Energy coordination is an important requirement for stable operation of the multi-microgrid system. This paper presents a hierarchical control scheme based on multi-agent system (MAS) to cope with the problem of energy coordination of a multi-microgrid system. Based on java agent development framework (JADE), a layered multi-agent system framework is constructed, including distributed generation level, microgrid level, multi-microgrids level and distribution network level. The energy coordination process and optimization objectives are discussed. Depending on the properties of the agents’ autonomy and collaboration, the system could ensure the energy coordination in a microgrid and among microgrids. An example of a typical multi-microgrid system is used to discuss the function of the agents and their interactions. The results verify the effectiveness of the hierarchical control scheme based on multi-agent system and its applicability for hierarchical energy management of multi-microgrid system.%多微网系统的能量协调是其稳定运行的必要条件。针对多微网系统的能量协调提出了基于多代理系统(Multi-Agent System,MAS)的分层控制方案,采用JADE(Java Agent Development Framework)平台构建包括单元层、单微网层、多微网层和配网层的层次化多代理系统框架,给出了多微网系统的能量协调过程和优化目标,利用代理的自治性和协作性,实现稳态运行时微网内部、多微网之间的能量协调。以一个多微网系统为例,讨论了各Agent的功能及各Agent之间的交互,验证了所建立的基于MAS的分层控制方案的有效性,适用于多微网系统能量分层管理。

  19. A Q-based integrating interaction framework system for multi-agent coordination

    Institute of Scientific and Technical Information of China (English)

    WANG Zhen-jie; SHENG Huan-ye; XIAO Zheng-guang

    2005-01-01

    Interaction is one of the crucial features of multi-agent systems, in which there are two kinds of interaction: agent-to-agent and human-to-agent. In order to unify the two kinds of interaction while designing multiagent systems, this paper introduces Q language-a scenario description language for designing interaction among agents and humans. Based on Q, we propose an integrating interaction framework system for multi-agent coordination, in which Q scenarios are used to uniformly describe both kinds of interactions. Being in accordance to the characteristics of Q language, the Q-based framework makes the interaction process open and easily understood by the users. Additionally, it makes specific applications of multi-agent systems easy to be established by application designers. By applying agent negotiation in agent-mediated e-commerce and agent cooperation in interoperable information query on the Semantic Web, we illustrate how the presented framework for multi-agent coordination is implemented in concrete applications. At the same time, these two different applications also demonstrate usability of the presented framework and verify validity of Q language.

  20. Network resources management in a multi-agent system: A simulative approach

    Directory of Open Access Journals (Sweden)

    Ganiyu A. Aderounmu

    2010-09-01

    Full Text Available Multi-agent systems (i.e. systems comprising many agents have been proposed for many Internet and distributed applications. The proposed systems have little or no consideration of the effects of this multi-agent approach on network resources. In this paper, we presented a simulation assessment of the effect of multi-agent systems on network resources. The routing scheme of the agents was formulated based on the travelling salesman problem. Lightweight agent (LWA controller was modelled using a fuzzy logic toolbox in the MATLAB environment. The performance metrics of bandwidth usage, response time and throughput were used to compare the network resources usage by different groups of LWAs (10 LWAs, 40 LWAs, 100 LWAs, 150 LWAs during their computational task on the network. Java programs were written for the implementation of lightweight agents in the simulation. The inputs to the system were realised by multiplicative pseudorandom number generation during the simulation. The simulation result analysis was carried out based on the performance metrics stated above for the four groups of agents. Increasing the number of LWAs in a simulated multi-agent system decreased the response time but increased the throughput and the bandwidth usage. All these performance measures should be considered for developing countries with bandwidth shortages, because having too many agents in a multi-agent system could result in bandwidth wastages.

  1. Finite-Horizon H∞ Consensus Control of Time-Varying Multiagent Systems With Stochastic Communication Protocol.

    Science.gov (United States)

    Zou, Lei; Wang, Zidong; Gao, Huijun; Alsaadi, Fuad E

    2017-03-31

    This paper is concerned with the distributed H∞ consensus control problem for a discrete time-varying multiagent system with the stochastic communication protocol (SCP). A directed graph is used to characterize the communication topology of the multiagent network. The data transmission between each agent and the neighboring ones is implemented via a constrained communication channel where only one neighboring agent is allowed to transmit data at each time instant. The SCP is applied to schedule the signal transmission of the multiagent system. A sequence of random variables is utilized to capture the scheduling behavior of the SCP. By using the mapping technology combined with the Hadamard product, the closed-loop multiagent system is modeled as a time-varying system with a stochastic parameter matrix. The purpose of the addressed problem is to design a cooperative controller for each agent such that, for all probabilistic scheduling behaviors, the H∞ consensus performance is achieved over a given finite horizon for the closed-loop multiagent system. A necessary and sufficient condition is derived to ensure the H∞ consensus performance based on the completing squares approach and the stochastic analysis technique. Then, the controller parameters are obtained by solving two coupled backward recursive Riccati difference equations. Finally, a numerical example is given to illustrate the effectiveness of the proposed controller design scheme.

  2. Reinforcement Magnitude: An Evaluation of Preference and Reinforcer Efficacy

    OpenAIRE

    Trosclair-Lasserre, Nicole M.; Lerman, Dorothea C; Call, Nathan A; Addison, Laura R; Kodak, Tiffany

    2008-01-01

    Consideration of reinforcer magnitude may be important for maximizing the efficacy of treatment for problem behavior. Nonetheless, relatively little is known about children's preferences for different magnitudes of social reinforcement or the extent to which preference is related to differences in reinforcer efficacy. The purpose of the current study was to evaluate the relations among reinforcer magnitude, preference, and efficacy by drawing on the procedures and results of basic experimenta...

  3. Hierarchical Prisoner's Dilemma in Hierarchical Public-Goods Game

    CERN Document Server

    Fujimoto, Yuma; Kaneko, Kunihiko

    2016-01-01

    The dilemma in cooperation is one of the major concerns in game theory. In a public-goods game, each individual pays a cost for cooperation, or to prevent defection, and receives a reward from the collected cost in a group. Thus, defection is beneficial for each individual, while cooperation is beneficial for the group. Now, groups (say, countries) consisting of individual players also play games. To study such a multi-level game, we introduce a hierarchical public-goods (HPG) game in which two groups compete for finite resources by utilizing costs collected from individuals in each group. Analyzing this HPG game, we found a hierarchical prisoner's dilemma, in which groups choose the defection policy (say, armaments) as a Nash strategy to optimize each group's benefit, while cooperation optimizes the total benefit. On the other hand, for each individual within a group, refusing to pay the cost (say, tax) is a Nash strategy, which turns to be a cooperation policy for the group, thus leading to a hierarchical d...

  4. Reinforcement Magnitude: An Evaluation of Preference and Reinforcer Efficacy

    Science.gov (United States)

    Trosclair-Lasserre, Nicole M.; Lerman, Dorothea C.; Call, Nathan A.; Addison, Laura R.; Kodak, Tiffany

    2008-01-01

    Consideration of reinforcer magnitude may be important for maximizing the efficacy of treatment for problem behavior. Nonetheless, relatively little is known about children's preferences for different magnitudes of social reinforcement or the extent to which preference is related to differences in reinforcer efficacy. The purpose of the current…

  5. Reinforcement and learning

    NARCIS (Netherlands)

    Servedio, M.R.; Sæther, S.A.; Sætre, G.-P.

    2009-01-01

    Evidence has been accumulating to support the process of reinforcement as a potential mechanism in speciation. In many species, mate choice decisions are influenced by cultural factors, including learned mating preferences (sexual imprinting) or learned mate attraction signals (e.g., bird song). It

  6. Motivated Reinforcement Learning

    CERN Document Server

    Maher, Mary Lou

    2009-01-01

    Motivated learning is a research field in artificial intelligence and cognitive modelling. This book describes how motivated reinforcement learning agents can be used in computer games for the design of non-player characters that can adapt their behaviour in response to unexpected changes in their environment

  7. Glass Fibre Reinforced Polymers

    NARCIS (Netherlands)

    Nikolaou, N.; Karagianni, L.; Sarakiniatti, M.V.

    2014-01-01

    This "designers' manual" is made during the TIDO-course AR0533 Innovation & Sustainability. Fibre reinforced polymers (FRPs) have been used in many applications over the years, from new construction to retrofitting. They are lightweight, no-corrosive, exhibit high specific strength and specific

  8. Oscillations following periodic reinforcement.

    Science.gov (United States)

    Monteiro, Tiago; Machado, Armando

    2009-06-01

    Three experiments examined behavior in extinction following periodic reinforcement. During the first phase of Experiment 1, four groups of pigeons were exposed to fixed interval (FI 16s or FI 48s) or variable interval (VI 16s or VI 48s) reinforcement schedules. Next, during the second phase, each session started with reinforcement trials and ended with an extinction segment. Experiment 2 was similar except that the extinction segment was considerably longer. Experiment 3 replaced the FI schedules with a peak procedure, with FI trials interspersed with non-food peak interval (PI) trials that were four times longer. One group of pigeons was exposed to FI 20s PI 80s trials, and another to FI 40s PI 160s trials. Results showed that, during the extinction segment, most pigeons trained with FI schedules, but not with VI schedules, displayed pause-peck oscillations with a period close to, but slightly greater than the FI parameter. These oscillations did not start immediately after the onset of extinction. Comparing the oscillations from Experiments 1 and 2 suggested that the alternation of reconditioning and re-extinction increases the reliability and earlier onset of the oscillations. In Experiment 3 the pigeons exhibited well-defined pause-peck cycles since the onset of extinction. These cycles had periods close to twice the value of the FI and lasted for long intervals of time. We discuss some hypotheses concerning the processes underlying behavioral oscillations following periodic reinforcement.

  9. Fibre reinforced polymer nanocomposites

    NARCIS (Netherlands)

    Vlasveld, D.P.N.

    2005-01-01

    In this thesis the results are described of the research on a combination of two types of composites: thermoplastic nanocomposites and continuous fibre composites. In this three-phase composite the main reinforcing phase are continuous glass or carbon fibres, and the matrix consists of a polyamide 6

  10. Turbomachine blade reinforcement

    Energy Technology Data Exchange (ETDEWEB)

    Garcia Crespo, Andres Jose

    2016-09-06

    Embodiments of the present disclosure include a system having a turbomachine blade segment including a blade and a mounting segment coupled to the blade, wherein the mounting segment has a plurality of reinforcement pins laterally extending at least partially through a neck of the mounting segment.

  11. Glass Fibre Reinforced Polymers

    NARCIS (Netherlands)

    Nikolaou, N.; Karagianni, L.; Sarakiniatti, M.V.

    2014-01-01

    This "designers' manual" is made during the TIDO-course AR0533 Innovation & Sustainability. Fibre reinforced polymers (FRPs) have been used in many applications over the years, from new construction to retrofitting. They are lightweight, no-corrosive, exhibit high specific strength and specific sti

  12. Reinforcement and learning

    NARCIS (Netherlands)

    Servedio, M.R.; Sæther, S.A.; Sætre, G.-P.

    2009-01-01

    Evidence has been accumulating to support the process of reinforcement as a potential mechanism in speciation. In many species, mate choice decisions are influenced by cultural factors, including learned mating preferences (sexual imprinting) or learned mate attraction signals (e.g., bird song). It

  13. Reinforced aerodynamic profile

    DEFF Research Database (Denmark)

    2010-01-01

    The present invention relates to the prevention of deformations in an aerodynamic profile caused by lack of resistance to the bending moment forces that are created when such a profile is loaded in operation. More specifically, the invention relates to a reinforcing element inside an aerodynamic...

  14. Hierarchical structure of biological systems

    Science.gov (United States)

    Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

    2014-01-01

    A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems. PMID:24145961

  15. Automatic Hierarchical Color Image Classification

    Directory of Open Access Journals (Sweden)

    Jing Huang

    2003-02-01

    Full Text Available Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This scheme relies on using a good low-level feature and subsequently performing feature-space reconfiguration using singular value decomposition to reduce noise and dimensionality. We use the training data to obtain a hierarchical classification tree that can be used to categorize new images. Our experimental results suggest that this scheme not only performs better than standard nearest-neighbor techniques, but also has both storage and computational advantages.

  16. Intuitionistic fuzzy hierarchical clustering algorithms

    Institute of Scientific and Technical Information of China (English)

    Xu Zeshui

    2009-01-01

    Intuitionistic fuzzy set (IFS) is a set of 2-tuple arguments, each of which is characterized by a mem-bership degree and a nonmembership degree. The generalized form of IFS is interval-valued intuitionistic fuzzy set (IVIFS), whose components are intervals rather than exact numbers. IFSs and IVIFSs have been found to be very useful to describe vagueness and uncertainty. However, it seems that little attention has been focused on the clus-tering analysis of IFSs and IVIFSs. An intuitionistic fuzzy hierarchical algorithm is introduced for clustering IFSs, which is based on the traditional hierarchical clustering procedure, the intuitionistic fuzzy aggregation operator, and the basic distance measures between IFSs: the Hamming distance, normalized Hamming, weighted Hamming, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance. Subsequently, the algorithm is extended for clustering IVIFSs. Finally the algorithm and its extended form are applied to the classifications of building materials and enterprises respectively.

  17. Hierarchical Formation of Galactic Clusters

    CERN Document Server

    Elmegreen, B G

    2006-01-01

    Young stellar groupings and clusters have hierarchical patterns ranging from flocculent spiral arms and star complexes on the largest scale to OB associations, OB subgroups, small loose groups, clusters and cluster subclumps on the smallest scales. There is no obvious transition in morphology at the cluster boundary, suggesting that clusters are only the inner parts of the hierarchy where stars have had enough time to mix. The power-law cluster mass function follows from this hierarchical structure: n(M_cl) M_cl^-b for b~2. This value of b is independently required by the observation that the summed IMFs from many clusters in a galaxy equals approximately the IMF of each cluster.

  18. Hierarchical matrices algorithms and analysis

    CERN Document Server

    Hackbusch, Wolfgang

    2015-01-01

    This self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix. The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition. Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists ...

  19. Hierarchical Cont-Bouchaud model

    CERN Document Server

    Paluch, Robert; Holyst, Janusz A

    2015-01-01

    We extend the well-known Cont-Bouchaud model to include a hierarchical topology of agent's interactions. The influence of hierarchy on system dynamics is investigated by two models. The first one is based on a multi-level, nested Erdos-Renyi random graph and individual decisions by agents according to Potts dynamics. This approach does not lead to a broad return distribution outside a parameter regime close to the original Cont-Bouchaud model. In the second model we introduce a limited hierarchical Erdos-Renyi graph, where merging of clusters at a level h+1 involves only clusters that have merged at the previous level h and we use the original Cont-Bouchaud agent dynamics on resulting clusters. The second model leads to a heavy-tail distribution of cluster sizes and relative price changes in a wide range of connection densities, not only close to the percolation threshold.

  20. Multi-agent based control of large-scale complex systems employing distributed dynamic inference engine

    Science.gov (United States)

    Zhang, Daili

    Increasing societal demand for automation has led to considerable efforts to control large-scale complex systems, especially in the area of autonomous intelligent control methods. The control system of a large-scale complex system needs to satisfy four system level requirements: robustness, flexibility, reusability, and scalability. Corresponding to the four system level requirements, there arise four major challenges. First, it is difficult to get accurate and complete information. Second, the system may be physically highly distributed. Third, the system evolves very quickly. Fourth, emergent global behaviors of the system can be caused by small disturbances at the component level. The Multi-Agent Based Control (MABC) method as an implementation of distributed intelligent control has been the focus of research since the 1970s, in an effort to solve the above-mentioned problems in controlling large-scale complex systems. However, to the author's best knowledge, all MABC systems for large-scale complex systems with significant uncertainties are problem-specific and thus difficult to extend to other domains or larger systems. This situation is partly due to the control architecture of multiple agents being determined by agent to agent coupling and interaction mechanisms. Therefore, the research objective of this dissertation is to develop a comprehensive, generalized framework for the control system design of general large-scale complex systems with significant uncertainties, with the focus on distributed control architecture design and distributed inference engine design. A Hybrid Multi-Agent Based Control (HyMABC) architecture is proposed by combining hierarchical control architecture and module control architecture with logical replication rings. First, it decomposes a complex system hierarchically; second, it combines the components in the same level as a module, and then designs common interfaces for all of the components in the same module; third, replications