A knowledge base architecture for distributed knowledge agents

Science.gov (United States)

Riedesel, Joel; Walls, Bryan

1990-01-01

A tuple space based object oriented model for knowledge base representation and interpretation is presented. An architecture for managing distributed knowledge agents is then implemented within the model. The general model is based upon a database implementation of a tuple space. Objects are then defined as an additional layer upon the database. The tuple space may or may not be distributed depending upon the database implementation. A language for representing knowledge and inference strategy is defined whose implementation takes advantage of the tuple space. The general model may then be instantiated in many different forms, each of which may be a distinct knowledge agent. Knowledge agents may communicate using tuple space mechanisms as in the LINDA model as well as using more well known message passing mechanisms. An implementation of the model is presented describing strategies used to keep inference tractable without giving up expressivity. An example applied to a power management and distribution network for Space Station Freedom is given.

An Intelligent Knowledge Management System from a Semantic Perspective

Directory of Open Access Journals (Sweden)

Vasile MAZILESCU

2008-01-01

Full Text Available Knowledge Management Systems (KMS are important tools by whichorganizations can better use information and, more importantly, manageknowledge. Unlike other strategies, knowledge management (KM is difficult todefine because it encompasses a range of concepts, management tasks,technologies, and organizational practices, all of which come under the umbrella ofthe information management. Semantic approaches allow easier and more efficienttraining, maintenance, and support knowledge. Current ICT markets are dominatedby relational databases and document-centric information technologies, proceduralalgorithmic programming paradigms, and stack architecture. A key driver of globaleconomic expansion in the coming decade is the build-out of broadbandtelecommunications and the deployment of intelligent services bundling. This paperintroduces the main characteristics of an Intelligent Knowledge ManagementSystem as a multiagent system used in a Learning Control Problem (IKMSLCP,from a semantic perspective. We describe an intelligent KM framework, allowingthe observer (a human agent to learn from experience. This framework makes thesystem dynamic (flexible and adaptable so it evolves, guaranteeing high levels ofstability when performing his domain problem P. To capture by the agent who learnthe control knowledge for solving a task-allocation problem, the control expertsystem uses at any time, an internal fuzzy knowledge model of the (businessprocess based on the last knowledge model.

Combining human and machine intelligence to derive agents' behavioral rules for groundwater irrigation

Science.gov (United States)

Hu, Yao; Quinn, Christopher J.; Cai, Ximing; Garfinkle, Noah W.

2017-11-01

For agent-based modeling, the major challenges in deriving agents' behavioral rules arise from agents' bounded rationality and data scarcity. This study proposes a "gray box" approach to address the challenge by incorporating expert domain knowledge (i.e., human intelligence) with machine learning techniques (i.e., machine intelligence). Specifically, we propose using directed information graph (DIG), boosted regression trees (BRT), and domain knowledge to infer causal factors and identify behavioral rules from data. A case study is conducted to investigate farmers' pumping behavior in the Midwest, U.S.A. Results show that four factors identified by the DIG algorithm- corn price, underlying groundwater level, monthly mean temperature and precipitation- have main causal influences on agents' decisions on monthly groundwater irrigation depth. The agent-based model is then developed based on the behavioral rules represented by three DIGs and modeled by BRTs, and coupled with a physically-based groundwater model to investigate the impacts of agents' pumping behavior on the underlying groundwater system in the context of coupled human and environmental systems.

Design and Application of an Intelligent Agent for Web Information Discovery

Institute of Scientific and Technical Information of China (English)

闵君; 冯珊; 唐超; 许立达

2003-01-01

With the propagation of applications on the internet, the internet has become a great information source which supplies users with valuable information. But it is hard for users to quickly acquire the right information on the web. This paper an intelligent agent for internet applications to retrieve and extract web information under user's guidance. The intelligent agent is made up of a retrieval script to identify web sources, an extraction script based on the document object model to express extraction process, a data translator to export the extracted information into knowledge bases with frame structures, and a data reasoning to reply users' questions. A GUI tool named Script Writer helps to generate the extraction script visually, and knowledge rule databases help to extract wanted information and to generate the answer to questions.

An Intelligent Agent-Controlled and Robot-Based Disassembly Assistant

Science.gov (United States)

Jungbluth, Jan; Gerke, Wolfgang; Plapper, Peter

2017-09-01

One key for successful and fluent human-robot-collaboration in disassembly processes is equipping the robot system with higher autonomy and intelligence. In this paper, we present an informed software agent that controls the robot behavior to form an intelligent robot assistant for disassembly purposes. While the disassembly process first depends on the product structure, we inform the agent using a generic approach through product models. The product model is then transformed to a directed graph and used to build, share and define a coarse disassembly plan. To refine the workflow, we formulate “the problem of loosening a connection and the distribution of the work” as a search problem. The created detailed plan consists of a sequence of actions that are used to call, parametrize and execute robot programs for the fulfillment of the assistance. The aim of this research is to equip robot systems with knowledge and skills to allow them to be autonomous in the performance of their assistance to finally improve the ergonomics of disassembly workstations.

An Intelligent Agent based Architecture for Visual Data Mining

OpenAIRE

Hamdi Ellouzi; Hela Ltifi; Mounir Ben Ayed

2016-01-01

the aim of this paper is to present an intelligent architecture of Decision Support System (DSS) based on visual data mining. This architecture applies the multi-agent technology to facilitate the design and development of DSS in complex and dynamic environment. Multi-Agent Systems add a high level of abstraction. To validate the proposed architecture, it is implemented to develop a distributed visual data mining based DSS to predict nosocomial infectionsoccurrence in intensive care units. Th...

Designing Intelligent Tutoring Systems: A Personalization Strategy using Case-Based Reasoning and Multi-Agent Systems

Directory of Open Access Journals (Sweden)

Rosalía LAZA

2013-05-01

Full Text Available Intelligent Tutoring Systems (ITSs are educational systems that use artificial intelligence techniques for representing the knowledge. ITSs design is often criticized for being a complex and challenging process. In this article, we propose a framework for the ITSs design using Case Based Reasoning (CBR and Multiagent systems (MAS. The major advantage of using CBR is to allow the intelligent system to propose smart and quick solutions to problems, even in complex domains, avoiding the time necessary to derive those solutions from scratch. The use of intelligent agents and MAS architectures supports the retrieval of similar students models and the adaptation of teaching strategies according to the student profile. We describe deeply how the combination of both technologies helps to simplify the design of new ITSs and personalize the e-learning process for each student

A Framework For Agent-Based Educational Guidance And ...

African Journals Online (AJOL)

This work applies principles of artificial intelligence and agent development of educational guidance and counselling. An agent – based expert system is developed. The system supports the storage and intelligent interactive processing of the knowledge acquired by study and experience of the human expert in the domain ...

An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

OpenAIRE

Bo Sun; Qiang Feng; Songjie Li

2012-01-01

According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules) based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negoti...

[Artificial intelligence--the knowledge base applied to nephrology].

Science.gov (United States)

Sancipriano, G P

2005-01-01

The idea that efficacy efficiency, and quality in medicine could not be reached without sorting the huge knowledge of medical and nursing science is very common. Engineers and computer scientists have developed medical software with great prospects for success, but currently these software applications are not so useful in clinical practice. The medical doctor and the trained nurse live the 'information age' in many daily activities, but the main benefits are not so widespread in working activities. Artificial intelligence and, particularly, export systems charm health staff because of their potential. The first part of this paper summarizes the characteristics of 'weak artificial intelligence' and of expert systems important in clinical practice. The second part discusses medical doctors' requirements and the current nephrologic knowledge bases available for artificial intelligence development.

The highly intelligent virtual agents for modeling financial markets

Science.gov (United States)

Yang, G.; Chen, Y.; Huang, J. P.

2016-02-01

Researchers have borrowed many theories from statistical physics, like ensemble, Ising model, etc., to study complex adaptive systems through agent-based modeling. However, one fundamental difference between entities (such as spins) in physics and micro-units in complex adaptive systems is that the latter are usually with high intelligence, such as investors in financial markets. Although highly intelligent virtual agents are essential for agent-based modeling to play a full role in the study of complex adaptive systems, how to create such agents is still an open question. Hence, we propose three principles for designing high artificial intelligence in financial markets and then build a specific class of agents called iAgents based on these three principles. Finally, we evaluate the intelligence of iAgents through virtual index trading in two different stock markets. For comparison, we also include three other types of agents in this contest, namely, random traders, agents from the wealth game (modified on the famous minority game), and agents from an upgraded wealth game. As a result, iAgents perform the best, which gives a well support for the three principles. This work offers a general framework for the further development of agent-based modeling for various kinds of complex adaptive systems.

Cognitive Agents as a Design Metaphor in Environmental-Knowledge Management

Science.gov (United States)

Ceccaroni, Luigi; Simon-Cuevas, Alfredo; Rosete-Suárez, Alejandro; Moreno-Espino, Mailyn

Representing and sharing knowledge has been a central problem in artificial intelligence since its inception. Representations such as semantic networks, frames, concept maps and ontologies, as well as various methodologies for using these systems have been proposed for dealing with such issues. However, problems exist about issues such as communication among heterogeneous agents, incomplete or uncertain knowledge, imprecise formal-izations, and so on. Here, a mapping system between knowledge representations (concept maps and ontologies) is modeled using a methodology for the development of multi agent systems. Ontologies are formalized from non-formal concept maps and can then be used to represent agents knowledge, and to facilitate the communication among persons and software agents. A system is presented, in which a set of agents, implementing three functionalities (retrieval, disambiguation and formalization), collaborates in the process of knowledge management. This multi-agent system is part of a larger knowledge management system based on concept maps, and facilitates the use of generated and managed knowledge by not only people but also other software agents, namely those which require knowledge about domains that have been represented as concept maps, such as the environment domain, object of this book.

Logics for Intelligent Agents and Multi-Agent Systems

NARCIS (Netherlands)

Meyer, John-Jules Charles

2014-01-01

This chapter presents the history of the application of logic in a quite popular paradigm in contemporary computer science and artificial intelligence, viz. the area of intelligent agents and multi-agent systems. In particular we discuss the logics that have been used to specify single agents, the

The influence of active vision on the exoskeleton of intelligent agents

Science.gov (United States)

Smith, Patrice; Terry, Theodore B.

2016-04-01

Chameleonization occurs when a self-learning autonomous mobile system's (SLAMR) active vision scans the surface of which it is perched causing the exoskeleton to changes colors exhibiting a chameleon effect. Intelligent agents having the ability to adapt to their environment and exhibit key survivability characteristics of its environments would largely be due in part to the use of active vision. Active vision would allow the intelligent agent to scan its environment and adapt as needed in order to avoid detection. The SLAMR system would have an exoskeleton, which would change, based on the surface it was perched on; this is known as the "chameleon effect." Not in the common sense of the term, but from the techno-bio inspired meaning as addressed in our previous paper. Active vision, utilizing stereoscopic color sensing functionality would enable the intelligent agent to scan an object within its close proximity, determine the color scheme, and match it; allowing the agent to blend with its environment. Through the use of its' optical capabilities, the SLAMR system would be able to further determine its position, taking into account spatial and temporal correlation and spatial frequency content of neighboring structures further ensuring successful background blending. The complex visual tasks of identifying objects, using edge detection, image filtering, and feature extraction are essential for an intelligent agent to gain additional knowledge about its environmental surroundings.

Eighth International Conference on Intelligent Systems and Knowledge Engineering

CERN Document Server

Li, Tianrui; ISKE 2013; Foundations of Intelligent Systems; Knowledge Engineering and Management; Practical Applications of Intelligent Systems

2014-01-01

"Foundations of Intelligent Systems" presents selected papers from the 2013 International Conference on Intelligent Systems and Knowledge Engineering (ISKE2013). The aim of this conference is to bring together experts from different expertise areas to discuss the state-of-the-art in Intelligent Systems and Knowledge Engineering, and to present new research results and perspectives on future development. The topics in this volume include, but not limited to: Artificial Intelligence Theories, Pattern Recognition, Intelligent System Models, Speech Recognition, Computer Vision, Multi-Agent Systems, Machine Learning, Soft Computing and Fuzzy Systems, Biological Inspired Computation, Game Theory, Cognitive Systems and Information Processing, Computational Intelligence, etc. The proceedings are benefit for both researchers and practitioners who want to utilize intelligent methods in their specific research fields. Dr. Zhenkun Wen is a Professor at the College of Computer and Software Engineering, Shenzhen University...

Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

Science.gov (United States)

Fayyad, Usama M. (Editor); Uthurusamy, Ramasamy (Editor)

1993-01-01

The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

Towards an Intelligent Planning Knowledge Base Development Environment

Science.gov (United States)

Chien, S.

1994-01-01

ract describes work in developing knowledge base editing and debugging tools for the Multimission VICAR Planner (MVP) system. MVP uses artificial intelligence planning techniques to automatically construct executable complex image processing procedures (using models of the smaller constituent image processing requests made to the JPL Multimission Image Processing Laboratory.

A Secured Cognitive Agent based Multi-strategic Intelligent Search System

Directory of Open Access Journals (Sweden)

Neha Gulati

2018-04-01

Full Text Available Search Engine (SE is the most preferred information retrieval tool ubiquitously used. In spite of vast scale involvement of users in SE’s, their limited capabilities to understand the user/searcher context and emotions places high cognitive, perceptual and learning load on the user to maintain the search momentum. In this regard, the present work discusses a Cognitive Agent (CA based approach to support the user in Web-based search process. The work suggests a framework called Secured Cognitive Agent based Multi-strategic Intelligent Search System (CAbMsISS to assist the user in search process. It helps to reduce the contextual and emotional mismatch between the SE’s and user. After implementation of the proposed framework, performance analysis shows that CAbMsISS framework improves Query Retrieval Time (QRT and effectiveness for retrieving relevant results as compared to Present Search Engine (PSE. Supplementary to this, it also provides search suggestions when user accesses a resource previously tagged with negative emotions. Overall, the goal of the system is to enhance the search experience for keeping the user motivated. The framework provides suggestions through the search log that tracks the queries searched, resources accessed and emotions experienced during the search. The implemented framework also considers user security. Keywords: BDI model, Cognitive Agent, Emotion, Information retrieval, Intelligent search, Search Engine

Business Intelligence & Knowledge Management - Technological Support for Strategic Management in the Knowledge Based Economy

Directory of Open Access Journals (Sweden)

Dorel PARASCHIV

2008-01-01

Full Text Available The viability and success of modern enterprises are subject to the increasing dynamic of the economic environment, so they need to adjust rapidly their policies and strategies in order to respond to sophistication of competitors, customers and suppliers, globalization of business, international competition. Perhaps the most critical component for success of the modern enterprise is its ability to take advantage of all available information - both internal and external. Making sense of all this information, gaining value and competitive advantage through represents real challenges for the enterprise. The IT solutions designed to address these challenges have been developed in two different approaches: structured data management (Business Intelligence and unstructured content management (Knowledge Management. Integrating Business Intelligence and Knowledge Management in new software applications designated not only to store highly structured data and exploit it in real time but also to interpret the results and communicate them to decision factors provides real technological support for Strategic Management. Integrating Business Intelligence and Knowledge Management in order to respond to the challenges the modern enterprise has to deal with represents not only a "new trend" in IT, but a necessity in the emerging knowledge based economy. These hybrid technologies are already widely known in both scientific and practice communities as Competitive Intelligence. In the end of paper,a competitive datawarehouse design is proposed, in an attempt to apply business intelligence technologies to economic environment analysis making use of romanian public data sources.

Knowledge based systems for intelligent robotics

Science.gov (United States)

Rajaram, N. S.

1982-01-01

It is pointed out that the construction of large space platforms, such as space stations, has to be carried out in the outer space environment. As it is extremely expensive to support human workers in space for large periods, the only feasible solution appears to be related to the development and deployment of highly capable robots for most of the tasks. Robots for space applications will have to possess characteristics which are very different from those needed by robots in industry. The present investigation is concerned with the needs of space robotics and the technologies which can be of assistance to meet these needs, giving particular attention to knowledge bases. 'Intelligent' robots are required for the solution of arising problems. The collection of facts and rules needed for accomplishing such solutions form the 'knowledge base' of the system.

Behavioural domain knowledge transfer for autonomous agents

CSIR Research Space (South Africa)

Rosman, Benjamin S

2014-11-01

Full Text Available , and Behavior Transfer in Autonomous Robots, AAAI 2014 Fall Symposium Series, 13-15 November 2014 Behavioural Domain Knowledge Transfer for Autonomous Agents Benjamin Rosman Mobile Intelligent Autonomous Systems Modelling and Digital Science Council...

Education or Personality Traits and Intelligence as Determinants of Political Knowledge?

DEFF Research Database (Denmark)

Hebbelstrup Rye Rasmussen, Stig

2016-01-01

Recently the causal influence of education on political knowledge has been questioned. Rather, pre-adult predispositions such as personality traits and intelligence are proposed as the real causal agents. This article investigates in two studies whether education retains its explanatory power...... on political knowledge when personality traits and intelligence are taken into account. One study draws on a draftee sample and has excellent measures of both personality traits and intelligence; the other study draws on a representative sample and has excellent measures of personality traits. Openness...

Intelligent Agents in E-Commerce

OpenAIRE

Valentin LITOIU; Amelia BADICA; Cristian ETEGAN

2006-01-01

This paper emphasizes the importance of intelligent agents in e-commerce, with a particular focus on the B2C and B2B context. From the consumer buying behaviour perspective, agents can be used to assist the following stages: need identification, product brokering, buyer coalition formation, merchant brokering and negotiation. Related to B2B commerce, intelligent agents are involved in partnership formation, brokering and negotiation.

Knowledge base mechanisms

Energy Technology Data Exchange (ETDEWEB)

Suwa, M; Furukawa, K; Makinouchi, A; Mizoguchi, T; Mizoguchi, F; Yamasaki, H

1982-01-01

One of the principal goals of the Fifth Generation Computer System Project for the coming decade is to develop a methodology for building knowledge information processing systems which will provide people with intelligent agents. The key notion of the fifth generation computer system is knowledge used for problem solving. In this paper the authors describe the plan of Randd on knowledge base mechanisms. A knowledge representation system is to be designed to support knowledge acquisition for the knowledge information processing systems. The system will include a knowledge representation language, a knowledge base editor and a debugger. It is also expected to perform as a kind of meta-inference system. In order to develop the large scale knowledge base systems, a knowledge base mechanism based on the relational model is to be studied in the earlier stage of the project. Distributed problem solving is also one of the main issues of the project. 19 references.

A multi-agent approach to intelligent monitoring in smart grids

Science.gov (United States)

Vallejo, D.; Albusac, J.; Glez-Morcillo, C.; Castro-Schez, J. J.; Jiménez, L.

2014-04-01

In this paper, we propose a scalable multi-agent architecture to give support to smart grids, paying special attention to the intelligent monitoring of distribution substations. The data gathered by multiple sensors are used by software agents that are responsible for monitoring different aspects or events of interest, such as normal voltage values or unbalanced intensity values that can end up blowing fuses and decreasing the quality of service of end consumers. The knowledge bases of these agents have been built by means of a formal model for normality analysis that has been successfully used in other surveillance domains. The architecture facilitates the integration of new agents and can be easily configured and deployed to monitor different environments. The experiments have been conducted over a power distribution network.

MULTI AGENT-BASED ENVIRONMENTAL LANDSCAPE (MABEL) - AN ARTIFICIAL INTELLIGENCE SIMULATION MODEL: SOME EARLY ASSESSMENTS

OpenAIRE

Alexandridis, Konstantinos T.; Pijanowski, Bryan C.

2002-01-01

The Multi Agent-Based Environmental Landscape model (MABEL) introduces a Distributed Artificial Intelligence (DAI) systemic methodology, to simulate land use and transformation changes over time and space. Computational agents represent abstract relations among geographic, environmental, human and socio-economic variables, with respect to land transformation pattern changes. A multi-agent environment is developed providing task-nonspecific problem-solving abilities, flexibility on achieving g...

Intelligent Agents in E-Commerce

Directory of Open Access Journals (Sweden)

Valentin LITOIU

2006-01-01

Full Text Available This paper emphasizes the importance of intelligent agents in e-commerce, with a particular focus on the B2C and B2B context. From the consumer buying behaviour perspective, agents can be used to assist the following stages: need identification, product brokering, buyer coalition formation, merchant brokering and negotiation. Related to B2B commerce, intelligent agents are involved in partnership formation, brokering and negotiation.

AN INTELLIGENT CONVERSATION AGENT FOR HEALTH CARE DOMAIN

Directory of Open Access Journals (Sweden)

K. Karpagam

2014-04-01

Full Text Available Human Computer Interaction is one of the pervasive application areas of computer science to develop with multimodal interaction for information sharings. The conversation agent acts as the major core area for developing interfaces between a system and user with applied AI for proper responses. In this paper, the interactive system plays a vital role in improving knowledge in the domain of health through the intelligent interface between machine and human with text and speech. The primary aim is to enrich the knowledge and help the user in the domain of health using conversation agent to offer immediate response with human companion feel.

Raising agents: sources of human social intelligence

NARCIS (Netherlands)

Hofstede, G.J.

2014-01-01

This paper urges that if we wish to give social intelligence to our agents, it pays to look at how we acquired our social intelligence ourselves. Our drives and motives are innate and deeply social. Next, as children we are social-ized to acquire norms and values. This motivational and group-based

Flood AI: An Intelligent Systems for Discovery and Communication of Disaster Knowledge

Science.gov (United States)

Demir, I.; Sermet, M. Y.

2017-12-01

Communities are not immune from extreme events or natural disasters that can lead to large-scale consequences for the nation and public. Improving resilience to better prepare, plan, recover, and adapt to disasters is critical to reduce the impacts of extreme events. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This project presents an intelligent system, Flood AI, for flooding to improve societal preparedness by providing a knowledge engine using voice recognition, artificial intelligence, and natural language processing based on a generalized ontology for disasters with a primary focus on flooding. The knowledge engine utilizes the flood ontology and concepts to connect user input to relevant knowledge discovery channels on flooding by developing a data acquisition and processing framework utilizing environmental observations, forecast models, and knowledge bases. Communication channels of the framework includes web-based systems, agent-based chat bots, smartphone applications, automated web workflows, and smart home devices, opening the knowledge discovery for flooding to many unique use cases.

Increasing the Intelligence of Virtual Sales Assistants through Knowledge Modeling Techniques

OpenAIRE

Molina, Martin

2001-01-01

Shopping agents are web-based applications that help consumers to find appropriate products in the context of e-commerce. In this paper we argue about the utility of advanced model-based techniques that recently have been proposed in the fields of Artificial Intelligence and Knowledge Engineering, in order to increase the level of support provided by this type of applications. We illustrate this approach with a virtual sales assistant that dynamically configures a product according to the nee...

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

Science.gov (United States)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land

The achievement of spacecraft autonomy through the thematic application of multiple cooperating intelligent agents

Science.gov (United States)

Rossomando, Philip J.

1992-01-01

A description is given of UNICORN, a prototype system developed for the purpose of investigating artificial intelligence (AI) concepts supporting spacecraft autonomy. UNICORN employs thematic reasoning, of the type first described by Rodger Schank of Northwestern University, to allow the context-sensitive control of multiple intelligent agents within a blackboard based environment. In its domain of application, UNICORN demonstrates the ability to reason teleologically with focused knowledge. Also presented are some of the lessons learned as a result of this effort. These lessons apply to any effort wherein system level autonomy is the objective.

MamMoeT : An intelligent agent-based communication support platform for multimodal transport

NARCIS (Netherlands)

Dullaert, Wout; Neutens, Tijs; Vanden Berghe, Greet; Vermeulen, Tijs; Vernimmen, Bert; Witlox, Frank

In this paper, an intelligent agent-based communication support platform for multimodal transport is developed. The rationale for doing so is found in the potential of such a system to increase cost efficiency, service and safety for different transport-related actors. Although, at present several

Intelligent control and maintenance of management integrated system based on multi-agents for coal preparation plant

Energy Technology Data Exchange (ETDEWEB)

Meng, F.; Wang, Y. [China University of Mining and technology, Xuzhou (China). School of Information and Electrical Engineering

2006-06-15

This paper discusses the progress of computer integrated processing (CIPS) of coal preparation and then presents an intelligence controlled production process, device-maintenance and production-management system of coal preparation based on multi-agents (IICMMS-CP). The construction of the IICMMS-CP, the distributed network control system based on live intelligence control stations and the strategy of implementing a distributed intelligence control system are studied in order to overcome the disadvantages brought about by the wide use of the PLC system by coal preparation plants. The software frame, based on a Multi-Agent Intelligence Control and Maintenance Management integrated system, is studied and the implementation methods of IICMMS-CP are discussed. The characteristics of distributed architecture, cooperation and parallel computing meet the needs of integrated control of coal preparation plants with large-scale spatial production distribution, densely-related processes and complex systems. Its application further improves the reliability and precision of process control, accuracy of fault identification and intelligence of production adjustment, establishes a technical basis for system integration and flexible production. The main function of the system has been tested in a coal preparation plant to good effect in stabilizing product quality, improving efficiency and reducing consumption. 17 refs., 4 figs.

An Emotional Agent Model Based on Granular Computing

Directory of Open Access Journals (Sweden)

Jun Hu

2012-01-01

Full Text Available Affective computing has a very important significance for fulfilling intelligent information processing and harmonious communication between human being and computers. A new model for emotional agent is proposed in this paper to make agent have the ability of handling emotions, based on the granular computing theory and the traditional BDI agent model. Firstly, a new emotion knowledge base based on granular computing for emotion expression is presented in the model. Secondly, a new emotional reasoning algorithm based on granular computing is proposed. Thirdly, a new emotional agent model based on granular computing is presented. Finally, based on the model, an emotional agent for patient assistant in hospital is realized, experiment results show that it is efficient to handle simple emotions.

An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

Directory of Open Access Journals (Sweden)

Bo Sun

2012-01-01

Full Text Available According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negotiation and independent negotiation is established, and the heuristic rules applied to global and local maintenance decision making is proposed. Based on Contract Net Protocol and the heuristic rules, the maintenance decision making algorithm is put forward. Finally, a fleet consisting of 10 aircrafts on a 3-wave continuous mission is illustrated to verify this method. Simulation results indicate that this method can improve the availability of the fleet, meet mission demands, rationalize the utilization of support resources and provide support for online maintenance decision making among a mission oriented fleet.

Distributed, cooperating knowledge-based systems

Science.gov (United States)

Truszkowski, Walt

1991-01-01

Some current research in the development and application of distributed, cooperating knowledge-based systems technology is addressed. The focus of the current research is the spacecraft ground operations environment. The underlying hypothesis is that, because of the increasing size, complexity, and cost of planned systems, conventional procedural approaches to the architecture of automated systems will give way to a more comprehensive knowledge-based approach. A hallmark of these future systems will be the integration of multiple knowledge-based agents which understand the operational goals of the system and cooperate with each other and the humans in the loop to attain the goals. The current work includes the development of a reference model for knowledge-base management, the development of a formal model of cooperating knowledge-based agents, the use of testbed for prototyping and evaluating various knowledge-based concepts, and beginning work on the establishment of an object-oriented model of an intelligent end-to-end (spacecraft to user) system. An introductory discussion of these activities is presented, the major concepts and principles being investigated are highlighted, and their potential use in other application domains is indicated.

MAINS: MULTI-AGENT INTELLIGENT SERVICE ARCHITECTURE FOR CLOUD COMPUTING

Directory of Open Access Journals (Sweden)

T. Joshva Devadas

2014-04-01

Full Text Available Computing has been transformed to a model having commoditized services. These services are modeled similar to the utility services water and electricity. The Internet has been stunningly successful over the course of past three decades in supporting multitude of distributed applications and a wide variety of network technologies. However, its popularity has become the biggest impediment to its further growth with the handheld devices mobile and laptops. Agents are intelligent software system that works on behalf of others. Agents are incorporated in many innovative applications in order to improve the performance of the system. Agent uses its possessed knowledge to react with the system and helps to improve the performance. Agents are introduced in the cloud computing is to minimize the response time when similar request is raised from an end user in the globe. In this paper, we have introduced a Multi Agent Intelligent system (MAINS prior to cloud service models and it was tested using sample dataset. Performance of the MAINS layer was analyzed in three aspects and the outcome of the analysis proves that MAINS Layer provides a flexible model to create cloud applications and deploying them in variety of applications.

Towards a Calendar Agent Society with Intelligent Agents in ASP-Updates

Directory of Open Access Journals (Sweden)

Marco A. Ramos C.

2012-03-01

Full Text Available Se presenta el análisis y algunas especificaciones para describir una sociedad multi-agente que representa agendas dinámicas en Answer Sets Programming, por medio de actualización de bases de conocimiento. Se trata de un estudio de caso para representar un grupo de agentes BD Iinteligentes con el fin común de programar una reunión, y se utiliza un ejemplo para mostrar la manera de distribuir y cambiar sus especificaciones bajo circunstancias imprevistas, así como un protocolo sencillo para realizar una reunión consensual. Sostenemos que el marco propuesto es apropiado para tener los beneficios de una base sólida como Answer Sets Programming, de la simplicidad de su programación lógica declarativa, así como de la practicidad para resolvedores existentes implementados, que pueden ser utilizados para un sistema más completo y útil de sociedades de agentes.We present the analysis and some preliminary specifications to describe a multi-agent society to represent dynamic appointments under in Answer-Sets Programming, by means of knowledge-base updates. This is a case study to represent a group of intelligent BDI agents with a common goal of scheduling a meeting, and we use an example to show how to distribute and change their specifications under unforeseen circumstances, as well as a simple protocol to realise a consensual meeting. We claim that the proposed framework is appropriate to have the benefits from a strong foundation like Answer-Sets Programming, simplicity for its declarative logic programming, as well as practicality for existent implemented solvers, which can be used to implement a more-complete and useful system of agent societies.

A Multi-Agent Architecture for an Intelligent Website in Insurance

NARCIS (Netherlands)

Jonker, C.M.; Lam, R.A.; Treur, J.

1999-01-01

In this paper a multi-agent architecture for intelligent Websites is presented and applied in insurance. The architecture has been designed and implemented using the compositional development method for multi-agent systems DESIRE. The agents within this architecture are based on a generic broker

Computational Intelligence Agent-Oriented Modelling

Czech Academy of Sciences Publication Activity Database

Neruda, Roman

2006-01-01

Roč. 5, č. 2 (2006), s. 430-433 ISSN 1109-2777 R&D Projects: GA MŠk 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : multi-agent systems * adaptive agents * computational intelligence Subject RIV: IN - Informatics, Computer Science

Recent progress in competitive intelligence, competitive technical intelligence and knowledge management

Directory of Open Access Journals (Sweden)

Dou Henri

2011-04-01

Full Text Available This paper discusses the role of competitive intelligence and knowledge management to create, maintain and sustain competitive advantages. The triple helix model, based on the integration of the public sector (government, business models (private corporations and universities to promote innovation is examined. Research trends in competitive intelligence are presented. It concludes that the systematic use of the technology monitoring should support the comparison between various business models of companies that hold the market best practices and form a basis to knowledge for the decision making process and strategies development.

Artificial intelligence in process control: Knowledge base for the shuttle ECS model

Science.gov (United States)

Stiffler, A. Kent

1989-01-01

The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

Amine : une plate-forme pour le développement de systèmes et d’agents intelligents

Directory of Open Access Journals (Sweden)

Karim Bouzoubaa

2005-10-01

Full Text Available This paper presents an overview of Amine ; a multi-layer and open-source platform, implemented in Java and dedicated to the development of intelligent systems and agents. Amine is composed of four layers : a a kernel layer that enables the creation, edition, update and manipulation of multi-lingua ontologies, b an algebraic layer that offers a set of elementary data types, structured types and various matching-based operations, c a programming layer that provides three programming paradigms: i an ontology or memory-based programming paradigm which is concerned by incremental and automatic integration of knowledge in an ontology (or agent memory, ii a pattern-matching and rule-based programming paradigm, embedded in PROLOG+CG language, and iii an activation and propagation-based programming paradigm, embedded in SYNERGY language, and d an agent and multi-agent systems layer that enables the development of agent-based applications.

Knowledge Management in Role Based Agents

Science.gov (United States)

Kır, Hüseyin; Ekinci, Erdem Eser; Dikenelli, Oguz

In multi-agent system literature, the role concept is getting increasingly researched to provide an abstraction to scope beliefs, norms, goals of agents and to shape relationships of the agents in the organization. In this research, we propose a knowledgebase architecture to increase applicability of roles in MAS domain by drawing inspiration from the self concept in the role theory of sociology. The proposed knowledgebase architecture has granulated structure that is dynamically organized according to the agent's identification in a social environment. Thanks to this dynamic structure, agents are enabled to work on consistent knowledge in spite of inevitable conflicts between roles and the agent. The knowledgebase architecture is also implemented and incorporated into the SEAGENT multi-agent system development framework.

Knowledge-based dialogue in Intelligent Decision Support Systems

International Nuclear Information System (INIS)

Hollnagel, E.

1987-01-01

The overall goal for the design of Intelligent Decision Support Systems (IDSS) is to enhance understanding of the process under all operating conditions. For an IDSS to be effective, it must: select or generate the right information; produce reliable and consistent information; allow flexible and effective operator interaction; relate information presentation to current plant status and problems; and make the presentation at the right time. Several ongoing R and D programs try to design and build IDSSs. A particular example is the ESPRIT project Graphics and Knowledge Based Diaglogue for Dynamic Systems (GRADIENT). This project, the problems it addresses, and its uses, are discussed here

An intelligent knowledge-based and customizable home care system framework with ubiquitous patient monitoring and alerting techniques.

Science.gov (United States)

Chen, Yen-Lin; Chiang, Hsin-Han; Yu, Chao-Wei; Chiang, Chuan-Yen; Liu, Chuan-Ming; Wang, Jenq-Haur

2012-01-01

This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

An Intelligent Knowledge-Based and Customizable Home Care System Framework with Ubiquitous Patient Monitoring and Alerting Techniques

Directory of Open Access Journals (Sweden)

Yen-Lin Chen

2012-08-01

Full Text Available This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

Agent Based Knowledge Management Solution using Ontology, Semantic Web Services and GIS

Directory of Open Access Journals (Sweden)

Andreea DIOSTEANU

2009-01-01

Full Text Available The purpose of our research is to develop an agent based knowledge management application framework using a specific type of ontology that is able to facilitate semantic web service search and automatic composition. This solution can later on be used to develop complex solutions for location based services, supply chain management, etc. This application for modeling knowledge highlights the importance of agent interaction that leads to efficient enterprise interoperability. Furthermore, it proposes an "agent communication language" ontology that extends the OWL Lite standard approach and makes it more flexible in retrieving proper data for identifying the agents that can best communicate and negotiate.

8th International Symposium on Intelligent Distributed Computing & Workshop on Cyber Security and Resilience of Large-Scale Systems & 6th International Workshop on Multi-Agent Systems Technology and Semantics

CERN Document Server

Braubach, Lars; Venticinque, Salvatore; Badica, Costin

2015-01-01

This book represents the combined peer-reviewed proceedings of the Eight International Symposium on Intelligent Distributed Computing - IDC'2014, of the Workshop on Cyber Security and Resilience of Large-Scale Systems - WSRL-2014, and of the Sixth International Workshop on Multi-Agent Systems Technology and Semantics- MASTS-2014. All the events were held in Madrid, Spain, during September 3-5, 2014. The 47 contributions published in this book address several topics related to theory and applications of the intelligent distributed computing and multi-agent systems, including: agent-based data processing, ambient intelligence, collaborative systems, cryptography and security, distributed algorithms, grid and cloud computing, information extraction, knowledge management, big data and ontologies, social networks, swarm intelligence or videogames amongst others.

Construction of Intelligence Knowledge Map for Complex Product Development

Directory of Open Access Journals (Sweden)

Yan-jie LV,

2013-11-01

Full Text Available The complex product design and development is an integrated discipline. A lot of knowledge overloads and knowledge trek phenomenon appeared with the raise of product complexity and the explosion of knowledge and information. To improve the utilization efficiency of the knowledge using and shorten the time and effort spent on the Knowledge screening, avoid missing the knowledge, which is required, the paper proposes a method for the intelligence knowledge map construct model based on knowledge requirements and knowledge connection. Analyzing the context information of the user and giving the method of acquiring the knowledge requirement based on the context information and the user’s personal knowledge structure. This method can get the knowledge requirements of the users to generate the knowledge retrieval expressions to obtain the knowledge points and then construct the intelligent knowledge map through the analysis of multiple dimensions and using the knowledge related to the development of aircraft landing gear as an example to verify the feasibility of this method.

An intelligent agent for optimal river-reservoir system management

Science.gov (United States)

Rieker, Jeffrey D.; Labadie, John W.

2012-09-01

A generalized software package is presented for developing an intelligent agent for stochastic optimization of complex river-reservoir system management and operations. Reinforcement learning is an approach to artificial intelligence for developing a decision-making agent that learns the best operational policies without the need for explicit probabilistic models of hydrologic system behavior. The agent learns these strategies experientially in a Markov decision process through observational interaction with the environment and simulation of the river-reservoir system using well-calibrated models. The graphical user interface for the reinforcement learning process controller includes numerous learning method options and dynamic displays for visualizing the adaptive behavior of the agent. As a case study, the generalized reinforcement learning software is applied to developing an intelligent agent for optimal management of water stored in the Truckee river-reservoir system of California and Nevada for the purpose of streamflow augmentation for water quality enhancement. The intelligent agent successfully learns long-term reservoir operational policies that specifically focus on mitigating water temperature extremes during persistent drought periods that jeopardize the survival of threatened and endangered fish species.

Competing intelligent search agents in global optimization

Energy Technology Data Exchange (ETDEWEB)

Streltsov, S.; Vakili, P. [Boston Univ., MA (United States); Muchnik, I. [Rutgers Univ., Piscataway, NJ (United States)

1996-12-31

In this paper we present a new search methodology that we view as a development of intelligent agent approach to the analysis of complex system. The main idea is to consider search process as a competition mechanism between concurrent adaptive intelligent agents. Agents cooperate in achieving a common search goal and at the same time compete with each other for computational resources. We propose a statistical selection approach to resource allocation between agents that leads to simple and efficient on average index allocation policies. We use global optimization as the most general setting that encompasses many types of search problems, and show how proposed selection policies can be used to improve and combine various global optimization methods.

A Note on Systems Intelligence in Knowledge Management

Science.gov (United States)

Sasaki, Yasuo

2017-01-01

Purpose: This paper aims to show that systems intelligence (SI) can be a useful perspective in knowledge management, particularly in the context of the socialization, externalization, combination and internalization (SECI) model. SI is a recently developed systemic concept, a certain kind of human intelligence based on a systems thinking…

Games and Agents: Designing Intelligent Gameplay

Directory of Open Access Journals (Sweden)

F. Dignum

2009-01-01

Full Text Available There is an attention shift within the gaming industry toward more natural (long-term behavior of nonplaying characters (NPCs. Multiagent system research offers a promising technology to implement cognitive intelligent NPCs. However, the technologies used in game engines and multiagent platforms are not readily compatible due to some inherent differences of concerns. Where game engines focus on real-time aspects and thus propagate efficiency and central control, multiagent platforms assume autonomy of the agents. Increased autonomy and intelligence may offer benefits for a more compelling gameplay and may even be necessary for serious games. However, it raises problems when current game design techniques are used to incorporate state-of-the-art multiagent system technology. In this paper, we will focus on three specific problem areas that arise from this difference of view: synchronization, information representation, and communication. We argue that the current attempts for integration still fall short on some of these aspects. We show that to fully integrate intelligent agents in games, one should not only use a technical solution, but also a design methodology that is amenable to agents. The game design should be adjusted to incorporate the possibilities of agents early on in the process.

GRASP agents: social first, intelligent later

NARCIS (Netherlands)

Hofstede, G.J.

2017-01-01

This paper urges that if we wish to give social intelligence to our agents, it pays to look at how we acquired our social intelligence ourselves. We are born with drives and motives that are innate and deeply social. Next, as children we are socialized to acquire norms and values and to understand

Intelligent agents for training on-board fire fighting

NARCIS (Netherlands)

Bosch, K. van den; Harbers, M.; Heuvelink, A.; Doesburg, W. van

2009-01-01

Simulation-based training in complex decision making often requires ample personnel for playing various roles (e.g. team mates, adversaries). Using intelligent agents may diminish the need for staff. However, to achieve goal-directed training, events in the simulation as well as the behavior of key

What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated.

Science.gov (United States)

Kumaran, Dharshan; Hassabis, Demis; McClelland, James L

2016-07-01

We update complementary learning systems (CLS) theory, which holds that intelligent agents must possess two learning systems, instantiated in mammalians in neocortex and hippocampus. The first gradually acquires structured knowledge representations while the second quickly learns the specifics of individual experiences. We broaden the role of replay of hippocampal memories in the theory, noting that replay allows goal-dependent weighting of experience statistics. We also address recent challenges to the theory and extend it by showing that recurrent activation of hippocampal traces can support some forms of generalization and that neocortical learning can be rapid for information that is consistent with known structure. Finally, we note the relevance of the theory to the design of artificial intelligent agents, highlighting connections between neuroscience and machine learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Multi-Agent-Based Intelligent Sensor and Actuator Network Design for Smart House and Home Automation

Directory of Open Access Journals (Sweden)

Fei Hu

2013-08-01

Full Text Available The smart-house technology aims to increase home automation and security with reduced energy consumption. A smart house consists of various intelligent sensors and actuators operating on different platforms with conflicting objectives. This paper proposes a multi-agent system (MAS design framework to achieve smart house automation. The novelties of this work include the developments of (1 belief, desire and intention (BDI agent behavior models; (2 a regulation policy-based multi-agent collaboration mechanism; and (3 a set of metrics for MAS performance evaluation. Simulations of case studies are performed using the Java Agent Development Environment (JADE to demonstrate the advantages of the proposed method.

7th International Symposium on Intelligent Distributed Computing

CERN Document Server

Jung, Jason; Badica, Costin

2014-01-01

This book represents the combined peer-reviewed proceedings of the Seventh International Symposium on Intelligent Distributed Computing - IDC-2013, of the Second Workshop on Agents for Clouds - A4C-2013, of the Fifth International Workshop on Multi-Agent Systems Technology and Semantics - MASTS-2013, and of the International Workshop on Intelligent Robots - iR-2013. All the events were held in Prague, Czech Republic during September 4-6, 2013. The 41 contributions published in this book address many topics related to theory and applications of intelligent distributed computing and multi-agent systems, including: agent-based data processing, ambient intelligence, bio-informatics, collaborative systems, cryptography and security, distributed algorithms, grid and cloud computing, information extraction, intelligent robotics, knowledge management, linked data, mobile agents, ontologies, pervasive computing, self-organizing systems, peer-to-peer computing, social networks and trust, and swarm intelligence.  .

Challenging problems and solutions in intelligent systems

CERN Document Server

Grzegorzewski, Przemysław; Kacprzyk, Janusz; Owsiński, Jan; Penczek, Wojciech; Zadrożny, Sławomir

2016-01-01

This volume presents recent research, challenging problems and solutions in Intelligent Systems– covering the following disciplines: artificial and computational intelligence, fuzzy logic and other non-classic logics, intelligent database systems, information retrieval, information fusion, intelligent search (engines), data mining, cluster analysis, unsupervised learning, machine learning, intelligent data analysis, (group) decision support systems, intelligent agents and multi-agent systems, knowledge-based systems, imprecision and uncertainty handling, electronic commerce, distributed systems, etc. The book defines a common ground for sometimes seemingly disparate problems and addresses them by using the paradigm of broadly perceived intelligent systems. It presents a broad panorama of a multitude of theoretical and practical problems which have been successfully dealt with using the paradigm of intelligent computing.

Agent-Based Model of Information Security System: Architecture and Formal Framework for Coordinated Intelligent Agents Behavior Specification

National Research Council Canada - National Science Library

Gorodetski, Vladimir

2001-01-01

The contractor will research and further develop the technology supporting an agent-based architecture for an information security system and a formal framework to specify a model of distributed knowledge...

An agent-based legal knowledge acquisition methodology for agile public administration

NARCIS (Netherlands)

Boer, A.; van Engers, T.

2011-01-01

This paper proposes a knowledge elicitation method based on serious gaming for theory construction about the effects of the law on the behaviours of agents. These games provide input to simulations of business process and product design alternatives. For knowledge representation, we have combined

Fatigue distribution optimization for offshore wind farms using intelligent agent control

DEFF Research Database (Denmark)

Zhao, Rongyong; Shen, Wen Zhong; Knudsen, Torben

2012-01-01

with its neighbouring downwind turbines and organizes them adaptively into a wind delivery group along the wind direction. The agent attributes and the event structure are designed on the basis of the intelligent agent theory by using the unified modelling language. The control strategy of the intelligent......A novel control approach is proposed to optimize the fatigue distribution of wind turbines in a large‐scale offshore wind farm on the basis of an intelligent agent theory. In this approach, each wind turbine is considered to be an intelligent agent. The turbine at the farm boundary communicates...... coefficient for every wind turbine. The optimization is constrained such that the average fatigue for every turbine is smaller than what would be achieved by conventional dispatch and such that the total power loss of the wind farm is restricted to a few percent of the total power. This intelligent agent...

A development framework for distributed artificial intelligence

Science.gov (United States)

Adler, Richard M.; Cottman, Bruce H.

1989-01-01

The authors describe distributed artificial intelligence (DAI) applications in which multiple organizations of agents solve multiple domain problems. They then describe work in progress on a DAI system development environment, called SOCIAL, which consists of three primary language-based components. The Knowledge Object Language defines models of knowledge representation and reasoning. The metaCourier language supplies the underlying functionality for interprocess communication and control access across heterogeneous computing environments. The metaAgents language defines models for agent organization coordination, control, and resource management. Application agents and agent organizations will be constructed by combining metaAgents and metaCourier building blocks with task-specific functionality such as diagnostic or planning reasoning. This architecture hides implementation details of communications, control, and integration in distributed processing environments, enabling application developers to concentrate on the design and functionality of the intelligent agents and agent networks themselves.

10th KES Conference on Agent and Multi-Agent Systems : Technologies and Applications

CERN Document Server

Chen-Burger, Yun-Heh; Howlett, Robert; Jain, Lakhmi

2016-01-01

The modern economy is driven by technologies and knowledge. Digital technologies can free, shift and multiply choices, often intruding on the space of other industries, by providing new ways of conducting business operations and creating values for customers and companies. The topics covered in this volume include software agents, multi-agent systems, agent modelling, mobile and cloud computing, big data analysis, business intelligence, artificial intelligence, social systems, computer embedded systems and nature inspired manufacturing, etc. that contribute to the modern Digital Economy. This volume highlights new trends and challenges in agent, new digital and knowledge economy research and includes 28 papers classified in the following specific topics: business process management, agent-based modeling and simulation, anthropic-oriented computing, learning paradigms, business informatics and gaming, digital economy, and advances in networked virtual enterprises. Published papers were selected for presentatio...

iMuseumA: An Agent-Based Context-Aware Intelligent Museum System

Directory of Open Access Journals (Sweden)

Inmaculada Ayala

2014-11-01

Full Text Available Currently, museums provide their visitors with interactive tour guide applications that can be installed in mobile devices and provide timely tailor-made multimedia information about exhibits on display. In this paper, we argue that mobile devices not only could provide help to visitors, but also to museum staff. Our goal is to integrate, within the same system, multimedia tour guides with the management facilities required by museums. In this paper, we present iMuseumA (intelligent museum with agents, a mobile-based solution to customize visits and perform context-aware management tasks. iMuseumA follows an agent-based approach, which makes it possible to interact easily with the museum environment and make decisions based on its current status. This system is currently deployed in the Museum of Informatics at the Informatics School of the University of Málaga, and its main contributions are: (i a mobile application that provides management facilities to museum staff by means of sensing and processing environmental data; (ii providing an integrated solution for visitors, tour guides and museum staff that allows coordination and communication enrichment among different groups of users; (iii using and benefiting from group communication for heterogeneous groups of users that can be created on demand.

The structure of intelligent agent projecting and the possibilities of its execution

Directory of Open Access Journals (Sweden)

Yefremov M.F.

2017-04-01

Full Text Available Most of today’s information systems are not designed for independent decision making, behavior of such systems should be incorporated at the design stage. Entering the conditions that are not included by system developers, lead to a crash. The exponential growth of computing power of modern processors leads to an increase in range of tasks that can be automated, and an increase in their complexity. Partially testing helps to solve the problem, but it has a drawback, precisely the behavior of the system is usually tested in conditions which are already taken into account at the design stage. One approach to address this problem is the agent-oriented programming and the use of multi-agent systems. The aim of the work is to highlight contemporary approaches: a definition of agent concepts, applications of multi-agent systems, mathematical model agent, modern methods of design and implementation of intelligent agents, also covered approaches to the definition of the concept of an intelligent agent, the application of intelligent agents and multi-agent systems, and methods theoretically agent and describe its implementation. The basis of these methods of abstract description of the intelligent agent is the works of M.Wooldridge and N.Jennings. We propose several methods to describe such behaviors of intelligent agent as self-learning, goal setting and forecasting, and planning. Therefore we cover the concept of «intent» and widespread mental (beliefs-desires-intentions BDI architecture of intelligent agent, as well as the proposed methods of their description in the framework of the developed formalism.

10th International Symposium on Intelligent Distributed Computing

CERN Document Server

Seghrouchni, Amal; Beynier, Aurélie; Camacho, David; Herpson, Cédric; Hindriks, Koen; Novais, Paulo

2017-01-01

This book presents the combined peer-reviewed proceedings of the tenth International Symposium on Intelligent Distributed Computing (IDC’2016), which was held in Paris, France from October 10th to 12th, 2016. The 23 contributions address a range of topics related to theory and application of intelligent distributed computing, including: Intelligent Distributed Agent-Based Systems, Ambient Intelligence and Social Networks, Computational Sustainability, Intelligent Distributed Knowledge Representation and Processing, Smart Networks, Networked Intelligence and Intelligent Distributed Applications, amongst others.

Dynamical Intention: Integrated Intelligence Modeling for Goal-directed Embodied Agents

Directory of Open Access Journals (Sweden)

Eric Aaron

2016-11-01

Full Text Available Intelligent embodied robots are integrated systems: As they move continuously through their environments, executing behaviors and carrying out tasks, components for low-level and high-level intelligence are integrated in the robot's cognitive system, and cognitive and physical processes combine to create their behavior. For a modeling framework to enable the design and analysis of such integrated intelligence, the underlying representations in the design of the robot should be dynamically sensitive, capable of reflecting both continuous motion and micro-cognitive influences, while also directly representing the necessary beliefs and intentions for goal-directed behavior. In this paper, a dynamical intention-based modeling framework is presented that satisfies these criteria, along with a hybrid dynamical cognitive agent (HDCA framework for employing dynamical intentions in embodied agents. This dynamical intention-HDCA (DI-HDCA modeling framework is a fusion of concepts from spreading activation networks, hybrid dynamical system models, and the BDI (belief-desire-intention theory of goal-directed reasoning, adapted and employed unconventionally to meet entailments of environment and embodiment. The paper presents two kinds of autonomous agent learning results that demonstrate dynamical intentions and the multi-faceted integration they enable in embodied robots: with a simulated service robot in a grid-world office environment, reactive-level learning minimizes reliance on deliberative-level intelligence, enabling task sequencing and action selection to be distributed over both deliberative and reactive levels; and with a simulated game of Tag, the cognitive-physical integration of an autonomous agent enables the straightforward learning of a user-specified strategy during gameplay, without interruption to the game. In addition, the paper argues that dynamical intentions are consistent with cognitive theory underlying goal-directed behavior, and

Modelling of robotic work cells using agent based-approach

Science.gov (United States)

Sękala, A.; Banaś, W.; Gwiazda, A.; Monica, Z.; Kost, G.; Hryniewicz, P.

2016-08-01

In the case of modern manufacturing systems the requirements, both according the scope and according characteristics of technical procedures are dynamically changing. This results in production system organization inability to keep up with changes in a market demand. Accordingly, there is a need for new design methods, characterized, on the one hand with a high efficiency and on the other with the adequate level of the generated organizational solutions. One of the tools that could be used for this purpose is the concept of agent systems. These systems are the tools of artificial intelligence. They allow assigning to agents the proper domains of procedures and knowledge so that they represent in a self-organizing system of an agent environment, components of a real system. The agent-based system for modelling robotic work cell should be designed taking into consideration many limitations considered with the characteristic of this production unit. It is possible to distinguish some grouped of structural components that constitute such a system. This confirms the structural complexity of a work cell as a specific production system. So it is necessary to develop agents depicting various aspects of the work cell structure. The main groups of agents that are used to model a robotic work cell should at least include next pattern representatives: machine tool agents, auxiliary equipment agents, robots agents, transport equipment agents, organizational agents as well as data and knowledge bases agents. In this way it is possible to create the holarchy of the agent-based system.

Modeling and simulating human teamwork behaviors using intelligent agents

Science.gov (United States)

Fan, Xiaocong; Yen, John

2004-12-01

Among researchers in multi-agent systems there has been growing interest in using intelligent agents to model and simulate human teamwork behaviors. Teamwork modeling is important for training humans in gaining collaborative skills, for supporting humans in making critical decisions by proactively gathering, fusing, and sharing information, and for building coherent teams with both humans and agents working effectively on intelligence-intensive problems. Teamwork modeling is also challenging because the research has spanned diverse disciplines from business management to cognitive science, human discourse, and distributed artificial intelligence. This article presents an extensive, but not exhaustive, list of work in the field, where the taxonomy is organized along two main dimensions: team social structure and social behaviors. Along the dimension of social structure, we consider agent-only teams and mixed human-agent teams. Along the dimension of social behaviors, we consider collaborative behaviors, communicative behaviors, helping behaviors, and the underpinning of effective teamwork-shared mental models. The contribution of this article is that it presents an organizational framework for analyzing a variety of teamwork simulation systems and for further studying simulated teamwork behaviors.

Current trends on knowledge-based systems

CERN Document Server

Valencia-García, Rafael

2017-01-01

This book presents innovative and high-quality research on the implementation of conceptual frameworks, strategies, techniques, methodologies, informatics platforms and models for developing advanced knowledge-based systems and their application in different fields, including Agriculture, Education, Automotive, Electrical Industry, Business Services, Food Manufacturing, Energy Services, Medicine and others. Knowledge-based technologies employ artificial intelligence methods to heuristically address problems that cannot be solved by means of formal techniques. These technologies draw on standard and novel approaches from various disciplines within Computer Science, including Knowledge Engineering, Natural Language Processing, Decision Support Systems, Artificial Intelligence, Databases, Software Engineering, etc. As a combination of different fields of Artificial Intelligence, the area of Knowledge-Based Systems applies knowledge representation, case-based reasoning, neural networks, Semantic Web and TICs used...

GROWTH OF COLLECTIVE INTELLIGENCE BY LINKING KNOWLEDGE WORKERS THROUGH SOCIAL MEDIA

Directory of Open Access Journals (Sweden)

JAROSLAVA KUBÁTOVÁ

2012-05-01

Full Text Available Collective intelligence can be defined, very broadly, as groups of individuals that do things collectively, and that seem to be intelligent. Collective intelligence has existed for ages. Families, tribes, companies, countries, etc., are all groups of individuals doing things collectively, and that seem to be intelligent. However, over the past two decades, the rise of the Internet has given upturn to new types of collective intelligence. Companies can take advantage from the so-called Web-enabled collective intelligence. Web-enabled collective intelligence is based on linking knowledge workers through social media. That means that companies can hire geographically dispersed knowledge workers and create so-called virtual teams of these knowledge workers (members of the virtual teams are connected only via the Internet and do not meet face to face. By providing an online social network, the companies can achieve significant growth of collective intelligence. But to create and use an online social network within a company in a really efficient way, the managers need to have a deep understanding of how such a system works. Thus the purpose of this paper is to share the knowledge about effective use of social networks in companies. The main objectives of this paper are as follows: to introduce some good practices of the use of social media in companies, to analyze these practices and to generalize recommendations for a successful introduction and use of social media to increase collective intelligence of a company.

Intelligent agents for e-commerce applications

Science.gov (United States)

Vuppala, Krishna

1999-12-01

This thesis focuses on development of intelligent agent solutions for e-commerce applications. E-Commerce has several complexities like: lack of information about the players, learning the nature of one's business partners/competitors, finding the right business partner to do business with, using the right strategy to get best profit out of the negotiations etc. The agent models developed can be used in any agent solution for e-commerce. Concepts and techniques from Game Theory and Artificial Intelligence are used. The developed models have several advantages over the existing ones as: the models assume the non-availability of information about other players in the market, the models of players get updated over the time as and when new information comes about the players, the negotiation model incorporates the patience levels of the players and expectations from other players in the market. Power industry has been chosen as the application area for the demonstration of the capabilities and usage of the developed agent models. Two e-commerce scenarios where sellers and buyers can go through the power exchanges to bid in auctions, or make bilateral deals outside of the exchange are addressed. In the first scenario agent helps market participants in coordinating strategies with other participants, bidding in auctions by analyzing and understanding the behavior of other participants. In the second scenario, called "Power Traders Assistant" agent helps power trader, who buys and sells power through bilateral negotiations, in negotiating deals with his customers.

A Multi-Agent Framework for Coordination of Intelligent Assistive Technologies

DEFF Research Database (Denmark)

Valente, Pedro Ricardo da Nova; Hossain, S.; Groenbaek, B.

2010-01-01

Intelligent care for the future is the IntelliCare project's main priority. This paper describes the design of a generic multi-agent framework for coordination of intelligent assistive technologies. The paper overviews technologies and software systems suitable for context awareness...... and housekeeping tasks, especially for performing a multi-robot cleaning-task activity. It also describes conducted work in the design of a multi-agent platform for coordination of intelligent assistive technologies. Instead of using traditional robot odometry estimation methods, we have tested an independent...

ANALYSIS AND CONCEPTION DEVELOPMENT OF INFORMATION DEFENSE CID AND CLOUD PLATFORM ON THE BASE OF INTELLIGENCE TECHNOLOGIES

Directory of Open Access Journals (Sweden)

V. A. Vishniakov

2014-01-01

Full Text Available Two problems the use of intelligence technologies in information defense (ITID – creating specialized knowledge bases with threats simulation and high the security level in corporative nets and cloud computing are presented. The analysis of t wo directions of the second ITID problem: the intelligence decision support systems and the malt y-agent system use are given. As trends and conception development of intelligence technologies are the perfection of methods. models, architectures, and hard-sot ware tools for ITID in corporative systems and cloud computing.

An Intelligent Control for the Distributed Flexible Network Photovoltaic System using Autonomous Control and Agent

Science.gov (United States)

Park, Sangsoo; Miura, Yushi; Ise, Toshifumi

This paper proposes an intelligent control for the distributed flexible network photovoltaic system using autonomous control and agent. The distributed flexible network photovoltaic system is composed of a secondary battery bank and a number of subsystems which have a solar array, a dc/dc converter and a load. The control mode of dc/dc converter can be selected based on local information by autonomous control. However, if only autonomous control using local information is applied, there are some problems associated with several cases such as voltage drop on long power lines. To overcome these problems, the authors propose introducing agents to improve control characteristics. The autonomous control with agents is called as intelligent control in this paper. The intelligent control scheme that employs the communication between agents is applied for the model system and proved with simulation using PSCAD/EMTDC.

Providing Evidence-Based, Intelligent Support for Flood Resilient Planning and Policy: The PEARL Knowledge Base

Directory of Open Access Journals (Sweden)

George Karavokiros

2016-09-01

Full Text Available While flood risk is evolving as one of the most imminent natural hazards and the shift from a reactive decision environment to a proactive one sets the basis of the latest thinking in flood management, the need to equip decision makers with necessary tools to think about and intelligently select options and strategies for flood management is becoming ever more pressing. Within this context, the Preparing for Extreme and Rare Events in Coastal Regions (PEARL intelligent knowledge-base (PEARL KB of resilience strategies is presented here as an environment that allows end-users to navigate from their observed problem to a selection of possible options and interventions worth considering within an intuitive visual web interface assisting advanced interactivity. Incorporation of real case studies within the PEARL KB enables the extraction of (evidence-based lessons from all over the word, while the KB’s collection of methods and tools directly supports the optimal selection of suitable interventions. The Knowledge-Base also gives access to the PEARL KB Flood Resilience Index (FRI tool, which is an online tool for resilience assessment at a city level available to authorities and citizens. We argue that the PEARL KB equips authorities with tangible and operational tools that can improve strategic and operational flood risk management by assessing and eventually increasing resilience, while building towards the strengthening of risk governance. The online tools that the PEARL KB gives access to were demonstrated and tested in the city of Rethymno, Greece.

Intelligent Agent Based Traffic Signal Control on Isolated Intersections

Directory of Open Access Journals (Sweden)

Daniela Koltovska

2014-08-01

Full Text Available The purpose of this paper is to develop an adaptive signal control strategy on isolated urban intersections. An innovative approach to defining the set of states dependent on the actual and primarily observed parameters has been introduced. ?he Q–learning algorithm has been applied. The developed self-learning adaptive signal strategy has been tested on a re?l intersection. The intelligent agent results have been compared to those in cases of fixed-time and actuated control. Regarding the average total delay, the total number of stops and the total throughput, the best results have been obtained for unknown traffic demand and over-capacity.

A reusable multi-agent architecture for active intelligent websites

NARCIS (Netherlands)

Jonker, C.M.; Lam, R.A.; Treur, J.

In this paper a reusable multi-agent architecture for intelligent Websites is presented and illustrated for an electronic department store. The architecture has been designed and implemented using the compositional design method for multi-agent systems DESIRE. The agents within this architecture are

A distributed agent architecture for real-time knowledge-based systems: Real-time expert systems project, phase 1

Science.gov (United States)

Lee, S. Daniel

1990-01-01

We propose a distributed agent architecture (DAA) that can support a variety of paradigms based on both traditional real-time computing and artificial intelligence. DAA consists of distributed agents that are classified into two categories: reactive and cognitive. Reactive agents can be implemented directly in Ada to meet hard real-time requirements and be deployed on on-board embedded processors. A traditional real-time computing methodology under consideration is the rate monotonic theory that can guarantee schedulability based on analytical methods. AI techniques under consideration for reactive agents are approximate or anytime reasoning that can be implemented using Bayesian belief networks as in Guardian. Cognitive agents are traditional expert systems that can be implemented in ART-Ada to meet soft real-time requirements. During the initial design of cognitive agents, it is critical to consider the migration path that would allow initial deployment on ground-based workstations with eventual deployment on on-board processors. ART-Ada technology enables this migration while Lisp-based technologies make it difficult if not impossible. In addition to reactive and cognitive agents, a meta-level agent would be needed to coordinate multiple agents and to provide meta-level control.

Knowledge Based Artificial Augmentation Intelligence Technology: Next Step in Academic Instructional Tools for Distance Learning

Science.gov (United States)

Crowe, Dale; LaPierre, Martin; Kebritchi, Mansureh

2017-01-01

With augmented intelligence/knowledge based system (KBS) it is now possible to develop distance learning applications to support both curriculum and administrative tasks. Instructional designers and information technology (IT) professionals are now moving from the programmable systems era that started in the 1950s to the cognitive computing era.…

New trends in computational collective intelligence

CERN Document Server

Kim, Sang-Wook; Trawiński, Bogdan

2015-01-01

This book consists of 20 chapters in which the authors deal with different theoretical and practical aspects of new trends in Collective Computational Intelligence techniques. Computational Collective Intelligence methods and algorithms are one the current trending research topics from areas related to Artificial Intelligence, Soft Computing or Data Mining among others. Computational Collective Intelligence is a rapidly growing field that is most often understood as an AI sub-field dealing with soft computing methods which enable making group decisions and processing knowledge among autonomous units acting in distributed environments. Web-based Systems, Social Networks, and Multi-Agent Systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. The chapters included in this volume cover a selection of topics and new trends in several domains related to Collective Computational Intelligence: Language and Knowledge Processing, Data Mining Methods an...

Knowledge representation an approach to artificial intelligence

CERN Document Server

Bench-Capon, TJM

1990-01-01

Although many texts exist offering an introduction to artificial intelligence (AI), this book is unique in that it places an emphasis on knowledge representation (KR) concepts. It includes small-scale implementations in PROLOG to illustrate the major KR paradigms and their developments.****back cover copy:**Knowledge representation is at the heart of the artificial intelligence enterprise: anyone writing a program which seeks to work by encoding and manipulating knowledge needs to pay attention to the scheme whereby he will represent the knowledge, and to be aware of the consequences of the ch

Software Development for Auto-Generation of Interlocking Knowledge base using Artificial Intelligence Approach

Energy Technology Data Exchange (ETDEWEB)

Ko, Yun Seok [Nanseoul University (Korea); Kim, JOng Sun [Kwangwoon University (Korea)

1999-06-01

This paper proposes IIKBAG (Intelligent Interlocking Knowledge Base Generator) which can build automatically the interlocking knowledge base utilized as the real-time interlocking strategy of the electronic interlocking system in order to enhance it's reliability and expansion. The IIKBAG consists of the inference engine and the knowledge base. The former has an auto-learning function which searches all the train routes for the given station model based on heuristic search technique while dynamically searching the model, and then generates automatically the interlocking patterns obtained from the interlocking relations of signal facilities on the routes. The latter is designed as the structure which the real-time expert system embedded on IS (Interlocking System) can use directly in order to enhances the reliability and accuracy. The IIKBAG is implemented in C computer language for the purpose of the build and interface of the station structure database. And, a typical station model is simulated to prove the validity of the proposed IIKBAG. (author). 13 refs., 5 figs., 2 tabs.

Business Intelligence: Turning Knowledge into Power

Science.gov (United States)

Endsley, Krista

2009-01-01

Today, many school districts are turning to business intelligence tools to retrieve, organize, and share knowledge for faster analysis and more effective, guided decision making. Business intelligence (BI) tools are the technologies and applications that gather and report information to help an organization's leaders make better decisions. BI…

Formalizing Knowledge in Multi-Scale Agent-Based Simulations.

Science.gov (United States)

Somogyi, Endre; Sluka, James P; Glazier, James A

2016-10-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.

Foundation: Transforming data bases into knowledge bases

Science.gov (United States)

Purves, R. B.; Carnes, James R.; Cutts, Dannie E.

1987-01-01

One approach to transforming information stored in relational data bases into knowledge based representations and back again is described. This system, called Foundation, allows knowledge bases to take advantage of vast amounts of pre-existing data. A benefit of this approach is inspection, and even population, of data bases through an intelligent knowledge-based front-end.

Developmental reversals in risky decision making: intelligence agents show larger decision biases than college students.

Science.gov (United States)

Reyna, Valerie F; Chick, Christina F; Corbin, Jonathan C; Hsia, Andrew N

2014-01-01

Intelligence agents make risky decisions routinely, with serious consequences for national security. Although common sense and most theories imply that experienced intelligence professionals should be less prone to irrational inconsistencies than college students, we show the opposite. Moreover, the growth of experience-based intuition predicts this developmental reversal. We presented intelligence agents, college students, and postcollege adults with 30 risky-choice problems in gain and loss frames and then compared the three groups' decisions. The agents not only exhibited larger framing biases than the students, but also were more confident in their decisions. The postcollege adults (who were selected to be similar to the students) occupied an interesting middle ground, being generally as biased as the students (sometimes more biased) but less biased than the agents. An experimental manipulation testing an explanation for these effects, derived from fuzzy-trace theory, made the students look as biased as the agents. These results show that, although framing biases are irrational (because equivalent outcomes are treated differently), they are the ironical output of cognitively advanced mechanisms of meaning making.

Qualitative Knowledge Representations for Intelligent Nuclear Power Plants

International Nuclear Information System (INIS)

Cha, Kyoungho; Huh, Young H.

1993-01-01

Qualitative Physics(QP) has systematically been approached to qualitative modeling of physical systems for recent two decades. Designing intelligent systems for NPP requires an efficient representation of qualitative knowledge about the behavior and structure of NPP or its components. A novel representation of qualitative knowledge also enables intelligent systems to derive meaningful conclusions from incomplete or uncertain knowledge of a plant behavior. We look mainly into representative QP works on nuclear applications and the representation of qualitative knowledge for the diagnostic model, the qualitative simulation of a mental model of NPP operator, and the qualitative interpretation of the measured raw data from NPP. We present the challenging areas for QP applications in nuclear industry. QP technology will make NPP more intelligent

Automation of the Work intensively based on Knowledge, a Challenge for the New Technologies

Directory of Open Access Journals (Sweden)

Vasile MAZILESCU

2011-06-01

Full Text Available Knowledge Management or knowledge-based management (noted and used throughout this paper as KM is defined as a collaborative practice, by which organizations deliberately and intelligibly create, organize, distribute and analyze their own knowledge, in terms of resources, documents and people’s skills. It is widely regarded as an internal tool for increasing the operational efficiency of any organization, and has the potential to revolutionize the intelligent interaction between humans and agents (intelligent, based on more and more advanced technology. Semantic Technologies (STs are distributed software technologies that make that meaning more explicit, principally so that it can be understood by computers. STs will dramatically impact enterprise architecture and the engineering of new system and infrastructure capabilities. They are tools that represent meanings, associations, theories, and know-how about the uses of things separately from data and knowledge, using reasoning algorithms. Time restrictions are not excessive in usual STs as distributed applications. Critical time reasoning problems may occur in case of faulty operations and overloading. At present, the reasoning depth developed for such system is still poor. This work represents research results for incorporating and considering appropriate semantic foundations in future technologies that can automate knowledge based work.

General Intelligence, Emotional Intelligence and Academic Knowledge as Predictors of Creativity Domains: A Study of Gifted Students

Science.gov (United States)

Sahin, Feyzullah

2016-01-01

Creativity of the individual is dependent on numerous factors, such as knowledge, general intelligence and emotional intelligence. The general purpose of this study is to investigate the effect of general intelligence, emotional intelligence and academic knowledge on the emerging of domain-specific creativity. The study was conducted on 178…

Knowledge exchange between agents in real-time environments

DEFF Research Database (Denmark)

Frisvad, Jeppe Revall; Falster, Peter; Møller, Gert Lykke

2005-01-01

To obtain unpredictable social interaction between autonomous agents in real-time environments, we present a simple method for logic-based knowledge exchange. A method which is able to form new knowledge rather than do simple exchange of particular rules found in predetermined rule sets. The appl......To obtain unpredictable social interaction between autonomous agents in real-time environments, we present a simple method for logic-based knowledge exchange. A method which is able to form new knowledge rather than do simple exchange of particular rules found in predetermined rule sets...

MULTIPLE INTELLIGENCES AS PREDICTORS OF READING COMPREHENSION AND VOCABULARY KNOWLEDGE

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Abbas Ali Zarei

2014-07-01

Full Text Available Abstract: The present study was conducted to investigate types of Multiple Intelligences as predictors of reading comprehension and vocabulary knowledge. To meet this objective, a 60-item TOEFL test and a 90-item multiple intelligences questionnaire were distributed among 240 male and female Iranians studying English at Qazali and Parsian Universities in Qazvin. Data were analyzed using a multiple regression procedure. The result of the data analysis indicated that musical, interpersonal, kinesthetic, and logical intelligences were predicators of reading comprehension. Moreover, musical, verbal, visual, kinesthetic and natural intelligences made significant contributions to predicting vocabulary knowledge.   Key words: Multiple intelligences, reading comprehension, vocabulary knowledge.

A learning-based agent for home neurorehabilitation.

Science.gov (United States)

Lydakis, Andreas; Meng, Yuanliang; Munroe, Christopher; Wu, Yi-Ning; Begum, Momotaz

2017-07-01

This paper presents the iterative development of an artificially intelligent system to promote home-based neurorehabilitation. Although proper, structured practice of rehabilitation exercises at home is the key to successful recovery of motor functions, there is no home-program out there which can monitor a patient's exercise-related activities and provide corrective feedback in real time. To this end, we designed a Learning from Demonstration (LfD) based home-rehabilitation framework that combines advanced robot learning algorithms with commercially available wearable technologies. The proposed system uses exercise-related motion information and electromyography signals (EMG) of a patient to train a Markov Decision Process (MDP). The trained MDP model can enable an agent to serve as a coach for a patient. On a system level, this is the first initiative, to the best of our knowledge, to employ LfD in an health-care application to enable lay users to program an intelligent system. From a rehabilitation research perspective, this is a completely novel initiative to employ machine learning to provide interactive corrective feedback to a patient in home settings.

An Immune Agent for Web-Based AI Course

Science.gov (United States)

Gong, Tao; Cai, Zixing

2006-01-01

To overcome weakness and faults of a web-based e-learning course such as Artificial Intelligence (AI), an immune agent was proposed, simulating a natural immune mechanism against a virus. The immune agent was built on the multi-dimension education agent model and immune algorithm. The web-based AI course was comprised of many files, such as HTML…

An intelligent spatial land use planning support system using socially rational agents

NARCIS (Netherlands)

Ghavami, S.M.; Taleai, M.; Arentze, T.A.

2017-01-01

This research presents an intelligent planning support system based on multi-agent systems for spatial urban land use planning. The proposed system consists of two main phases: a pre-negotiation phase and an automated negotiation phase. The pre-negotiation phase involves interaction between human

Intelligent virtual agents as language trainers facilitate multilingualism.

Science.gov (United States)

Macedonia, Manuela; Groher, Iris; Roithmayr, Friedrich

2014-01-01

intelligent virtual agents (IVAs) with human appearance and the capability to teach foreign language vocabulary. We report results from studies that we have conducted with Billie, an IVA employed as a vocabulary trainer, as well as research findings on the acceptance of the agent as a trainer by adults and children. The results show that Billie can train humans as well as a human teacher can and that both adults and children accept the IVA as a trainer. The advantages of IVAs are multiple. First, their teaching methods can be based on neuropsychological research findings concerning memory and learning practice. Second, virtual teachers can provide individualized training. Third, they coach users during training, are always supportive, and motivate learners to train. Fourth, agents will reside in the user's mobile devices and thus be at the user's disposal everywhere and anytime. Agents in apps will make foreign language training accessible to anybody at low cost. This will enable people around the world, including physically, financially, and geographically disadvantaged persons, to learn a foreign language and help to facilitate multilingualism.

An Integrated Open Approach to Capturing Systematic Knowledge for Manufacturing Process Innovation Based on Collective Intelligence

Directory of Open Access Journals (Sweden)

Gangfeng Wang

2018-02-01

Full Text Available Process innovation plays a vital role in the manufacture realization of increasingly complex new products, especially in the context of sustainable development and cleaner production. Knowledge-based innovation design can inspire designers’ creative thinking; however, the existing scattered knowledge has not yet been properly captured and organized according to Computer-Aided Process Innovation (CAPI. Therefore, this paper proposes an integrated approach to tackle this non-trivial issue. By analyzing the design process of CAPI and technical features of open innovation, a novel holistic paradigm of process innovation knowledge capture based on collective intelligence (PIKC-CI is constructed from the perspective of the knowledge life cycle. Then, a multi-source innovation knowledge fusion algorithm based on semantic elements reconfiguration is applied to form new public knowledge. To ensure the credibility and orderliness of innovation knowledge refinement, a collaborative editing strategy based on knowledge lock and knowledge–social trust degree is explored. Finally, a knowledge management system MPI-OKCS integrating the proposed techniques is implemented into the pre-built CAPI general platform, and a welding process innovation example is provided to illustrate the feasibility of the proposed approach. It is expected that our work would lay the foundation for the future knowledge-inspired CAPI and smart process planning.

On construction method of shipborne and airborne radar intelligence and related equipment knowledge graph

Science.gov (United States)

Hao, Ruizhe; Huang, Jian

2017-08-01

Knowledge graph construction in military intelligence domain is sprouting but technically immature. This paper presents a method to construct the heterogeneous knowledge graph in the field of shipborne and airborne radar and equipment. Based on the expert knowledge and the up-to-date Internet open source information, we construct the knowledge graph of radar characteristic information and the equipment respectively, and establish relationships between two graphs, providing the pipeline and method for the intelligence organization and management in the context of the crowding battlefields big data.

Irrigation System through Intelligent Agents Implemented with Arduino Technology

Directory of Open Access Journals (Sweden)

Rodolfo SALAZAR

2013-11-01

Full Text Available The water has become in recent years a valuable and increasingly scarce. Its proper use in agriculture has demanded incorporate new technologies, mainly in the area of ICT. In this paper we present a smart irrigation system based on multi-agent architecture using fuzzy logic. The architecture incorporates different types of intelligent agents that an autonomous way monitor and are responsible for deciding if required enable / disable the irrigation system. This project proposes a real and innovative solution to the problem of inadequate water use with current irrigation systems employed in agricultural projects. This article presents the different technologies used, their adaptation to the solution of the problem and briefly discusses the first results obtained.

SME Internationalization Intelligence Information and Knowledge on International Opportunities

Directory of Open Access Journals (Sweden)

Zizah Che Senik

2014-12-01

Full Text Available Small and medium enterprises (SMEs internationalization intelligence, referring to the process of gathering information and knowledge on international opportunities, is crucial to initiate SMEs’ internationalization. The literature has stressed organizational resources, networks and information sharing as means to acquire internationalization intelligence, suggesting that the resource-based, network and social capital perspectives can be adopted to explore this issue. However, previous literature still lacks evidence on how SMEs acquire relevant intelligence, and who or what are involved with the process. To address this lack of evidence, we interviewed 54 SME owners/key personnel in the manufacturing sector to: identify sources of internationalization intelligence; examine how those sources assist SMEs to internationalize; and develop propositions on internationalization intelligence. Analyzing the data using NVivo, four themes emerged including institutions, business associates, personal efforts, and other means. The analysis suggests internationalization intelligence occurs mainly through the networks of the SME owners/key personnel, built on their firm’s resources through their internal and external information sharing activities, indicating the need of the SMEs to position themselves in their environments. These findings are developed into propositions. The study indicates multiple perspectives in conceptualizing the process of internationalization intelligence. This study advances a conceptualization of internationalization intelligence, and offers avenues for future research.

9th International Symposium on Intelligent Distributed Computing

CERN Document Server

Camacho, David; Analide, Cesar; Seghrouchni, Amal; Badica, Costin

2016-01-01

This book represents the combined peer-reviewed proceedings of the ninth International Symposium on Intelligent Distributed Computing – IDC’2015, of the Workshop on Cyber Security and Resilience of Large-Scale Systems – WSRL’2015, and of the International Workshop on Future Internet and Smart Networks – FI&SN’2015. All the events were held in Guimarães, Portugal during October 7th-9th, 2015. The 46 contributions published in this book address many topics related to theory and applications of intelligent distributed computing, including: Intelligent Distributed Agent-Based Systems, Ambient Intelligence and Social Networks, Computational Sustainability, Intelligent Distributed Knowledge Representation and Processing, Smart Networks, Networked Intelligence and Intelligent Distributed Applications, amongst others.

Building an adaptive agent to monitor and repair the electrical power system of an orbital satellite

Science.gov (United States)

Tecuci, Gheorghe; Hieb, Michael R.; Dybala, Tomasz

1995-01-01

Over several years we have developed a multistrategy apprenticeship learning methodology for building knowledge-based systems. Recently we have developed and applied our methodology to building intelligent agents. This methodology allows a subject matter expert to build an agent in the same way in which the expert would teach a human apprentice. The expert will give the agent specific examples of problems and solutions, explanations of these solutions, or supervise the agent as it solves new problems. During such interactions, the agent learns general rules and concepts, continuously extending and improving its knowledge base. In this paper we present initial results on applying this methodology to build an intelligent adaptive agent for monitoring and repair of the electrical power system of an orbital satellite, stressing the interaction with the expert during apprenticeship learning.

Knowledge-based processing for aircraft flight control

Science.gov (United States)

Painter, John H.; Glass, Emily; Economides, Gregory; Russell, Paul

1994-01-01

This Contractor Report documents research in Intelligent Control using knowledge-based processing in a manner dual to methods found in the classic stochastic decision, estimation, and control discipline. Such knowledge-based control has also been called Declarative, and Hybid. Software architectures were sought, employing the parallelism inherent in modern object-oriented modeling and programming. The viewpoint adopted was that Intelligent Control employs a class of domain-specific software architectures having features common over a broad variety of implementations, such as management of aircraft flight, power distribution, etc. As much attention was paid to software engineering issues as to artificial intelligence and control issues. This research considered that particular processing methods from the stochastic and knowledge-based worlds are duals, that is, similar in a broad context. They provide architectural design concepts which serve as bridges between the disparate disciplines of decision, estimation, control, and artificial intelligence. This research was applied to the control of a subsonic transport aircraft in the airport terminal area.

AN INTRODUCTION TO KNOWLEDGE-GROWING SYSTEM: A NOVEL FIELD IN ARTIFICIAL INTELLIGENCE

Directory of Open Access Journals (Sweden)

Arwin Datumaya Wahyudi Sumari

2010-07-01

Full Text Available The essential matter of Artificial Intelligence (AI is how to build an entity that mimics human intelligence in the way of learning of a phenomenon in a real life to gain knowledge of it and uses the knowledge to solve problems related to it. Based on the findings of intelligenct characteristic displayed by the human brain in growing and generating new knowledge by fusing information perceived by sensory organs, we develop brain-inspired Knowledge-Growing System (KGS that is, a system that is capable of growing its knowledge along with the accretion of information as the time passes. The essential matter of KGS is knowledge-growing method which is based on a new algorithm called Observation Multi-time A3S (OMA3S information-inferencing fusion method. In this paper we deliver the development of KGS along with some examples of KGS application to a real-life problem. Based on the state-of-the-art of AI and approaches to construct OMA3S method as KG method as well as validations to assess the system performance, we state that brain-inspired KGS is a novel field in AI.

Intelligent Virtual Agents as Language Trainers Facilitate Multilingualism

Directory of Open Access Journals (Sweden)

Manuela eMacedonia

2014-04-01

Full Text Available In this paper we introduce a new generation of language trainers: intelligent virtual agents (IVAs with human appearance and the capability to teach foreign language vocabulary. We report results from studies that we have conducted with Billie, an IVA employed as a vocabulary trainer, as well as research findings on the acceptance of the agent as a trainer by adults and children. The results show that Billie can train humans as well as a human teacher can and that both adults and children accept the IVA as a trainer. The advantages of IVAs are multiple. First, their teaching methods can be based on neuropsychological research findings concerning memory and learning practice. Second, virtual teachers can provide individualized training. Third, they coach users during training, are always supportive, and motivate learners to train. Fourth, agents will reside in the user’s mobile devices and thus be at the user’s disposal everywhere and anytime. Agents in apps will make foreign language training accessible to anybody at low cost. This will enable people around the world, including physically, financially and geographically disadvantaged persons, to learn a foreign language and help to facilitate multilingualism.

Systems Intelligence in Knowledge Management Implementation: A Momentum of the SECI Model

OpenAIRE

Sasaki, Yasuo

2014-01-01

This paper discusses the role of systems intelligence in knowledge management implementations, in particular, in the SECI model, a widely acknowledged knowledge creation process in an organization identified by Nonaka and Takeuchi (1995). The SECI model deals with interactions and conversions of tacit knowledge and explicit knowledge and mainly consists of four stages. The author illustrates systems intelligence, a certain kind of human intelligence focusing on systems thinking perspective pr...

Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017 Workshop by the North Atlantic Treaty Organization (NATO) Research Group IST-152 RTG

Science.gov (United States)

2018-04-18

simple example? 15. SUBJECT TERMS cybersecurity , cyber defense, autonomous agents, resilience, adversarial intelligence 16. SECURITY CLASSIFICATION...explained” based on other attack sequences (e.g., Kullback–Leibler [K-L] divergence). For example, the DARPA Explainable Artificial Intelligence ...a failure of humanity, not artificial intelligence . The notion of self-guidance approaches the field of robot ethics. How can autonomous agents be

Toward Intelligent Autonomous Agents for Cyber Defense: Report of the 2017 Workshop by the North Atlantic Treaty Organization (NATO) Research Group IST-152-RTG

Science.gov (United States)

2018-04-01

simple example? 15. SUBJECT TERMS cybersecurity , cyber defense, autonomous agents, resilience, adversarial intelligence 16. SECURITY CLASSIFICATION...explained” based on other attack sequences (e.g., Kullback–Leibler [K-L] divergence). For example, the DARPA Explainable Artificial Intelligence ...a failure of humanity, not artificial intelligence . The notion of self-guidance approaches the field of robot ethics. How can autonomous agents be

Building the competitive intelligence knowledge: processes and activities in a corporate organisation

OpenAIRE

Sreenivasulu, V.

1999-01-01

This paper discusses the process of building and developing comprehensive tools, techniques, support systems, and better methods of harnessing the competitive intelligence knowledge processes. The author stresses the need for building sophisticated methodological competitive intelligence knowledge acquisition, systematic collection of competitive intelligence knowledge from various sources for critical analysis, process, organization, synthesis, assessment, screening, filtering and interpreta...

Toward a systems- and control-oriented agent framework.

Science.gov (United States)

Fregene, Kingsley; Kennedy, Diane C; Wang, David W L

2005-10-01

This paper develops a systems- and control-oriented intelligent agent framework called the hybrid intelligent control agent (HICA), as well as its composition into specific kinds of multiagent systems. HICA is essentially developed around a hybrid control system core so that knowledge-based planning and coordination can be integrated with verified hybrid control primitives to achieve the coordinated control of multiple multimode dynamical systems. The scheme is applied to the control of teams of unmanned air and ground vehicles engaged in a pursuit-evasion war game. Results are demonstrated in simulation.

Nondestructive Intervention to Multi-Agent Systems through an Intelligent Agent

Science.gov (United States)

Han, Jing; Wang, Lin

2013-01-01

For a given multi-agent system where the local interaction rule of the existing agents can not be re-designed, one way to intervene the collective behavior of the system is to add one or a few special agents into the group which are still treated as normal agents by the existing ones. We study how to lead a Vicsek-like flocking model to reach synchronization by adding special agents. A popular method is to add some simple leaders (fixed-headings agents). However, we add one intelligent agent, called ‘shill’, which uses online feedback information of the group to decide the shill's moving direction at each step. A novel strategy for the shill to coordinate the group is proposed. It is strictly proved that a shill with this strategy and a limited speed can synchronize every agent in the group. The computer simulations show the effectiveness of this strategy in different scenarios, including different group sizes, shill speed, and with or without noise. Compared to the method of adding some fixed-heading leaders, our method can guarantee synchronization for any initial configuration in the deterministic scenario and improve the synchronization level significantly in low density groups, or model with noise. This suggests the advantage and power of feedback information in intervention of collective behavior. PMID:23658695

Nondestructive intervention to multi-agent systems through an intelligent agent.

Directory of Open Access Journals (Sweden)

Jing Han

Full Text Available For a given multi-agent system where the local interaction rule of the existing agents can not be re-designed, one way to intervene the collective behavior of the system is to add one or a few special agents into the group which are still treated as normal agents by the existing ones. We study how to lead a Vicsek-like flocking model to reach synchronization by adding special agents. A popular method is to add some simple leaders (fixed-headings agents. However, we add one intelligent agent, called 'shill', which uses online feedback information of the group to decide the shill's moving direction at each step. A novel strategy for the shill to coordinate the group is proposed. It is strictly proved that a shill with this strategy and a limited speed can synchronize every agent in the group. The computer simulations show the effectiveness of this strategy in different scenarios, including different group sizes, shill speed, and with or without noise. Compared to the method of adding some fixed-heading leaders, our method can guarantee synchronization for any initial configuration in the deterministic scenario and improve the synchronization level significantly in low density groups, or model with noise. This suggests the advantage and power of feedback information in intervention of collective behavior.

EEVADO-ontology based construction of a knowledge based system for handling radiation emergency

International Nuclear Information System (INIS)

Datta, D.; Hegde, A.G.

2001-01-01

The basic aim of handling a radiation emergency is to protect the site personnel and public in the off-site areas. Hence it is required to assess the accident to develop the protective action recommendations for the site personnel, members of the public and emergency workers. An explanation facility is required to analyze the emergency situation and make needful decision. Algorithmic based software cannot provide this support as it does not have any such facility. A knowledge based system (KBS) obviously would act as a special purpose intelligent agent on behalf or at the behest of the emergency organization. Knowledge of the KBS has been elicited on the basis of ontology, a set of definitions of classes, objects, attributes, relations and constraints. Ontology provides a vocabulary for the expression of domain knowledge. The present paper discusses the development and utility of a knowledge based system - EEVADO (Emergency Evaluation and Dosimetry). The present software is verified and validated by ontology and by conducting Desktop Exercise in training program on Emergency Preparedness. (author)

A knowledge-based system for fluidization studies

Energy Technology Data Exchange (ETDEWEB)

1990-04-01

Chemical engineers depend on process simulation models to determine optimal'' plant configurations which are technically feasible and economically viable. This research was undertaken to develop a comprehensive knowledge based simulation environment IPSE (Intelligent Process Simulation Environment) that can enhance the productivity of chemical engineers/modelers by serving as an intelligent assistant during all phases of process simulation involving fossil energy processes. In summary, the goals of this research are: application of knowledge-based techniques to the process modeling domain for enhancement of productivity; archiving and distribution of the knowledge of the best experts of process modeling; cross-model inference assistance to modelers not familiar with the process; and development of IPSE to serve as an intelligent tutoring system for process simulation. 18 figs.

Agent-based transportation planning compared with scheduling heuristics

NARCIS (Netherlands)

Mes, Martijn R.K.; van der Heijden, Matthijs C.; van Harten, Aart

2004-01-01

Here we consider the problem of dynamically assigning vehicles to transportation orders that have di¤erent time windows and should be handled in real time. We introduce a new agent-based system for the planning and scheduling of these transportation networks. Intelligent vehicle agents schedule

A Conversation Model Enabling Intelligent Agents to Give Emotional Support

NARCIS (Netherlands)

Van der Zwaan, J.M.; Dignum, V.; Jonker, C.M.

2012-01-01

In everyday life, people frequently talk to others to help them deal with negative emotions. To some extent, everybody is capable of comforting other people, but so far conversational agents are unable to deal with this type of situation. To provide intelligent agents with the capability to give

Modeling intelligent agent beliefs in a card game scenario

Science.gov (United States)

Gołuński, Marcel; Tomanek, Roman; WÄ siewicz, Piotr

In this paper we explore the problem of intelligent agent beliefs. We model agent beliefs using multimodal logics of belief, KD45(m) system implemented as a directed graph depicting Kripke semantics, precisely. We present a card game engine application which allows multiple agents to connect to a given game session and play the card game. As an example simplified version of popular Saboteur card game is used. Implementation was done in Java language using following libraries and applications: Apache Mina, LWJGL.

A Multi-task Principal Agent Model for Knowledge Contribution of Enterprise Staff

Directory of Open Access Journals (Sweden)

Chengyi LE

2016-10-01

Full Text Available According to the different behavior characteristics of knowledge contribution of enterprise employees, a multi-task principal-agent relationship of knowledge contribution between enterprise and employees is established based on principal-agent theory, analyzing staff’s knowledge contribution behavior of knowledge creation and knowledge participation. Based on this, a multi-task principal agent model for knowledge contribution of enterprise staff is developed to formulate the asymmetry of information in knowledge contribution Then, a set of incentive measures are derived from the theoretic model, aiming to prompt the knowledge contribution in enterprise. The result shows that staff’s knowledge creation behavior and positive participation behavior can influence and further promote each other Enterprise should set up respective target levels of both knowledge creation contribution and knowledge participation contribution and make them irreplaceable to each other. This work contributes primarily to the development of the literature on knowledge management and principal-agent theory. In addition, the applicability of the findings will be improved by further empirical analysis.

Semantic Network and Frame Knowledge Representation Formalisms in Artificial Intelligence

OpenAIRE

Rashid, Pshtiwan Qader

2015-01-01

ABSTRACT: Choosing a suitable method to represent the knowledge concerning the real world is one of the major issues involved in Artificial Intelligence. The purpose of this research is to consider the important beneficial roles of semantic network and frame formalisms for knowledge representation in Artificial Intelligence. The basic properties of the above methods for appropriate structuring and arranging the knowledge are presented. Some types of relationships, the conceptual graph...

Agent-Based Collaborative Traffic Flow Management, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — We propose agent-based game-theoretic approaches for simulation of strategies involved in multi-objective collaborative traffic flow management (CTFM). Intelligent...

Case-based reasoning: The marriage of knowledge base and data base

Science.gov (United States)

Pulaski, Kirt; Casadaban, Cyprian

1988-01-01

The coupling of data and knowledge has a synergistic effect when building an intelligent data base. The goal is to integrate the data and knowledge almost to the point of indistinguishability, permitting them to be used interchangeably. Examples given in this paper suggest that Case-Based Reasoning is a more integrated way to link data and knowledge than pure rule-based reasoning.

An Application of Artificial Intelligence to the Implementation of Electronic Commerce

Science.gov (United States)

Srivastava, Anoop Kumar

In this paper, we present an application of Artificial Intelligence (AI) to the implementation of Electronic Commerce. We provide a multi autonomous agent based framework. Our agent based architecture leads to flexible design of a spectrum of multiagent system (MAS) by distributing computation and by providing a unified interface to data and programs. Autonomous agents are intelligent enough and provide autonomy, simplicity of communication, computation, and a well developed semantics. The steps of design and implementation are discussed in depth, structure of Electronic Marketplace, an ontology, the agent model, and interaction pattern between agents is given. We have developed mechanisms for coordination between agents using a language, which is called Virtual Enterprise Modeling Language (VEML). VEML is a integration of Java and Knowledge Query and Manipulation Language (KQML). VEML provides application programmers with potential to globally develop different kinds of MAS based on their requirements and applications. We have implemented a multi autonomous agent based system called VE System. We demonstrate efficacy of our system by discussing experimental results and its salient features.

Knowledge Is Power for Medical Assistants: Crystallized and Fluid Intelligence As Predictors of Vocational Knowledge

Directory of Open Access Journals (Sweden)

Anne Moehring

2018-02-01

Full Text Available Medical education research has focused almost entirely on the education of future physicians. In comparison, findings on other health-related occupations, such as medical assistants, are scarce. With the current study, we wanted to examine the knowledge-is-power hypothesis in a real life educational setting and add to the sparse literature on medical assistants. Acquisition of vocational knowledge in vocational education and training (VET was examined for medical assistant students (n = 448. Differences in domain-specific vocational knowledge were predicted by crystallized and fluid intelligence in the course of VET. A multiple matrix design with 3 year-specific booklets was used for the vocational knowledge tests of the medical assistants. The unique and joint contributions of the predictors were investigated with structural equation modeling. Crystallized intelligence emerged as the strongest predictor of vocational knowledge at every stage of VET, while fluid intelligence only showed weak effects. The present results support the knowledge-is-power hypothesis, even in a broad and more naturalistic setting. This emphasizes the relevance of general knowledge for occupations, such as medical assistants, which are more focused on learning hands-on skills than the acquisition of academic knowledge.

Knowledge Is Power for Medical Assistants: Crystallized and Fluid Intelligence As Predictors of Vocational Knowledge.

Science.gov (United States)

Moehring, Anne; Schroeders, Ulrich; Wilhelm, Oliver

2018-01-01

Medical education research has focused almost entirely on the education of future physicians. In comparison, findings on other health-related occupations, such as medical assistants, are scarce. With the current study, we wanted to examine the knowledge-is-power hypothesis in a real life educational setting and add to the sparse literature on medical assistants. Acquisition of vocational knowledge in vocational education and training (VET) was examined for medical assistant students ( n = 448). Differences in domain-specific vocational knowledge were predicted by crystallized and fluid intelligence in the course of VET. A multiple matrix design with 3 year-specific booklets was used for the vocational knowledge tests of the medical assistants. The unique and joint contributions of the predictors were investigated with structural equation modeling. Crystallized intelligence emerged as the strongest predictor of vocational knowledge at every stage of VET, while fluid intelligence only showed weak effects. The present results support the knowledge-is-power hypothesis, even in a broad and more naturalistic setting. This emphasizes the relevance of general knowledge for occupations, such as medical assistants, which are more focused on learning hands-on skills than the acquisition of academic knowledge.

The representation of knowledge within model-based control systems

International Nuclear Information System (INIS)

Weygand, D.P.; Koul, R.

1987-01-01

The ability to represent knowledge is often considered essential to build systems with reasoning capabilities. In computer science, a good solution often depends on a good representation. The first step in development of most computer applications is selection of a representation for the input, output, and intermediate results that the program will operate upon. For applications in artificial intelligence, this initial choice of representation is especially important. This is because the possible representational paradigms are diverse and the forcing criteria for the choice are usually not clear in the beginning. Yet, the consequences of an inadequate choice can be devastating in the later state of a project if it is discovered that critical information cannot be encoded within the chosen representational paradigm. Problems arise when designing representational systems to support any kind of Knowledge-Base System, that is a computer system that uses knowledge to perform some task. The general case of knowledge-based systems can be thought of as reasoning agents applying knowledge to achieve goals. Artificial Intelligence (AI) research involves building computer systems to perform tasks of perception and reasoning, as well as storage and retrieval of data. The problem of automatically perceiving large patterns in data is a perceptual task that begins to be important for many expert systems applications. Most of AI research assumes that what needs to be represented is known a priori; an AI researcher's job is just figuring out how to encode the information in the system's data structure and procedures. 10 refs

Intelligent Agent Transparency in Human-Agent Teaming for Multi-UxV Management.

Science.gov (United States)

Mercado, Joseph E; Rupp, Michael A; Chen, Jessie Y C; Barnes, Michael J; Barber, Daniel; Procci, Katelyn

2016-05-01

We investigated the effects of level of agent transparency on operator performance, trust, and workload in a context of human-agent teaming for multirobot management. Participants played the role of a heterogeneous unmanned vehicle (UxV) operator and were instructed to complete various missions by giving orders to UxVs through a computer interface. An intelligent agent (IA) assisted the participant by recommending two plans-a top recommendation and a secondary recommendation-for every mission. A within-subjects design with three levels of agent transparency was employed in the present experiment. There were eight missions in each of three experimental blocks, grouped by level of transparency. During each experimental block, the IA was incorrect three out of eight times due to external information (e.g., commander's intent and intelligence). Operator performance, trust, workload, and usability data were collected. Results indicate that operator performance, trust, and perceived usability increased as a function of transparency level. Subjective and objective workload data indicate that participants' workload did not increase as a function of transparency. Furthermore, response time did not increase as a function of transparency. Unlike previous research, which showed that increased transparency resulted in increased performance and trust calibration at the cost of greater workload and longer response time, our results support the benefits of transparency for performance effectiveness without additional costs. The current results will facilitate the implementation of IAs in military settings and will provide useful data to the design of heterogeneous UxV teams. © 2016, Human Factors and Ergonomics Society.

An Integrated Conceptual Environment based on Collective Intelligence and Distributed Artificial Intelligence for Connecting People on Problem Solving

Directory of Open Access Journals (Sweden)

Vasile MAZILESCU

2012-12-01

Full Text Available This paper aims to analyze the different forms of intelligence within organizations in a systemic and inclusive vision, in order to conceptualize an integrated environment based on Distributed Artificial Intelligence (DAI and Collective Intelligence (CI. In this way we effectively shift the classical approaches of connecting people with people using collaboration tools (which allow people to work together, such as videoconferencing or email, groupware in virtual space, forums, workflow, of connecting people with a series of content management knowledge (taxonomies and documents classification, ontologies or thesauri, search engines, portals, to the current approaches of connecting people on the use (automatic of operational knowledge to solve problems and make decisions based on intellectual cooperation. The best way to use collective intelligence is based on knowledge mobilization and semantic technologies. We must not let computers to imitate people but to support people think and develop their ideas within a group. CI helps people to think together, while DAI tries to support people so as to limit human error. Within an organization, to manage CI is to combine instruments like Semantic Technologies (STs, knowledge mobilization methods for developing Knowledge Management (KM strategies, and the processes that promote connection and collaboration between individual minds in order to achieve collective objectives, to perform a task or to solve increasingly economic complex problems.

Tools for the Knowledge-Based Organization

DEFF Research Database (Denmark)

Ravn, Ib

2002-01-01

exist. They include a Master’s degree in knowledge management, a web- or print-based intelligence hub for the knowledge society, collaboration with the Danish intellectual capital reporting project, ongoing research on expertise and ethics in knowledge workers, a comparative study of competence...

Enhancing E-Learning through Web Service and Intelligent Agents

Directory of Open Access Journals (Sweden)

Nasir Hussain

2006-04-01

Full Text Available E-learning is basically the integration of various technologies. E-Learning technology is now maturing and we can find a multiplicity of standards. New technologies such as agents and web services are promising better results. In this paper we have proposed an e-learning architecture that is dependent on intelligent agent systems and web services. These communication technologies will make the architecture more robust, scalable and efficient.

Agent-Based Computing: Promise and Perils

OpenAIRE

Jennings, N. R.

1999-01-01

Agent-based computing represents an exciting new synthesis both for Artificial Intelligence (AI) and, more genrally, Computer Science. It has the potential to significantly improve the theory and practice of modelling, designing and implementing complex systems. Yet, to date, there has been little systematic analysis of what makes an agent such an appealing and powerful conceptual model. Moreover, even less effort has been devoted to exploring the inherent disadvantages that stem from adoptin...

Emotional Intelligence, Pain Knowledge, and Attitudes of Nursing Students in Hong Kong.

Science.gov (United States)

Chan, Joanne C Y; Hamamura, Takeshi

2016-04-01

Research on nursing students' pain knowledge and attitudes is limited. Although emotions play a role in pain assessment, no study has examined the associations between emotional intelligence and pain knowledge and the attitudes of nursing students. This cross-sectional quantitative study aimed to address this research gap by assessing the pain knowledge and attitudes of nursing students in Hong Kong and examining associations between emotional intelligence and the pain knowledge and attitudes of nursing students. A total of 104 postgraduate nursing students (45 Year 1 students and 59 Year 3 students) completed a questionnaire that included demographic information, the Schutte Emotional Intelligence Scale (SEIS) and the Knowledge and Attitudes Survey Regarding Pain (KASRP). Data analyses included descriptive statistics, correlational analyses, chi-square test and t-tests. The pain knowledge and attitudes of both Year 1 students (M = 20.40, SD = 3.78) and Year 3 students (M = 21.36, SD = 3.15) were suboptimal, t(102) = -1.41, p = .16. Year 1 students had higher emotional intelligence (M = 122.44, SD = 8.90) than Year 3 students (M = 117.71, SD = 14.34), t(98.35) = 2.07, p = .04. For Year 1 students, emotional intelligence was negatively correlated with pain knowledge and attitudes, but the correlation was not significant (r = -.15, p = .33). For Year 3 students, emotional intelligence, pain knowledge and attitudes were negatively correlated, but the correlation was significant (r = -.31, p = .02). These results suggest that nursing students' pain knowledge and attitudes could be improved. Implications for nurse educators to enhance emotional intelligence and pain education for nursing students are discussed. Copyright © 2016 American Society for Pain Management Nursing. Published by Elsevier Inc. All rights reserved.

Students’ thinking level based on intrapersonal intelligence

Science.gov (United States)

Sholikhati, Rahadian; Mardiyana; Retno Sari Saputro, Dewi

2017-12-01

This research aims to determine the students’ thinking level based on bloom taxonomy guidance and reviewed from students' Intrapersonal Intelligence. Taxonomy bloom is a taxonomy that classifies the students' thinking level into six, ie the remembering, understanding, applying, analyzing, creating, and evaluating levels. Students' Intrapersonal Intelligence is the intelligence associated with awareness and knowledge of oneself. The type of this research is descriptive research with qualitative approach. The research subject were taken by one student in each Intrapersonal Intelligence category (high, moderate, and low) which then given the problem solving test and the result was triangulated by interview. From this research, it is found that high Intrapersonal Intelligence students can achieve analyzing thinking level, subject with moderate Intrapersonal Intelligence being able to reach the level of applying thinking, and subject with low Intrapersonal Intelligence able to reach understanding level.

The BioIntelligence Framework: a new computational platform for biomedical knowledge computing.

Science.gov (United States)

Farley, Toni; Kiefer, Jeff; Lee, Preston; Von Hoff, Daniel; Trent, Jeffrey M; Colbourn, Charles; Mousses, Spyro

2013-01-01

Breakthroughs in molecular profiling technologies are enabling a new data-intensive approach to biomedical research, with the potential to revolutionize how we study, manage, and treat complex diseases. The next great challenge for clinical applications of these innovations will be to create scalable computational solutions for intelligently linking complex biomedical patient data to clinically actionable knowledge. Traditional database management systems (DBMS) are not well suited to representing complex syntactic and semantic relationships in unstructured biomedical information, introducing barriers to realizing such solutions. We propose a scalable computational framework for addressing this need, which leverages a hypergraph-based data model and query language that may be better suited for representing complex multi-lateral, multi-scalar, and multi-dimensional relationships. We also discuss how this framework can be used to create rapid learning knowledge base systems to intelligently capture and relate complex patient data to biomedical knowledge in order to automate the recovery of clinically actionable information.

Artificial intelligence and knowledge management

OpenAIRE

Hoesch, Hugo Cesar; Barcellos, Vânia

2006-01-01

This article intends to make an analysis about the Artificial Intelligence (AI) and the Knowledge Management (KM). Faced with the dualism mind and body how we be able to see it AI? It doesn’t intent to create identical copy of human being, but try to find the better form to represent all the knowledge contained in our minds. The society of the information lives a great paradox, at the same time that we have access to an innumerable amount of information, the capacity and the forms of its proc...

Using Intelligent Agents to Manage Business Processes

OpenAIRE

Jennings, N. R.; Faratin, P.; Johnson, M. J.; O'Brien, P.; Wiegand, M. E.

1996-01-01

Management of the business process requires pertinent, consistent and up-to-date information gathering and information dissemination. These complex and time consuming tasks prompt organizations to develop an Information Technology system to assist with the management of various aspects of their business processes. Intelligent agents are the strongest solution candidates because of their many advantages, namely: autonomy, social ability, responsiveness and proactiveness. Given these characteri...

DEVELOPMENT OF THE INTELLECTUAL AGENT-ORIENTED SYSTEM FOR DECISION SUPPORT AT ENTERPRISE

Directory of Open Access Journals (Sweden)

G. Chornous

2014-06-01

Full Text Available Actual status of management confirms usefulness and necessity for development of scientific modeling tools for decision-making processes based on distributed artificial intelligence. The paper presents opportunities of the agent – oriented approach to support operative and strategic management decisions at the pharmaceutical enterprise. It is argued that the combination of intelligent agents technology and Data Mining (DM produces a powerful synergistic effect. The basis of the intellectual agent – oriented DSS (AODSS is proposed to put a hybrid approach to the use of DM. Hybrid intelligent AODSS is represented numerous network of small agents, it provides concurrent operation execution, solutions distribution, knowledge management. Agents can be divided into groups: data agents, monitoring agents, agents for solutions search, modeling agents, impact agents and presentations agents. The result of research is development of AODSS created as a multi-level system wherein the project, process and environment levels are intercommunicated. The combination of intelligent technologies in AODSS allows involve rules, cases, a wide range of DM methods and models. The paper proposes a variant of AODSS implementation within the real enterprise IT-infrastructure based on SAP NetWeaver. The analysis results of the semi-commercial operation of the system assures that it can improve managerial decisions inasmuch as accuracy, consistency, flexibility, speed together form the basis of actual efficient solutions.

The impact of emotional intelligence on faculty members' knowledge sharing behaviors

Directory of Open Access Journals (Sweden)

Masoomeh Arabshahi,

2013-12-01

Full Text Available Universities and institutions of higher education with a professional, special, educational and cultural environment, play an important role in effective knowledge management and preparing the background for knowledge sharing. Faculty members are known as the main elements of the university who own mental and intellectual property. Their knowledge sharing under certain conditions along with knowledge sharing behaviors improve individual and organizational operations. Moreover, the tendency to do these actions is the most important factor in knowledge sharing behavior and emotional intelligence (EQ, as one of the social intelligence factors, can guide individual thinking and activity. This study examines the impact of emotional intelligence on faculty members' knowledge sharing behaviors. Regarding the purpose and nature, this study was functional and its methodology was exploratory and due to evaluation of the relations and impacts among variables, it was a correlational method. Data collection included interviews with experts for the qualitative part and a questionnaire for the quantitative part. The qualitative findings indicate different emotional intelligence dimensions, which includes self-awareness, social skills, coping with pressure, adaptability and overall creation. In addition, the result of EQ dimensions on knowledge sharing behavior reveal that “social skills, coping with pressure, and overall creation” share a link with faculty members' research behavior among the four dimensions of knowledge sharing behavior and that “adaptability” has no significant relationship with knowledge sharing behavior.

A Multi-Agent Traffic Control Model Based on Distributed System

Directory of Open Access Journals (Sweden)

Qian WU

2014-06-01

Full Text Available With the development of urbanization construction, urban travel has become a quite thorny and imminent problem. Some previous researches on the large urban traffic systems easily change into NPC problems. We purpose a multi-agent inductive control model based on the distributed approach. To describe the real traffic scene, this model designs four different types of intelligent agents, i.e. we regard each lane, route, intersection and traffic region as different types of intelligent agents. Each agent can achieve the real-time traffic data from its neighbor agents, and decision-making agents establish real-time traffic signal plans through the communication between local agents and their neighbor agents. To evaluate the traffic system, this paper takes the average delay, the stopped time and the average speed as performance parameters. Finally, the distributed multi-agent is simulated on the VISSIM simulation platform, the simulation results show that the multi-agent system is more effective than the adaptive control system in solving the traffic congestion.

Using Students' Knowledge to Generate Individual Feedback: Concept for an Intelligent Educational System on Logistics.

Science.gov (United States)

Ziems, Dietrich; Neumann, Gaby

1997-01-01

Discusses a methods kit for interactive problem-solving exercises in engineering education as well as a methodology for intelligent evaluation of solutions. The quality of a system teaching logistics thinking can be improved using artificial intelligence. Embedding a rule-based diagnosis module that evaluates the student's knowledge actively…

ACCOUNTING INFORMATION SYSTEMS: AN APPROACH FOCUSED ON OBJECTS WITH INTELLIGENT AGENTS

Directory of Open Access Journals (Sweden)

Marcelo Botelho da Costa Moraes

2010-01-01

Full Text Available Accounting aims at the treatment of information related to economic events within organizations. In order to do so, the double entry method is used (debt and credit accounting, which only considers monetary variations. With the development of information technologies, accounting information systems are born. In the 1980’s, the REA model (economic Resources, economic Events and economic Agents is created, which focuses on accounting information records, based on the association of economic resources, economic events and economic agents. The objective of this work is to demonstrate an object-oriented modeling with intelligent agents use, for information development and analysis focused on users. The proposed model is also analyzed according to accounting information quality, necessary for accounting information users, capable to comply with the needs of different user groups, with advantages in applications.

Detection of cyst using image segmentation and building knowledge-based intelligent decision support system as an aid to telemedicine

Science.gov (United States)

Janet, J.; Natesan, T. R.; Santhosh, Ramamurthy; Ibramsha, Mohideen

2005-02-01

An intelligent decision support tool to the Radiologist in telemedicine is described. Medical prescriptions are given based on the images of cyst that has been transmitted over computer networks to the remote medical center. The digital image, acquired by sonography, is converted into an intensity image. This image is then subjected to image preprocessing which involves correction methods to eliminate specific artifacts. The image is resized into a 256 x 256 matrix by using bilinear interpolation method. The background area is detected using distinct block operation. The area of the cyst is calculated by removing the background area from the original image. Boundary enhancement and morphological operations are done to remove unrelated pixels. This gives us the cyst volume. This segmented image of the cyst is sent to the remote medical center for analysis by Knowledge based artificial Intelligent Decision Support System (KIDSS). The type of cyst is detected and reported to the control mechanism of KIDSS. Then the inference engine compares this with the knowledge base and gives appropriate medical prescriptions or treatment recommendations by applying reasoning mechanisms at the remote medical center.

The Consciousness-Intelligence-Knowledge Pyramid: An 8x8 Layer Model

Directory of Open Access Journals (Sweden)

Athanasios S. Drigas

2017-10-01

Full Text Available Cognitive and metacognitive skills are recognized and studied since antiquity. From the theory of Aristotle, according to which knowledge is product of the human mind and Platonic gnosiology and the theory of true knowledge, to the modern cognitive science, the question of how people acquire knowledge, has occupied a multitude of scientists. In this article we present a cognitive-based approach to the process of acquiring knowledge, we analyze the dominant theories of knowledge, theories of intelligence, as well as learning theories, and thus we propose an eight-layer pyramid of knowledge. We also analyze the cognitive processes and metacognitive skills required to get an individual to the highest layer of the knowledge pyramid.

Knowledge-based utility

International Nuclear Information System (INIS)

Chwalowski, M.

1997-01-01

This presentation provides industry examples of successful marketing practices by companies facing deregulation and competition. The common thread through the examples is that long term survival of today's utility structure is dependent on the strategic role of knowledge. As opposed to regulated monopolies which usually own huge physical assets and have very little intelligence about their customers, unregulated enterprises tend to be knowledge-based, characterized by higher market value than book value. A knowledge-based enterprise gathers data, creates information and develops knowledge by leveraging it as a competitive weapon. It institutionalizes human knowledge as a corporate asset for use over and over again by the use of databases, computer networks, patents, billing, collection and customer services (BCCS), branded interfaces and management capabilities. Activities to become knowledge-based such as replacing inventory/fixed assets with information about material usage to reduce expenditure and achieve more efficient operations, and by focusing on integration and value-adding delivery capabilities, were reviewed

Exploiting Mobile Ad Hoc Networking and Knowledge Generation to Achieve Ambient Intelligence

Directory of Open Access Journals (Sweden)

Anna Lekova

2012-01-01

Full Text Available Ambient Intelligence (AmI joins together the fields of ubiquitous computing and communications, context awareness, and intelligent user interfaces. Energy, fault-tolerance, and mobility are newly added dimensions of AmI. Within the context of AmI the concept of mobile ad hoc networks (MANETs for “anytime and anywhere” is likely to play larger roles in the future in which people are surrounded and supported by small context-aware, cooperative, and nonobtrusive devices that will aid our everyday life. The connection between knowledge generation and communication ad hoc networking is symbiotic—knowledge generation utilizes ad hoc networking to perform their communication needs, and MANETs will utilize the knowledge generation to enhance their network services. The contribution of the present study is a distributed evolving fuzzy modeling framework (EFMF to observe and categorize relationships and activities in the user and application level and based on that social context to take intelligent decisions about MANETs service management. EFMF employs unsupervised online one-pass fuzzy clustering method to recognize nodes' mobility context from social scenario traces and ubiquitously learn “friends” and “strangers” indirectly and anonymously.

A deep knowledge architecture for intelligent support of nuclear waste transportation decisions

International Nuclear Information System (INIS)

Batra, D.; Bowen, W.M.; Hill, T.R.; Weeks, K.D.

1988-01-01

The concept of intelligent decision support has been discussed and explored in several recent papers, one of which has suggested the use of a Deep Knowledge Architecture. This paper explores this concept through application to a specific decision environment. The complex problems involved in nuclear waste disposal decisions provide an excellent test case. The resulting architecture uses an integrated, multi-level model base to represent the deep knowledge of the problem. Combined with the surface level knowledge represented by the database, the proposed knowledge base complements that of the decision-maker, allowing analysis at a range of levels of decisions which may also occur at a range of levels

Chronic Heart Failure Follow-up Management Based on Agent Technology.

Science.gov (United States)

Mohammadzadeh, Niloofar; Safdari, Reza

2015-10-01

Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making.

Intelligent Agent Based Semantic Web in Cloud Computing Environment

OpenAIRE

Mukhopadhyay, Debajyoti; Sharma, Manoj; Joshi, Gajanan; Pagare, Trupti; Palwe, Adarsha

2013-01-01

Considering today's web scenario, there is a need of effective and meaningful search over the web which is provided by Semantic Web. Existing search engines are keyword based. They are vulnerable in answering intelligent queries from the user due to the dependence of their results on information available in web pages. While semantic search engines provides efficient and relevant results as the semantic web is an extension of the current web in which information is given well defined meaning....

CATS-based Air Traffic Controller Agents

Science.gov (United States)

Callantine, Todd J.

2002-01-01

This report describes intelligent agents that function as air traffic controllers. Each agent controls traffic in a single sector in real time; agents controlling traffic in adjoining sectors can coordinate to manage an arrival flow across a given meter fix. The purpose of this research is threefold. First, it seeks to study the design of agents for controlling complex systems. In particular, it investigates agent planning and reactive control functionality in a dynamic environment in which a variety perceptual and decision making skills play a central role. It examines how heuristic rules can be applied to model planning and decision making skills, rather than attempting to apply optimization methods. Thus, the research attempts to develop intelligent agents that provide an approximation of human air traffic controller behavior that, while not based on an explicit cognitive model, does produce task performance consistent with the way human air traffic controllers operate. Second, this research sought to extend previous research on using the Crew Activity Tracking System (CATS) as the basis for intelligent agents. The agents use a high-level model of air traffic controller activities to structure the control task. To execute an activity in the CATS model, according to the current task context, the agents reference a 'skill library' and 'control rules' that in turn execute the pattern recognition, planning, and decision-making required to perform the activity. Applying the skills enables the agents to modify their representation of the current control situation (i.e., the 'flick' or 'picture'). The updated representation supports the next activity in a cycle of action that, taken as a whole, simulates air traffic controller behavior. A third, practical motivation for this research is to use intelligent agents to support evaluation of new air traffic control (ATC) methods to support new Air Traffic Management (ATM) concepts. Current approaches that use large, human

An Agent-Based Model for the Development of Intelligent Mobile Services

NARCIS (Netherlands)

Koch, F.L.

2009-01-01

The next generation of mobile services must invisible, convenient, and useful. It requires new techniques to design and develop mobile computing applications, based on user-centred, environment-aware, adaptive behaviour. I propose an alternative technology for the development of intelligent mobile

Intelligent Virtual Agents : 9th International Conference, IVA 2009 Amsterdam, The Netherlands, September 14-16, 2009 Proceedings

NARCIS (Netherlands)

Ruttkay, Z.M.; Kipp, M.; Nijholt, Antinus; Vilhjalmsson, H.H.

2009-01-01

Welcome to the Proceedings of the 9th International Conference on Intelligent Virtual Agents, held 14-16 September, 2009 in Amsterdam, The Netherlands. Intelligent Virtual Agents (IVAs) are interactive characters that exhibit humanlike qualities and communicate with humans or with each other using

Active Learning for Autonomous Intelligent Agents: Exploration, Curiosity, and Interaction

OpenAIRE

Lopes, Manuel; Montesano, Luis

2014-01-01

In this survey we present different approaches that allow an intelligent agent to explore autonomous its environment to gather information and learn multiple tasks. Different communities proposed different solutions, that are in many cases, similar and/or complementary. These solutions include active learning, exploration/exploitation, online-learning and social learning. The common aspect of all these approaches is that it is the agent to selects and decides what information to gather next. ...

Intelligent tutoring system of the university department

Directory of Open Access Journals (Sweden)

A. S. Aleshchenko

2016-01-01

Full Text Available The aim of the research is intelligent tutoring system for planning and development of individual learning programs for students. One of the important components of modern training programs is the individual practice programs that are formed from the first course and built up in the process of learning in the subsequent courses. Each individual practice program is formed on the basis of the Working program of practice for a specific group. At later practice stages planning and adjustment of the individual program are worked out for a particular student.The agent-oriented approach for the planning of individual learning programs is used for the formation of individual practice program. Agents of the intelligent learning systems are created according to the requirements of service-oriented architecture. To apply knowledge there used an integrated approach to represent knowledge.As a result of research, the authors propose the architecture of intelligent educational systems of the University Department, using the repository of learning objects, telecommunication systems and such agents as: the learner, the assessment of the student’s knowledge, the formation of individual programs for learning, the personal learning environment, the methodical support, the businesses. The authors demonstrate the possibility for the formation of individual practice programs using an agent of the methodical support.Application of the approaches and technologies which were considered in the article will allow to solve problems of the formation of individual practice programs. The use of such applications will extend the possibilities of intelligent tutoring systems of the University departments.

Developing technology intelligence strategy to access knowledge of innovation clusters.

OpenAIRE

Rani Jeanne Dang; Letizia Mortara; Ruth Thomson; Tim Minshall

2010-01-01

Current times are characterised by a knowledge-based economy and fast technological change. In this difficult environment, companies compete to maintain a relevant position through innovation. In response to these challenges, many companies are currently adopting an open approach to innovation, pursuing innovation by combining internal and external resources. Technology intelligence (TI) activities support the implementation of open innovation with the systematic capture and delivery of infor...

Strategic Management Model with Lens of Knowledge Management and Competitive Intelligence: A Review Approach

OpenAIRE

Shujahat, Muhammad; Hussain, Saddam; Javed, Sammar; Muhammad, Imran Malik; Thursamy, Ramayah; Ali, Junaid

2017-01-01

Purpose:\\ud First purpose of this study is to discuss the synergic and separate use of knowledge and\\ud intelligence, via knowledge management and competitive intelligence, in each stage of strategic\\ud management process. Second purpose is to discuss the implications of each stage of strategic\\ud management process for knowledge management and competitive intelligence and vice versa.\\ud Methodology/Design/Approach:\\ud A systematic literature review was performed within timeframe of 2000 to 2...

Hospital-based nurses' perceptions of the adoption of Web 2.0 tools for knowledge sharing, learning, social interaction and the production of collective intelligence.

Science.gov (United States)

Lau, Adela S M

2011-11-11

Web 2.0 provides a platform or a set of tools such as blogs, wikis, really simple syndication (RSS), podcasts, tags, social bookmarks, and social networking software for knowledge sharing, learning, social interaction, and the production of collective intelligence in a virtual environment. Web 2.0 is also becoming increasingly popular in e-learning and e-social communities. The objectives were to investigate how Web 2.0 tools can be applied for knowledge sharing, learning, social interaction, and the production of collective intelligence in the nursing domain and to investigate what behavioral perceptions are involved in the adoption of Web 2.0 tools by nurses. The decomposed technology acceptance model was applied to construct the research model on which the hypotheses were based. A questionnaire was developed based on the model and data from nurses (n = 388) were collected from late January 2009 until April 30, 2009. Pearson's correlation analysis and t tests were used for data analysis. Intention toward using Web 2.0 tools was positively correlated with usage behavior (r = .60, P Web 2.0 tools and enable them to better plan the strategy of implementation of Web 2.0 tools for knowledge sharing, learning, social interaction, and the production of collective intelligence.

Hospital-Based Nurses’ Perceptions of the Adoption of Web 2.0 Tools for Knowledge Sharing, Learning, Social Interaction and the Production of Collective Intelligence

Science.gov (United States)

2011-01-01

Background Web 2.0 provides a platform or a set of tools such as blogs, wikis, really simple syndication (RSS), podcasts, tags, social bookmarks, and social networking software for knowledge sharing, learning, social interaction, and the production of collective intelligence in a virtual environment. Web 2.0 is also becoming increasingly popular in e-learning and e-social communities. Objectives The objectives were to investigate how Web 2.0 tools can be applied for knowledge sharing, learning, social interaction, and the production of collective intelligence in the nursing domain and to investigate what behavioral perceptions are involved in the adoption of Web 2.0 tools by nurses. Methods The decomposed technology acceptance model was applied to construct the research model on which the hypotheses were based. A questionnaire was developed based on the model and data from nurses (n = 388) were collected from late January 2009 until April 30, 2009. Pearson’s correlation analysis and t tests were used for data analysis. Results Intention toward using Web 2.0 tools was positively correlated with usage behavior (r = .60, P Web 2.0 tools and enable them to better plan the strategy of implementation of Web 2.0 tools for knowledge sharing, learning, social interaction, and the production of collective intelligence. PMID:22079851

Policy based Agents in Wireless Body Sensor Mesh Networks for Patient Health Monitoring

OpenAIRE

Kevin Miller; Suresh Sankaranarayanan

2009-01-01

There is presently considerable research interest in using wireless and mobile technologies in patient health monitoring particularly in hospitals and nursing homes. For health monitoring,, an intelligent agent based hierarchical architecture has already been published by one of the authors of this paper. Also, the technique of monitoring and notifying the health of patients using an intelligent agent, to the concerned hospital personnel, has also been proposed. We now present the details of ...

Design of an Intelligent Support Agent Model for People with a Cognitive Vulnerability

NARCIS (Netherlands)

Aziz, A.A.; Klein, M.C.A.; Zhang, B.; Wang, Y.; Kinser, W.

2010-01-01

This paper presents the design of an intelligent agent application aimed at supporting people with a cognitive vulnerability to prevent the onset of a depression. For this, a computational model of the cognitive processes around depression is used. The agent application uses the principles of

On Intelligent Design and Planning Method of Process Route Based on Gun Breech Machining Process

Science.gov (United States)

Hongzhi, Zhao; Jian, Zhang

2018-03-01

The paper states an approach of intelligent design and planning of process route based on gun breech machining process, against several problems, such as complex machining process of gun breech, tedious route design and long period of its traditional unmanageable process route. Based on gun breech machining process, intelligent design and planning system of process route are developed by virtue of DEST and VC++. The system includes two functional modules--process route intelligent design and its planning. The process route intelligent design module, through the analysis of gun breech machining process, summarizes breech process knowledge so as to complete the design of knowledge base and inference engine. And then gun breech process route intelligently output. On the basis of intelligent route design module, the final process route is made, edited and managed in the process route planning module.

Recent advances in knowledge-based paradigms and applications enhanced applications using hybrid artificial intelligence techniques

CERN Document Server

Jain, Lakhmi

2014-01-01

This book presents carefully selected contributions devoted to the modern perspective of AI research and innovation. This collection covers several areas of applications and motivates new research directions. The theme across all chapters combines several domains of AI research , Computational Intelligence and Machine Intelligence including an introduction to  the recent research and models. Each of the subsequent chapters reveals leading edge research and innovative solution that employ AI techniques with an applied perspective. The problems include classification of spatial images, early smoke detection in outdoor space from video images, emergent segmentation from image analysis, intensity modification in images, multi-agent modeling and analysis of stress. They all are novel pieces of work and demonstrate how AI research contributes to solutions for difficult real world problems that benefit the research community, industry and society.

How to Improve Artificial Intelligence through Web

Directory of Open Access Journals (Sweden)

Adrian LUPASC

2005-10-01

Full Text Available Intelligent agents, intelligent software applications and artificial intelligent applications from artificial intelligence service providers maymake their way onto the Web in greater number as adaptive software, dynamic programming languages and Learning Algorithms are introduced intoWeb Services. The evolution of Web architecture may allow intelligent applications to run directly on the Web by introducing XML, RDF and logiclayer. The Intelligent Wireless Web’s significant potential for rapidly completing information transactions may take an important contribution toglobal worker productivity. Artificial intelligence can be defined as the study of the ways in which computers can be made to perform cognitivetasks. Examples of such tasks include understanding natural language statements, recognizing visual patterns or scenes, diagnosing diseases orillnesses, solving mathematical problems, performing financial analyses, learning new procedures for solving problems. The term expert system canbe considered to be a particular type of knowledge-based system. An expert system is a system in which the knowledge is deliberately represented“as it is”. Expert systems are applications that make decisions in real-life situations that would otherwise be performed by a human expert. They areprograms designed to mimic human performance at specialized, constrained problem-solving tasks. They are constructed as a collection of IF-THENproduction rules combined with a reasoning engine that applies those rules, either in a forward or backward direction, to specific problems.

Machine Learning-based Intelligent Formal Reasoning and Proving System

Science.gov (United States)

Chen, Shengqing; Huang, Xiaojian; Fang, Jiaze; Liang, Jia

2018-03-01

The reasoning system can be used in many fields. How to improve reasoning efficiency is the core of the design of system. Through the formal description of formal proof and the regular matching algorithm, after introducing the machine learning algorithm, the system of intelligent formal reasoning and verification has high efficiency. The experimental results show that the system can verify the correctness of propositional logic reasoning and reuse the propositional logical reasoning results, so as to obtain the implicit knowledge in the knowledge base and provide the basic reasoning model for the construction of intelligent system.

The role of knowledge management tools in supporting sustainable forest management

Directory of Open Access Journals (Sweden)

H. Vacik

2013-12-01

Full Text Available Aim of study: Knowledge Management (KM tools facilitate the implementation of knowledge processes by identifying, creating, structuring, and sharing knowledge through use of information technology in order to improve decision-making. In this contribution, we review the way in which KM tools and techniques are used in forest management, and categorize a selected set of them according to their contribution to support decision makers in the phases of problem identification, problem modelling, and problem solving.Material and Methods: Existing examples of cognitive mapping tools, web portals, workflow systems, best practices, and expert systems as well as intelligent agents are screened for their applicability and use in the context of decision support for sustainable forest management. Evidence from scientific literature and case studies is utilized to evaluate the contribution of the different KM tools to support problem identification, problem modelling, and problem solving.Main results: Intelligent agents, expert systems and cognitive maps support all phases of the forest planning process strongly. Web based tools have good potential to support participatory forest planning. Based on the needs of forest management decision support and the thus-far underutilized capabilities of KM tools it becomes evident that future decision analysis will have to consider the use of KM more intensively. Research highlights: As the problem-solving process is the vehicle for connecting both knowledge and decision making performance, the next generation of DSS will need to better encapsulate practices that enhance and promote knowledge management. Web based tools will substitute desktop applications by utilizing various model libraries on the internet.Keywords: best practices; cognitive mapping; expert systems; intelligent agents; web portals; workflow systems; Decision Support Systems. 

Decision Support for Software Process Management Teams: An Intelligent Software Agent Approach

National Research Council Canada - National Science Library

Church, Lori

2000-01-01

... to market, eliminate redundancy, and ease job stress. This thesis proposes a conceptual model for software process management decision support in the form of an intelligent software agent network...

Environmental Knowledge as Design Development Agent

Directory of Open Access Journals (Sweden)

Buthayna Hasan Eilouti

2012-06-01

Full Text Available Linking knowledge learnt from nature with concepts of man-made product generation, Biomimetics represents an application of environmental knowledge on engineering design. In this paper, an exploratory approach that is based on the concepts of Biomimetics and their potential transformations into design processing agents is introduced. The approach is tested as a project that applies knowledge inspired by organisms in their natural biomes for the derivation of architectural designs. The project is implemented in a digital architectural design studio in order to model metamorphosis and simulate adaptations of products. The results of the project implementation seem to encourage adopting its associative environmental problem-solving techniques and inter-disciplinary methods as alternatives or complementary to conventional functional- or formal-oriented problem-solving approaches.

Artificial Intelligence, Expert Systems, Natural Language Interfaces, Knowledge Engineering and the Librarian.

Science.gov (United States)

Davies, Jim

This paper begins by examining concepts of artificial intelligence (AI) and discusses various definitions of the concept that have been suggested in the literature. The nesting relationship of expert systems within the broader framework of AI is described, and expert systems are characterized as knowledge-based systems (KBS) which attempt to solve…

Domain-specific knowledge as the "dark matter" of adult intelligence: Gf/Gc, personality and interest correlates.

Science.gov (United States)

Ackerman, P L

2000-03-01

An enduring controversy in intelligence theory and assessment, the argument that middle-aged adults are, on average, less intelligent than young adults, is addressed in this study. A sample of 228 educated adults between ages 21 and 62 years was given an array of tests that focused on a broad assessment of intelligence-as-knowledge, traditional estimates of fluid intelligence (Gf) and crystallized intelligence (Gc), personality, and interests. The results indicate that middle-aged adults are more knowledgeable in many domains, compared with younger adults. A coherent pattern of ability, personality, and interest relations is found. The results are consistent with a developmental perspective of intelligence that includes both traditional ability and non-ability determinants of intelligence during adulthood. A reassessment of the nature of intelligence in adulthood is provided, in the context of a lifelong learning and investment model, called PPIK, for intelligence-as-Process, Personality, Interests, and intelligence-as-Knowledge (Ackerman, 1996).

Intelligent Learning Infrastructure for Knowledge Intensive Organizations: A Semantic Web Perspective

Science.gov (United States)

Lytras, Miltiadis, Ed.; Naeve, Ambjorn, Ed.

2005-01-01

In the context of Knowledge Society, the convergence of knowledge and learning management is a critical milestone. "Intelligent Learning Infrastructure for Knowledge Intensive Organizations: A Semantic Web Perspective" provides state-of-the art knowledge through a balanced theoretical and technological discussion. The semantic web perspective…

Evaluating Quality of Chatbots and Intelligent Conversational Agents

OpenAIRE

Radziwill, Nicole M.; Benton, Morgan C.

2017-01-01

Chatbots are one class of intelligent, conversational software agents activated by natural language input (which can be in the form of text, voice, or both). They provide conversational output in response, and if commanded, can sometimes also execute tasks. Although chatbot technologies have existed since the 1960s and have influenced user interface development in games since the early 1980s, chatbots are now easier to train and implement. This is due to plentiful open source code, widely ava...

Intelligent personal navigator supported by knowledge-based systems for estimating dead reckoning navigation parameters

Science.gov (United States)

Moafipoor, Shahram

Personal navigators (PN) have been studied for about a decade in different fields and applications, such as safety and rescue operations, security and emergency services, and police and military applications. The common goal of all these applications is to provide precise and reliable position, velocity, and heading information of each individual in various environments. In the PN system developed in this dissertation, the underlying assumption is that the system does not require pre-existing infrastructure to enable pedestrian navigation. To facilitate this capability, a multisensor system concept, based on the Global Positioning System (GPS), inertial navigation, barometer, magnetometer, and a human pedometry model has been developed. An important aspect of this design is to use the human body as navigation sensor to facilitate Dead Reckoning (DR) navigation in GPS-challenged environments. The system is designed predominantly for outdoor environments, where occasional loss of GPS lock may happen; however, testing and performance demonstration have been extended to indoor environments. DR navigation is based on a relative-measurement approach, with the key idea of integrating the incremental motion information in the form of step direction (SD) and step length (SL) over time. The foundation of the intelligent navigation system concept proposed here rests in exploiting the human locomotion pattern, as well as change of locomotion in varying environments. In this context, the term intelligent navigation represents the transition from the conventional point-to-point DR to dynamic navigation using the knowledge about the mechanism of the moving person. This approach increasingly relies on integrating knowledge-based systems (KBS) and artificial intelligence (AI) methodologies, including artificial neural networks (ANN) and fuzzy logic (FL). In addition, a general framework of the quality control for the real-time validation of the DR processing is proposed, based on a

The Construction of Intelligent English Teaching Model Based on Artificial Intelligence

Directory of Open Access Journals (Sweden)

Xiaoguang Li

2017-12-01

Full Text Available In order to build a modernized tool platform that can help students improve their English learning efficiency according to their mastery of knowledge and personality, this paper develops an online intelligent English learning system that uses Java and artificial intelligence language Prolog as the software system. This system is a creative reflection of the thoughts of expert system in artificial intelligence. Established on the Struts Spring Hibernate lightweight JavaEE framework, the system modules are coupled with each other in a much lower degree, which is convenient to future function extension. Combined with the idea of expert system in artificial intelligence, the system developed appropriate learning strategies to help students double the learning effect with half the effort; Finally, the system takes into account the forgetting curve of memory, on which basis the knowledge that has been learned will be tested periodically, intending to spare students’ efforts to do a sea of exercises and obtain better learning results.

Towards Intelligence and Flexibility of Learning and Knowledge Testing Environments

Directory of Open Access Journals (Sweden)

Nerijus AUKSTAKALNIS

2006-02-01

Full Text Available The proposed goal oriented knowledge acquisition and assessment are based on the flexible educational model and allows to implement an adaptive control of the enhanced learning process according to the requirements of student's knowledge level, his state of cognition and subject learning history. The enhanced learner knowledge model specifies how the cognition state of the user will be achieved step by step. The use case actions definition is a starting point of the specification, which depends on different levels of learning scenarios and user cognition sub goals. The use case actions specification is used as a basis to set the requirements for service software specification and attributes of learning objects respectively. The paper presents the enhanced architecture of the student self-evaluation and on-line assessment system TestTool. The system is explored as an assessment engine capable of supporting and improving the individualized intelligent goal oriented self-instructional and simulation based mode of learning, grounded on the GRID distributed service architecture.

Experiments in Knowledge Refinement for a Large Rule-Based System

Science.gov (United States)

1993-08-01

empirical analysis to refine expert system knowledge bases. Aritificial Intelligence , 22:23-48, 1984. *! ...The Addison- Weslev series in artificial intelligence . Addison-Weslev. Reading, Massachusetts. 1981. Cooke, 1991: ttoger M. Cooke. Experts in...ment for classification systems. Artificial Intelligence , 35:197-226, 1988. 14 Overall, we believe that it will be possible to build a heuristic system

Large-scale agent-based social simulation : A study on epidemic prediction and control

NARCIS (Netherlands)

Zhang, M.

2016-01-01

Large-scale agent-based social simulation is gradually proving to be a versatile methodological approach for studying human societies, which could make contributions from policy making in social science, to distributed artificial intelligence and agent technology in computer science, and to theory

Towards a People-Oriented Knowledge Management Environment

NARCIS (Netherlands)

Dignum, V.

2000-01-01

In this preliminary report we present ongoing research on intelligent knowledge management (KM) environments supporting communication in a virtual environment. An agent community handles the interaction between knowledge sources of different degrees of formality and knowledge users and

How People Interact with Technology based on Natural and Artificial Intelligence

Directory of Open Access Journals (Sweden)

Vasile MAZILESCU

2017-04-01

Full Text Available This paper aims to analyse the different forms of intelligence within organizations in a systemic and inclusive vision, in order to design an integrated environment based on Artificial Intelligence (AI and Collective Intelligence (CI. This way we effectively shift the classical approaches of connecting people with people using collaboration tools (which allow people to work together, such as videoconferencing or email, groupware in virtual space, forums, workflow, of connecting people with a series of content management knowledge (taxonomies and documents classification, ontologies or thesauri, search engines, portals, to the current approaches of connecting people on the use (automatic of operational knowledge to solve problems and make decisions based on intellectual cooperation. Few technologies have the big potential to review how we live, move, and work. Artificial intelligence (AI is nowdays equivalent of electricity and the Internet. AI is expected to bring massive shifts in how people perceive and interact with technology, with machines performing a wider range of tasks, in many cases doing a better job than humans.

From conventional software based systems to knowledge based systems

International Nuclear Information System (INIS)

Bologna, S.

1995-01-01

Even if todays nuclear power plants have a very good safety record, there is a continuous search for still improving safety. One direction of this effort address operational safety, trying to improve the handling of disturbances and accidents partly by further automation, partly by creating a better control room environment, providing the operator with intelligent support systems to help in the decision making process. Introduction of intelligent computerised operator support systems has proved to be an efficient way of improving the operators performance. A number of systems have been developed worldwide, assisting in tasks like process fault detection and diagnosis, selection and implementation of proper remedial actions. Unfortunately, the use of Knowledge Based Systems (KBSs), introduces a new dimension to the problem of the licensing process. KBSs, despite the different technology employed, are still nothing more than a computer program. Unfortunately, quite a few people building knowledge based systems seem to ignore the many good programming practices that have evolved over the years for producing traditional computer programs. In this paper the author will try to point out similarities and differences between conventional software based systems, and knowledge based systems, introducing also the concept of model based reasoning. (orig.) (25 refs., 2 figs.)

9th KES Conference on Agent and Multi-Agent Systems : Technologies and Applications

CERN Document Server

Howlett, Robert; Jain, Lakhmi

2015-01-01

Agents and multi-agent systems are related to a modern software paradigm which has long been recognized as a promising technology for constructing autonomous, complex and intelligent systems. The topics covered in this volume include agent-oriented software engineering, agent co-operation, co-ordination, negotiation, organization and communication, distributed problem solving, specification of agent communication languages, agent privacy, safety and security, formalization of ontologies and conversational agents. The volume highlights new trends and challenges in agent and multi-agent research and includes 38 papers classified in the following specific topics: learning paradigms, agent-based modeling and simulation, business model innovation and disruptive technologies, anthropic-oriented computing, serious games and business intelligence, design and implementation of intelligent agents and multi-agent systems, digital economy, and advances in networked virtual enterprises. Published p...

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. 

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. 

INTELLIGENT AUTOMATED SYSTEM OF CONTROL OF KNOWLEDGE: LINGUISTIC SUBSYSTEM

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I. Katerynchuk

2010-08-01

Full Text Available A flowchart linguistic structure (morfological, syntactical, semantic and pragmatic analysis of sentences of the automated system of control of intellectual knowledge. The model of artificial intelligence recognition and evaluation of textual answers.

R&D networks and regional knowledge production: an agent-based simulation of the Austrian competence centres programme

Directory of Open Access Journals (Sweden)

Manuela Korber

2014-06-01

Full Text Available Publicly funded competence centres have gained high recognition for improving science-industry collaboration. With the requirement for long-term and geographically concentrated R&D, competence centres provide an environment for joint learning and transfer of “sticky” knowledge. The objective of this paper is to investigate how a competence centres programme affects knowledge production in the regional innovation system. In order to address this issue, we draw on a simulation approach and develop an agent-based model of the Vienna Life Sciences innovation system. Companies, research organisations and universities are heterogeneous agents that create scientific publications, patents, as well as high-tech jobs. Simulation runs refer to long-term scenarios regarding the level and duration of public funding. By addressing the complexities of knowledge interaction in the context of the “local buzz” versus “global pipelines” discussion, the results show the potential of empirically calibrated simulation models for ex-ante impact assessment in R&D policy.

An Innovative Thinking-Based Intelligent Information Fusion Algorithm

Directory of Open Access Journals (Sweden)

Huimin Lu

2013-01-01

Full Text Available This study proposes an intelligent algorithm that can realize information fusion in reference to the relative research achievements in brain cognitive theory and innovative computation. This algorithm treats knowledge as core and information fusion as a knowledge-based innovative thinking process. Furthermore, the five key parts of this algorithm including information sense and perception, memory storage, divergent thinking, convergent thinking, and evaluation system are simulated and modeled. This algorithm fully develops innovative thinking skills of knowledge in information fusion and is a try to converse the abstract conception of brain cognitive science to specific and operable research routes and strategies. Furthermore, the influences of each parameter of this algorithm on algorithm performance are analyzed and compared with those of classical intelligent algorithms trough test. Test results suggest that the algorithm proposed in this study can obtain the optimum problem solution by less target evaluation times, improve optimization effectiveness, and achieve the effective fusion of information.

A New Dimension of Business Intelligence: Location-based Intelligence

OpenAIRE

Zeljko Panian

2012-01-01

Through the course of this paper we define Locationbased Intelligence (LBI) which is outgrowing from process of amalgamation of geolocation and Business Intelligence. Amalgamating geolocation with traditional Business Intelligence (BI) results in a new dimension of BI named Location-based Intelligence. LBI is defined as leveraging unified location information for business intelligence. Collectively, enterprises can transform location data into business intelligence applic...

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…

MULTIPLE INTELLIGENCES AS PREDICTORS OF READING COMPREHENSION AND VOCABULARY KNOWLEDGE

OpenAIRE

Abbas Ali Zarei; Nima Shokri Afshar

2014-01-01

Abstract: The present study was conducted to investigate types of Multiple Intelligences as predictors of reading comprehension and vocabulary knowledge. To meet this objective, a 60-item TOEFL test and a 90-item multiple intelligences questionnaire were distributed among 240 male and female Iranians studying English at Qazali and Parsian Universities in Qazvin. Data were analyzed using a multiple regression procedure. The result of the data analysis indicated that musical, interpersonal, kin...

Knowledge Base for an Intelligent System in order to Identify Security Requirements for Government Agencies Software Projects

Directory of Open Access Journals (Sweden)

Adán Beltrán G.

2016-01-01

Full Text Available It has been evidenced that one of the most common causes in the failure of software security is the lack of identification and specification of requirements for information security, it is an activity with an insufficient importance in the software development or software acquisition We propose the knowledge base of CIBERREQ. CIBERREQ is an intelligent knowledge-based system used for the identification and specification of security requirements in the software development cycle or in the software acquisition. CIBERREQ receives functional software requirements written in natural language and produces non-functional security requirements through a semi-automatic process of risk management. The knowledge base built is formed by an ontology developed collaboratively by experts in information security. In this process has been identified six types of assets: electronic data, physical data, hardware, software, person and service; as well as six types of risk: competitive disadvantage, loss of credibility, economic risks, strategic risks, operational risks and legal sanctions. In addition there are defined 95 vulnerabilities, 24 threats, 230 controls, and 515 associations between concepts. Additionally, automatic expansion was used with Wikipedia for the asset types Software and Hardware, obtaining 7125 and 5894 software and hardware subtypes respectively, achieving thereby an improvement of 10% in the identification of the information assets candidates, one of the most important phases of the proposed system.

Persuasion Model and Its Evaluation Based on Positive Change Degree of Agent Emotion

Science.gov (United States)

Jinghua, Wu; Wenguang, Lu; Hailiang, Meng

For it can meet needs of negotiation among organizations take place in different time and place, and for it can make its course more rationality and result more ideal, persuasion based on agent can improve cooperation among organizations well. Integrated emotion change in agent persuasion can further bring agent advantage of artificial intelligence into play. Emotion of agent persuasion is classified, and the concept of positive change degree is given. Based on this, persuasion model based on positive change degree of agent emotion is constructed, which is explained clearly through an example. Finally, the method of relative evaluation is given, which is also verified through a calculation example.

Emotion based Agent Architectures for Tutoring Systems : The INES Architecture

NARCIS (Netherlands)

Poel, Mannes; op den Akker, Rieks; Heylen, Dirk; Nijholt, Anton; Trappl, Robert

2004-01-01

In this paper we discuss our approach to integrate emotions in the agent based tutoring system INES (Intelligent Nursing Education System). First we discuss the INES system where we emphasize the emotional component of the system. Afterwards we show how a more advanced emotion generation

Emotion based Agent Architectures for Tutoring Systems: The INES Architecture

NARCIS (Netherlands)

Poel, Mannes; op den Akker, Hendrikus J.A.; Heylen, Dirk K.J.; Nijholt, Antinus; Trappl, R.

2004-01-01

In this paper we discuss our approach to integrate emotions in the agent based tutoring system INES (Intelligent Nursing Education System). First we discuss the INES system where we emphasize the emotional component of the system. Afterwards we show how a more advanced emotion generation

Knowledge management, business intelligence, and content management the IT practitioner's guide

CERN Document Server

Keyes, Jessica

2006-01-01

The New Intelligence: The Birth of the KnowledgeManagement Industry Buried in Information From Batch to Decision Support A Short Course in Knowledge Representation Data, Information, Knowledge, and Wisdom - and Why WeNeed to Do This Embedding Knowledge Management in the OrganizationWhere Do We Go Next?Knowledge Management Transfer Strategies KM Frameworks Knowledge Transfer TechniquesWhere Do We Go Next?Knowledge-Engineering Techniques Two Levels of Knowledge ElicitationA Knowledge-Engineering MethodologyWhere Do We Go Next? Innovation ManagementSources of InnovationGenerating Innovation Compu

Knowledge base technology: a developer view

Directory of Open Access Journals (Sweden)

G. Ginkul

1996-09-01

Full Text Available In present paper we have endeavoured to tell about some reasonings, conclusions and pricticals results, to which we have come being busy with one of most interesting problems of modern science. This paper is a brief report of the group of scientists from the Laboratory of Artificial Intelligence Systems about their experience of work in the field of knowledge engineering. The researches in this area was started in our Laboratory more than 10 years ago, i.e. about in the moment, when there was just another rise in Artificial Intelligence, caused by mass emerging of expert systems. The tasks of knowledge engineering were being varied, and focal point of our researches was being varied too. Certainly, we have not solved all the problems, originating in this area. Our knowledge still has an approximate nature, but nevertheless, the outcomes obtained by us seem rather important and interesting. So, we want to tell about our experience in building of knowledge-based systems, and expert systems, in particular.

5th International Conference on Computational Collective Intelligence

CERN Document Server

Trawinski, Bogdan; Nguyen, Ngoc

2014-01-01

The book consists of 19 extended and revised chapters based on original works presented during a poster session organized within the 5th International Conference on Computational Collective Intelligence that was held between 11 and 13 of September 2013 in Craiova, Romania. The book is divided into three parts. The first part is titled “Agents and Multi-Agent Systems” and consists of 8 chapters that concentrate on many problems related to agent and multi-agent systems, including: formal models, agent autonomy, emergent properties, agent programming, agent-based simulation and planning. The second part of the book is titled “Intelligent Computational Methods” and consists of 6 chapters. The authors present applications of various intelligent computational methods like neural networks, mathematical optimization and multistage decision processes in areas like cooperation, character recognition, wireless networks, transport, and metal structures. The third part of the book is titled “Language and Knowled...

An empirical investigation on relationship between organizational intelligence and faculty members' knowledge sharing behaviors

Directory of Open Access Journals (Sweden)

Masoomeh Arabshahi

2013-11-01

Full Text Available Universities and institutions of higher education with a professional, special, educational and cultural environment play important roles in the direction towards the effective management of knowledge and space provision for the sharing of knowledge. Faculty members are known as the main elements of the university and they are the mental and intellectual investment banks who share their knowledge under certain conditions. In addition, their knowledge sharing behaviors lead to the success and improvement of individual and organizational operations. Moreover, organizational intelligence is the capacity of the organization to create knowledge and to use it in a strategic way to coordinate and to conform itself to its surroundings. This study examines the impact of organizational intelligence on faculty members' knowledge sharing behaviors. Data collection for qualitative research includes interviews with experts and quantitative research is performed using a questionnaire. The research results show that there was a significant relationship between organizational intelligence and faculty members' knowledge sharing behaviors. Among these dimensions, “knowledge application” influenced other dimensions. On the other hand, “common outcome” had a significant relationship with the “behavioral” dimension and “special and professional activities”.

Writing cases as a knowledge capture process in a competitive intelligence program

OpenAIRE

Mallowan , Monica; Marcon , Christian

2009-01-01

International audience; Students in Competitive Intelligence (CI) programs submit a report following their internship in an organisation. It is proposed that the result of their experiences be shared with their peers, in the form of cases written for in-class analysis. A knowledge base is thus created, which gradually becomes the program's memory and, by its constant renewal and connection with the reality, the most useful teaching tool for the professor.

PROMOTING THE MANAGEMENT BASED ON KNOWLEDGE IN THE ROMANIAN ORGANIZATIONAL ENVIRONMENT

Directory of Open Access Journals (Sweden)

Alin NIOAȚĂ

2012-05-01

Full Text Available The organizations based on knowledge are intelligent collective actors of the informational society and they are determinant for affirming it as a knowledge society; belonging to the contemporary reality both as an environment of professional and managerial environment and as an object of scientific research and strategic project, they mark the convergence between two phenomena defining the human nature – the knowledge one and the organization one – in a symbolic social construction for the ideas of collective competence, intelligent action and sustainable performance.

Constructing and Refining Knowledge Bases: A Collaborative Apprenticeship Multistrategy Learning Approach

National Research Council Canada - National Science Library

Tecuci, Gheorghe

2000-01-01

This research has developed a theory, methodology and learning agent shell for development of knowledge bases and knowledge-based agents, by domain experts, with limited assistance from knowledge engineers...

Intelligent Learning for Knowledge Graph towards Geological Data

Directory of Open Access Journals (Sweden)

Yueqin Zhu

2017-01-01

Full Text Available Knowledge graph (KG as a popular semantic network has been widely used. It provides an effective way to describe semantic entities and their relationships by extending ontology in the entity level. This article focuses on the application of KG in the traditional geological field and proposes a novel method to construct KG. On the basis of natural language processing (NLP and data mining (DM algorithms, we analyze those key technologies for designing a KG towards geological data, including geological knowledge extraction and semantic association. Through this typical geological ontology extracting on a large number of geological documents and open linked data, the semantic interconnection is achieved, KG framework for geological data is designed, application system of KG towards geological data is constructed, and dynamic updating of the geological information is completed accordingly. Specifically, unsupervised intelligent learning method using linked open data is incorporated into the geological document preprocessing, which generates a geological domain vocabulary ultimately. Furthermore, some application cases in the KG system are provided to show the effectiveness and efficiency of our proposed intelligent learning approach for KG.

Community Intelligence in Knowledge Curation: An Application to Managing Scientific Nomenclature

OpenAIRE

Dai, Lin; Xu, Chao; Tian, Ming; Sang, Jian; Zou, Dong; Li, Ang; Liu, Guocheng; Chen, Fei; Wu, Jiayan; Xiao, Jingfa; Wang, Xumin; Yu, Jun; Zhang, Zhang

2013-01-01

Harnessing community intelligence in knowledge curation bears significant promise in dealing with communication and education in the flood of scientific knowledge. As knowledge is accumulated at ever-faster rates, scientific nomenclature, a particular kind of knowledge, is concurrently generated in all kinds of fields. Since nomenclature is a system of terms used to name things in a particular discipline, accurate translation of scientific nomenclature in different languages is of critical im...

Instructable autonomous agents. Ph.D. Thesis

Science.gov (United States)

Huffman, Scott Bradley

1994-01-01

In contrast to current intelligent systems, which must be laboriously programmed for each task they are meant to perform, instructable agents can be taught new tasks and associated knowledge. This thesis presents a general theory of learning from tutorial instruction and its use to produce an instructable agent. Tutorial instruction is a particularly powerful form of instruction, because it allows the instructor to communicate whatever kind of knowledge a student needs at whatever point it is needed. To exploit this broad flexibility, however, a tutorable agent must support a full range of interaction with its instructor to learn a full range of knowledge. Thus, unlike most machine learning tasks, which target deep learning of a single kind of knowledge from a single kind of input, tutorability requires a breadth of learning from a broad range of instructional interactions. The theory of learning from tutorial instruction presented here has two parts. First, a computational model of an intelligent agent, the problem space computational model, indicates the types of knowledge that determine an agent's performance, and thus, that should be acquirable via instruction. Second, a learning technique, called situated explanation specifies how the agent learns general knowledge from instruction. The theory is embodied by an implemented agent, Instructo-Soar, built within the Soar architecture. Instructo-Soar is able to learn hierarchies of completely new tasks, to extend task knowledge to apply in new situations, and in fact to acquire every type of knowledge it uses during task performance - control knowledge, knowledge of operators' effects, state inferences, etc. - from interactive natural language instructions. This variety of learning occurs by applying the situated explanation technique to a variety of instructional interactions involving a variety of types of instructions (commands, statements, conditionals, etc.). By taking seriously the requirements of flexible

Neuroprotective Drug for Nerve Trauma Revealed Using Artificial Intelligence

OpenAIRE

Romeo-Guitart, David; Forés, Joaquim; Herrando-Grabulosa, Mireia; Valls, Raquel; Leiva-Rodríguez, Tatiana; Galea, Elena; González-Pérez, Francisco; Navarro, Xavier; Petegnief, Valerie; Bosch, Assumpció; Coma, Mireia; Mas, José Manuel; Casas, Caty

2018-01-01

Here we used a systems biology approach and artificial intelligence to identify a neuroprotective agent for the treatment of peripheral nerve root avulsion. Based on accumulated knowledge of the neurodegenerative and neuroprotective processes that occur in motoneurons after root avulsion, we built up protein networks and converted them into mathematical models. Unbiased proteomic data from our preclinical models were used for machine learning algorithms and for restrictions to be imposed on m...

Automated knowledge acquisition for second generation knowledge base systems: A conceptual analysis and taxonomy

Energy Technology Data Exchange (ETDEWEB)

Williams, K.E.; Kotnour, T.

1991-01-01

In this paper, we present a conceptual analysis of knowledge-base development methodologies. The purpose of this research is to help overcome the high cost and lack of efficiency in developing knowledge base representations for artificial intelligence applications. To accomplish this purpose, we analyzed the available methodologies and developed a knowledge-base development methodology taxonomy. We review manual, machine-aided, and machine-learning methodologies. A set of developed characteristics allows description and comparison among the methodologies. We present the results of this conceptual analysis of methodologies and recommendations for development of more efficient and effective tools.

Automated knowledge acquisition for second generation knowledge base systems: A conceptual analysis and taxonomy

Energy Technology Data Exchange (ETDEWEB)

Williams, K.E.; Kotnour, T.

1991-12-31

In this paper, we present a conceptual analysis of knowledge-base development methodologies. The purpose of this research is to help overcome the high cost and lack of efficiency in developing knowledge base representations for artificial intelligence applications. To accomplish this purpose, we analyzed the available methodologies and developed a knowledge-base development methodology taxonomy. We review manual, machine-aided, and machine-learning methodologies. A set of developed characteristics allows description and comparison among the methodologies. We present the results of this conceptual analysis of methodologies and recommendations for development of more efficient and effective tools.

An agent-based intelligent environmental monitoring system

OpenAIRE

Athanasiadis, Ioannis N; Mitkas, Pericles A

2004-01-01

Fairly rapid environmental changes call for continuous surveillance and on-line decision making. There are two main areas where IT technologies can be valuable. In this paper we present a multi-agent system for monitoring and assessing air-quality attributes, which uses data coming from a meteorological station. A community of software agents is assigned to monitor and validate measurements coming from several sensors, to assess air-quality, and, finally, to fire alarms to appropriate recipie...

Fault Reconnaissance Agent for Sensor Networks

Directory of Open Access Journals (Sweden)

Elhadi M. Shakshuki

2010-01-01

Full Text Available One of the key prerequisite for a scalable, effective and efficient sensor network is the utilization of low-cost, low-overhead and high-resilient fault-inference techniques. To this end, we propose an intelligent agent system with a problem solving capability to address the issue of fault inference in sensor network environments. The intelligent agent system is designed and implemented at base-station side. The core of the agent system – problem solver – implements a fault-detection inference engine which harnesses Expectation Maximization (EM algorithm to estimate fault probabilities of sensor nodes. To validate the correctness and effectiveness of the intelligent agent system, a set of experiments in a wireless sensor testbed are conducted. The experimental results show that our intelligent agent system is able to precisely estimate the fault probability of sensor nodes.

Knowledge creation using artificial intelligence: a twin approach to improve breast screening attendance.

Science.gov (United States)

Baskaran, Vikraman; Bali, Rajeev K; Arochena, Hisbel; Naguib, Rauf N G; Wallis, Matthew; Wheaton, Margot

2006-01-01

Knowledge management (KM) is rapidly becoming established as a core organizational element within the healthcare industry to assist in the delivery of better patient care. KM is a cyclical process which typically starts with knowledge creation (KC), progresses to knowledge sharing, knowledge accessibility and eventually results in new KC (in the same or a related domain). KC plays a significant role in KM as it creates the necessary "seeds" for propagating many more knowledge cycles. This paper addresses the potential of KC in the context of the UK's National Health Service (NHS) breast screening service. KC can be automated to a greater extent by embedding processes within an artificial intelligence (AI) based environment. The UK breast screening service is concerned about non-attendance and this paper discusses issues pertaining to increasing attendance.

Use of Agent Based Modelling to Investigate the Dynamics of Slum ...

African Journals Online (AJOL)

Urban planners and policy makers face challenges in effective management of slum ... slum characteristics using various remote sensing and artificial intelligence ... an empirically informed agent based prototype that can simulate future patterns ... The study incorporates physical, environmental, social and economic factors ...

Knowledge-based diagnosis for aerospace systems

Science.gov (United States)

Atkinson, David J.

1988-01-01

The need for automated diagnosis in aerospace systems and the approach of using knowledge-based systems are examined. Research issues in knowledge-based diagnosis which are important for aerospace applications are treated along with a review of recent relevant research developments in Artificial Intelligence. The design and operation of some existing knowledge-based diagnosis systems are described. The systems described and compared include the LES expert system for liquid oxygen loading at NASA Kennedy Space Center, the FAITH diagnosis system developed at the Jet Propulsion Laboratory, the PES procedural expert system developed at SRI International, the CSRL approach developed at Ohio State University, the StarPlan system developed by Ford Aerospace, the IDM integrated diagnostic model, and the DRAPhys diagnostic system developed at NASA Langley Research Center.

Project X: competitive intelligence data mining and analysis

Science.gov (United States)

Gilmore, John F.; Pagels, Michael A.; Palk, Justin

2001-03-01

Competitive Intelligence (CI) is a systematic and ethical program for gathering and analyzing information about your competitors' activities and general business trends to further your own company's goals. CI allows companies to gather extensive information on their competitors and to analyze what the competition is doing in order to maintain or gain a competitive edge. In commercial business this potentially translates into millions of dollars in annual savings or losses. The Internet provides an overwhelming portal of information for CI analysis. The problem is how a company can automate the translation of voluminous information into valuable and actionable knowledge. This paper describes Project X, an agent-based data mining system specifically developed for extracting and analyzing competitive information from the Internet. Project X gathers CI information from a variety of sources including online newspapers, corporate websites, industry sector reporting sites, speech archiving sites, video news casts, stock news sites, weather sites, and rumor sites. It uses individual industry specific (e.g., pharmaceutical, financial, aerospace, etc.) commercial sector ontologies to form the knowledge filtering and discovery structures/content required to filter and identify valuable competitive knowledge. Project X is described in detail and an example competitive intelligence case is shown demonstrating the system's performance and utility for business intelligence.

Knowledge Discovery, Integration and Communication for Extreme Weather and Flood Resilience Using Artificial Intelligence: Flood AI Alpha

Science.gov (United States)

Demir, I.; Sermet, M. Y.

2016-12-01

Nobody is immune from extreme events or natural hazards that can lead to large-scale consequences for the nation and public. One of the solutions to reduce the impacts of extreme events is to invest in improving resilience with the ability to better prepare, plan, recover, and adapt to disasters. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This abstracts presents our project on developing a resilience framework for flooding to improve societal preparedness with objectives; (a) develop a generalized ontology for extreme events with primary focus on flooding; (b) develop a knowledge engine with voice recognition, artificial intelligence, natural language processing, and inference engine. The knowledge engine will utilize the flood ontology and concepts to connect user input to relevant knowledge discovery outputs on flooding; (c) develop a data acquisition and processing framework from existing environmental observations, forecast models, and social networks. The system will utilize the framework, capabilities and user base of the Iowa Flood Information System (IFIS) to populate and test the system; (d) develop a communication framework to support user interaction and delivery of information to users. The interaction and delivery channels will include voice and text input via web-based system (e.g. IFIS), agent-based bots (e.g. Microsoft Skype, Facebook Messenger), smartphone and augmented reality applications (e.g. smart assistant), and automated web workflows (e.g. IFTTT, CloudWork) to open the knowledge discovery for flooding to thousands of community extensible web workflows.

2nd International Conference on Intelligent Computing, Communication & Devices

CERN Document Server

Popentiu-Vladicescu, Florin

2017-01-01

The book presents high quality papers presented at 2nd International Conference on Intelligent Computing, Communication & Devices (ICCD 2016) organized by Interscience Institute of Management and Technology (IIMT), Bhubaneswar, Odisha, India, during 13 and 14 August, 2016. The book covers all dimensions of intelligent sciences in its three tracks, namely, intelligent computing, intelligent communication and intelligent devices. intelligent computing track covers areas such as intelligent and distributed computing, intelligent grid and cloud computing, internet of things, soft computing and engineering applications, data mining and knowledge discovery, semantic and web technology, hybrid systems, agent computing, bioinformatics, and recommendation systems. Intelligent communication covers communication and network technologies, including mobile broadband and all optical networks that are the key to groundbreaking inventions of intelligent communication technologies. This covers communication hardware, soft...

Methodology for testing and validating knowledge bases

Science.gov (United States)

Krishnamurthy, C.; Padalkar, S.; Sztipanovits, J.; Purves, B. R.

1987-01-01

A test and validation toolset developed for artificial intelligence programs is described. The basic premises of this method are: (1) knowledge bases have a strongly declarative character and represent mostly structural information about different domains, (2) the conditions for integrity, consistency, and correctness can be transformed into structural properties of knowledge bases, and (3) structural information and structural properties can be uniformly represented by graphs and checked by graph algorithms. The interactive test and validation environment have been implemented on a SUN workstation.

ISHM-oriented adaptive fault diagnostics for avionics based on a distributed intelligent agent system

Science.gov (United States)

Xu, Jiuping; Zhong, Zhengqiang; Xu, Lei

2015-10-01

In this paper, an integrated system health management-oriented adaptive fault diagnostics and model for avionics is proposed. With avionics becoming increasingly complicated, precise and comprehensive avionics fault diagnostics has become an extremely complicated task. For the proposed fault diagnostic system, specific approaches, such as the artificial immune system, the intelligent agents system and the Dempster-Shafer evidence theory, are used to conduct deep fault avionics diagnostics. Through this proposed fault diagnostic system, efficient and accurate diagnostics can be achieved. A numerical example is conducted to apply the proposed hybrid diagnostics to a set of radar transmitters on an avionics system and to illustrate that the proposed system and model have the ability to achieve efficient and accurate fault diagnostics. By analyzing the diagnostic system's feasibility and pragmatics, the advantages of this system are demonstrated.

A general framework for intelligent recommender systems

Directory of Open Access Journals (Sweden)

Jose Aguilar

2017-07-01

Full Text Available In this paper, we propose a general framework for an intelligent recommender system that extends the concept of a knowledge-based recommender system. The intelligent recommender system exploits knowledge, learns, discovers new information, infers preferences and criticisms, among other things. For that, the framework of an intelligent recommender system is defined by the following components: knowledge representation paradigm, learning methods, and reasoning mechanisms. Additionally, it has five knowledge models about the different aspects that we can consider during a recommendation: users, items, domain, context and criticisms. The mix of the components exploits the knowledge, updates it and infers, among other things. In this work, we implement one intelligent recommender system based on this framework, using Fuzzy Cognitive Maps (FCMs. Next, we test the performance of the intelligent recommender system with specialized criteria linked to the utilization of the knowledge in order to test the versatility and performance of the framework.

Domain-based Teaching Strategy for Intelligent Tutoring System Based on Generic Rules

Science.gov (United States)

Kseibat, Dawod; Mansour, Ali; Adjei, Osei; Phillips, Paul

In this paper we present a framework for selecting the proper instructional strategy for a given teaching material based on its attributes. The new approach is based on a flexible design by means of generic rules. The framework was adapted in an Intelligent Tutoring System to teach Modern Standard Arabic language to adult English-speaking learners with no pre-knowledge of Arabic language is required.

KNOWLEDGE AND XML BASED CAPP SYSTEM

Institute of Scientific and Technical Information of China (English)

ZHANG Shijie; SONG Laigang

2006-01-01

In order to enhance the intelligent level of system and improve the interactivity with other systems, a knowledge and XML based computer aided process planning (CAPP) system is implemented. It includes user management, bill of materials(BOM) management, knowledge based process planning, knowledge management and database maintaining sub-systems. This kind of nesting knowledge representation method the system provided can represent complicated arithmetic and logical relationship to deal with process planning tasks. With the representation and manipulation of XML based technological file, the system solves some important problems in web environment such as information interactive efficiency and refreshing of web page. The CAPP system is written in ASP VBScript, JavaScript, Visual C++ languages and Oracle database. At present, the CAPP system is running in Shenyang Machine Tools. The functions of it meet the requirements of enterprise production.

Towards Intelligently - Sustainable Cities? From Intelligent and Knowledge City Programmes to the Achievement of Urban Sustainability

NARCIS (Netherlands)

Gargiulo Morelli, V.; Weijnen, M.P.C.; Van Bueren, E.M.; Wenzler, I.; De Reuver, G.A.; Salvati, L.

2013-01-01

In the quest for achieving sustainable cities, Intelligent and Knowledge City Programmes (ICPs and KCPs) represent cost-efficient strategies for improving the overall performance of urban systems, especially when compared with the costs of physical restructuring and/or retrofitting projects.

Intelligent management in the knowledge economy

DEFF Research Database (Denmark)

Junghagen, Sven; Linderoth, Henrik

The knowledge economy is a notion that has been used, since the 1990s, to describe a new economic order perceived by scholars and practitioners. The authors argue that this order, triggered by new information and communication technologies, has resulted in a different set of challenges...... for effective management of the contemporary firm. Knowledge will play an important role in managing these challenges, with the onus being on new hardware and software as much as how businesses can be organized with regard to relationships with customers and suppliers. This volume shows how "intelligent...... management will be the key to how internal operations can be organized, in order to take advantage of opportunities brought about by new technologies. This change in management is discussed throughout the book from a wide array of perspectives ranging from contextual and philosophical aspects, through tools...

Managing knowledge business intelligence: A cognitive analytic approach

Science.gov (United States)

Surbakti, Herison; Ta'a, Azman

2017-10-01

The purpose of this paper is to identify and analyze integration of Knowledge Management (KM) and Business Intelligence (BI) in order to achieve competitive edge in context of intellectual capital. Methodology includes review of literatures and analyzes the interviews data from managers in corporate sector and models established by different authors. BI technologies have strong association with process of KM for attaining competitive advantage. KM have strong influence from human and social factors and turn them to the most valuable assets with efficient system run under BI tactics and technologies. However, the term of predictive analytics is based on the field of BI. Extracting tacit knowledge is a big challenge to be used as a new source for BI to use in analyzing. The advanced approach of the analytic methods that address the diversity of data corpus - structured and unstructured - required a cognitive approach to provide estimative results and to yield actionable descriptive, predictive and prescriptive results. This is a big challenge nowadays, and this paper aims to elaborate detail in this initial work.

Artificial intelligence and the future.

Science.gov (United States)

Clocksin, William F

2003-08-15

We consider some of the ideas influencing current artificial-intelligence research and outline an alternative conceptual framework that gives priority to social relationships as a key component and constructor of intelligent behaviour. The framework starts from Weizenbaum's observation that intelligence manifests itself only relative to specific social and cultural contexts. This is in contrast to a prevailing view, which sees intelligence as an abstract capability of the individual mind based on a mechanism for rational thought. The new approach is not based on the conventional idea that the mind is a rational processor of symbolic information, nor does it require the idea that thought is a kind of abstract problem solving with a semantics that is independent of its embodiment. Instead, priority is given to affective and social responses that serve to engage the whole agent in the life of the communities in which it participates. Intelligence is seen not as the deployment of capabilities for problem solving, but as constructed by the continual, ever-changing and unfinished engagement with the social group within the environment. The construction of the identity of the intelligent agent involves the appropriation or 'taking up' of positions within the conversations and narratives in which it participates. Thus, the new approach argues that the intelligent agent is shaped by the meaning ascribed to experience, by its situation in the social matrix, and by practices of self and of relationship into which intelligent life is recruited. This has implications for the technology of the future, as, for example, classic artificial intelligence models such as goal-directed problem solving are seen as special cases of narrative practices instead of as ontological foundations.

Intelligent Information Fusion in the Aviation Domain: A Semantic-Web based Approach

Science.gov (United States)

Ashish, Naveen; Goforth, Andre

2005-01-01

Information fusion from multiple sources is a critical requirement for System Wide Information Management in the National Airspace (NAS). NASA and the FAA envision creating an "integrated pool" of information originally coming from different sources, which users, intelligent agents and NAS decision support tools can tap into. In this paper we present the results of our initial investigations into the requirements and prototype development of such an integrated information pool for the NAS. We have attempted to ascertain key requirements for such an integrated pool based on a survey of DSS tools that will benefit from this integrated pool. We then advocate key technologies from computer science research areas such as the semantic web, information integration, and intelligent agents that we believe are well suited to achieving the envisioned system wide information management capabilities.

Towards the internet of agents: an analysis of the internet of things from the intelligence and autonomy perspective

Directory of Open Access Journals (Sweden)

Pablo Antonio Pico Valencia

2018-01-01

Full Text Available Recently, the scientific community has demonstrated a special interest in the process related to the integration of the agent-oriented technology with Internet of Things (IoT platforms. Then, it arises a novel approach named Internet of Agents (IoA as an alternative to add an intelligence and autonomy component for IoT devices and networks. This paper presents an analysis of the main benefits derived from the use of the IoA approach, based on a practical point of view regarding the necessities that humans demand in their daily life and work, which can be solved by IoT networks modeled as IoA infrastructures. It has been presented 24 study cases of the IoA approach at different domains ––smart industry, smart city and smart health wellbeing–– in order to define the scope of these proposals in terms of intelligence and autonomy in contrast to their corresponding generic IoT applications.

Artificial Intelligence and Moral intelligence

OpenAIRE

Laura Pana

2008-01-01

We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined,...

Rule-based statistical data mining agents for an e-commerce application

Science.gov (United States)

Qin, Yi; Zhang, Yan-Qing; King, K. N.; Sunderraman, Rajshekhar

2003-03-01

Intelligent data mining techniques have useful e-Business applications. Because an e-Commerce application is related to multiple domains such as statistical analysis, market competition, price comparison, profit improvement and personal preferences, this paper presents a hybrid knowledge-based e-Commerce system fusing intelligent techniques, statistical data mining, and personal information to enhance QoS (Quality of Service) of e-Commerce. A Web-based e-Commerce application software system, eDVD Web Shopping Center, is successfully implemented uisng Java servlets and an Oracle81 database server. Simulation results have shown that the hybrid intelligent e-Commerce system is able to make smart decisions for different customers.

Ontology-Based Information Extraction for Business Intelligence

Science.gov (United States)

Saggion, Horacio; Funk, Adam; Maynard, Diana; Bontcheva, Kalina

Business Intelligence (BI) requires the acquisition and aggregation of key pieces of knowledge from multiple sources in order to provide valuable information to customers or feed statistical BI models and tools. The massive amount of information available to business analysts makes information extraction and other natural language processing tools key enablers for the acquisition and use of that semantic information. We describe the application of ontology-based extraction and merging in the context of a practical e-business application for the EU MUSING Project where the goal is to gather international company intelligence and country/region information. The results of our experiments so far are very promising and we are now in the process of building a complete end-to-end solution.

Future applications of artificial intelligence to Mission Control Centers

Science.gov (United States)

Friedland, Peter

1991-01-01

Future applications of artificial intelligence to Mission Control Centers are presented in the form of the viewgraphs. The following subject areas are covered: basic objectives of the NASA-wide AI program; inhouse research program; constraint-based scheduling; learning and performance improvement for scheduling; GEMPLAN multi-agent planner; planning, scheduling, and control; Bayesian learning; efficient learning algorithms; ICARUS (an integrated architecture for learning); design knowledge acquisition and retention; computer-integrated documentation; and some speculation on future applications.

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

This paper is focused on a multi-agent system based event-triggered hybrid control for intelligently restructuring the operating mode of an microgrid (MG) to ensure the energy supply with high security, stability and cost effectiveness. Due to the microgrid is composed of different types...... 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...

Knowledge-based control of an adaptive interface

Science.gov (United States)

Lachman, Roy

1989-01-01

The analysis, development strategy, and preliminary design for an intelligent, adaptive interface is reported. The design philosophy couples knowledge-based system technology with standard human factors approaches to interface development for computer workstations. An expert system has been designed to drive the interface for application software. The intelligent interface will be linked to application packages, one at a time, that are planned for multiple-application workstations aboard Space Station Freedom. Current requirements call for most Space Station activities to be conducted at the workstation consoles. One set of activities will consist of standard data management services (DMS). DMS software includes text processing, spreadsheets, data base management, etc. Text processing was selected for the first intelligent interface prototype because text-processing software can be developed initially as fully functional but limited with a small set of commands. The program's complexity then can be increased incrementally. The intelligent interface includes the operator's behavior and three types of instructions to the underlying application software are included in the rule base. A conventional expert-system inference engine searches the data base for antecedents to rules and sends the consequents of fired rules as commands to the underlying software. Plans for putting the expert system on top of a second application, a database management system, will be carried out following behavioral research on the first application. The intelligent interface design is suitable for use with ground-based workstations now common in government, industrial, and educational organizations.

Intelligence, General Knowledge and Personality as Predictors of Creativity

Science.gov (United States)

Batey, Mark; Furnham, Adrian; Safiullina, Xeniya

2010-01-01

This study sought to examine the contribution of fluid intelligence, general knowledge and Big Five personality traits in predicting four indices of creativity: Divergent Thinking (DT) fluency, Rated DT, Creative Achievement and Self-Rated creativity and a combined Total Creativity variable. When creativity was assessed by DT test, the consistent…

An Ambient Intelligent Agent Model for Relapse and Recurrence Monitoring in Unipolar Depression

NARCIS (Netherlands)

Aziz, A.A.; Klein, M.C.A.; Treur, J.; Combi, C.; Shahar, Y.; Abu-Hanna, A.

2009-01-01

Mental healthcare is a prospective area for applying AI techniques. For example, a computerized system could support individuals with a history of depression in maintaining their well-being throughout their lifetime. In this paper, the design of an ambient intelligent agent to support these

Agent planning in AgScala

Science.gov (United States)

Tošić, Saša; Mitrović, Dejan; Ivanović, Mirjana

2013-10-01

Agent-oriented programming languages are designed to simplify the development of software agents, especially those that exhibit complex, intelligent behavior. This paper presents recent improvements of AgScala, an agent-oriented programming language based on Scala. AgScala includes declarative constructs for managing beliefs, actions and goals of intelligent agents. Combined with object-oriented and functional programming paradigms offered by Scala, it aims to be an efficient framework for developing both purely reactive, and more complex, deliberate agents. Instead of the Prolog back-end used initially, the new version of AgScala relies on Agent Planning Package, a more advanced system for automated planning and reasoning.

Knowledge-based simulation using object-oriented programming

Science.gov (United States)

Sidoran, Karen M.

1993-01-01

Simulations have become a powerful mechanism for understanding and modeling complex phenomena. Their results have had substantial impact on a broad range of decisions in the military, government, and industry. Because of this, new techniques are continually being explored and developed to make them even more useful, understandable, extendable, and efficient. One such area of research is the application of the knowledge-based methods of artificial intelligence (AI) to the computer simulation field. The goal of knowledge-based simulation is to facilitate building simulations of greatly increased power and comprehensibility by making use of deeper knowledge about the behavior of the simulated world. One technique for representing and manipulating knowledge that has been enhanced by the AI community is object-oriented programming. Using this technique, the entities of a discrete-event simulation can be viewed as objects in an object-oriented formulation. Knowledge can be factual (i.e., attributes of an entity) or behavioral (i.e., how the entity is to behave in certain circumstances). Rome Laboratory's Advanced Simulation Environment (RASE) was developed as a research vehicle to provide an enhanced simulation development environment for building more intelligent, interactive, flexible, and realistic simulations. This capability will support current and future battle management research and provide a test of the object-oriented paradigm for use in large scale military applications.

Reasoning robots the art and science of programming robotic agents

CERN Document Server

Thielscher, Michael

2005-01-01

The book provides an in-depth and uniform treatment of a mathematical model for reasoning robotic agents. The book also contains an introduction to a programming method and system based on this model. The mathematical model, known as the "Fluent Calculus,'' describes how to use classical first-order logic to set up symbolic models of dynamic worlds and to represent knowledge of actions and their effects. Robotic agents use this knowledge and their reasoning facilities to make decisions when following high-level, long-term strategies. The book covers the issues of reasoning about sensor input, acting under incomplete knowledge and uncertainty, planning, intelligent troubleshooting, and many other topics. The mathematical model is supplemented by a programming method which allows readers to design their own reasoning robotic agents. The usage of this method, called "FLUX,'' is illustrated by many example programs. The book includes the details of an implementation of FLUX using the standard programming language...

A Framework for Intelligent Instructional Systems: An Artificial Intelligence Machine Learning Approach.

Science.gov (United States)

Becker, Lee A.

1987-01-01

Presents and develops a general model of the nature of a learning system and a classification for learning systems. Highlights include the relationship between artificial intelligence and cognitive psychology; computer-based instructional systems; intelligent instructional systems; and the role of the learner's knowledge base in an intelligent…

Recent progress in econophysics: Chaos, leverage, and business cycles as revealed by agent-based modeling and human experiments

Science.gov (United States)

Xin, Chen; Huang, Ji-Ping

2017-12-01

Agent-based modeling and controlled human experiments serve as two fundamental research methods in the field of econophysics. Agent-based modeling has been in development for over 20 years, but how to design virtual agents with high levels of human-like "intelligence" remains a challenge. On the other hand, experimental econophysics is an emerging field; however, there is a lack of experience and paradigms related to the field. Here, we review some of the most recent research results obtained through the use of these two methods concerning financial problems such as chaos, leverage, and business cycles. We also review the principles behind assessments of agents' intelligence levels, and some relevant designs for human experiments. The main theme of this review is to show that by combining theory, agent-based modeling, and controlled human experiments, one can garner more reliable and credible results on account of a better verification of theory; accordingly, this way, a wider range of economic and financial problems and phenomena can be studied.

Recent progress in econophysics: Chaos, leverage,and business cycles as revealed by agent-based modeling and human experiments

Institute of Scientific and Technical Information of China (English)

Chen Xin; Ji-Ping Huang

2017-01-01

Agent-based modeling and controlled human experiments serve as two fundamental research methods in the field of econophysics.Agent-based modeling has been in development for over 20 years,but how to design virtual agents with high levels of human-like "intelligence" remains a challenge.On the other hand,experimental econophysics is an emerging field;however,there is a lack of experience and paradigms related to the field.Here,we review some of the most recent research results obtained through the use of these two methods concerning financial problems such as chaos,leverage,and business cycles.We also review the principles behind assessments of agents' intelligence levels,and some relevant designs for human experiments.The main theme of this review is to show that by combining theory,agent-based modeling,and controlled human experiments,one can garner more reliable and credible results on account of a better verification of theory;accordingly,this way,a wider range of economic and financial problems and phenomena can be studied.

Knowledge-based computer systems for radiotherapy planning.

Science.gov (United States)

Kalet, I J; Paluszynski, W

1990-08-01

Radiation therapy is one of the first areas of clinical medicine to utilize computers in support of routine clinical decision making. The role of the computer has evolved from simple dose calculations to elaborate interactive graphic three-dimensional simulations. These simulations can combine external irradiation from megavoltage photons, electrons, and particle beams with interstitial and intracavitary sources. With the flexibility and power of modern radiotherapy equipment and the ability of computer programs that simulate anything the machinery can do, we now face a challenge to utilize this capability to design more effective radiation treatments. How can we manage the increased complexity of sophisticated treatment planning? A promising approach will be to use artificial intelligence techniques to systematize our present knowledge about design of treatment plans, and to provide a framework for developing new treatment strategies. Far from replacing the physician, physicist, or dosimetrist, artificial intelligence-based software tools can assist the treatment planning team in producing more powerful and effective treatment plans. Research in progress using knowledge-based (AI) programming in treatment planning already has indicated the usefulness of such concepts as rule-based reasoning, hierarchical organization of knowledge, and reasoning from prototypes. Problems to be solved include how to handle continuously varying parameters and how to evaluate plans in order to direct improvements.

An Agent-based Approach for Ideational Support in Learning - Integration and Impact.

NARCIS (Netherlands)

Aroyo, L.M.; Stoyanov, S.; Kommers, Petrus A.M.

1999-01-01

This paper provides results from research work done in respect to the application of agent technology within educational settings. It focuses on problem solving, information handling issues and idea generation. It is based on two research system examples: Solution, Mapping, Intelligent, Learning,

An approach to knowledge dynamic maintenance for emotional agents

OpenAIRE

Fulladoza Dalibón, Santiago E.; Martínez, Diego C.; Simari, Guillermo Ricardo

2014-01-01

In this work we present an approach to emotional reasoning for believable agents, by introducing a mechanism to progressively build a map of knowledge for reasoning. We present the notion of inference graph for progressive reasoning in an emotional context. In this model, knowledge is partially highlighted and noticed by the agent.

DynaLearn-An Intelligent Learning Environment for Learning Conceptual Knowledge

NARCIS (Netherlands)

Bredeweg, Bert; Liem, Jochem; Beek, Wouter; Linnebank, Floris; Gracia, Jorge; Lozano, Esther; Wißner, Michael; Bühling, René; Salles, Paulo; Noble, Richard; Zitek, Andreas; Borisova, Petya; Mioduser, David

2013-01-01

Articulating thought in computerbased media is a powerful means for humans to develop their understanding of phenomena. We have created DynaLearn, an intelligent learning environment that allows learners to acquire conceptual knowledge by constructing and simulating qualitative models of how systems

Agent-Based Health Monitoring System, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — We propose combination of software intelligent agents to achieve decentralized reasoning, with fault detection and diagnosis using PCA, neural nets, and maximum...

International workshop on knowledge management in scientific organizations, KMSO 2009, Damascus (SY), 9-11 March 2009

International Nuclear Information System (INIS)

2009-01-01

This publication includes the papers presented at the International workshop on knowledge management in scientific organizations which held in Damascus 9-11 March 2009. KM processes and technologies are main topics of the workshop with keynote speeches and exercises covering: Knowledge Generation, Knowledge Preservation, Knowledge Distribution, Knowledge Utilization and KM technologies which cover Information and Communication Technology, Internet, Intranet and Extranet, Data Mining and Warehousing, Knowledge bases and information repositories, Information retrieval, Intelligent agents and expert systems, Groupware and collaborative systems

A prototype system for perinatal knowledge engineering using an artificial intelligence tool.

Science.gov (United States)

Sokol, R J; Chik, L

1988-01-01

Though several perinatal expert systems are extant, the use of artificial intelligence has, as yet, had minimal impact in medical computing. In this evaluation of the potential of AI techniques in the development of a computer based "Perinatal Consultant," a "top down" approach to the development of a perinatal knowledge base was taken, using as a source for such a knowledge base a 30-page manuscript of a chapter concerning high risk pregnancy. The UNIX utility "style" was used to parse sentences and obtain key words and phrases, both as part of a natural language interface and to identify key perinatal concepts. Compared with the "gold standard" of sentences containing key facts as chosen by the experts, a semiautomated method using a nonmedical speller to identify key words and phrases in context functioned with a sensitivity of 79%, i.e., approximately 8 in 10 key sentences were detected as the basis for PROLOG, rules and facts for the knowledge base. These encouraging results suggest that functional perinatal expert systems may well be expedited by using programming utilities in conjunction with AI tools and published literature.

Dynamic knowledge representation using agent-based modeling: ontology instantiation and verification of conceptual models.

Science.gov (United States)

An, Gary

2009-01-01

The sheer volume of biomedical research threatens to overwhelm the capacity of individuals to effectively process this information. Adding to this challenge is the multiscale nature of both biological systems and the research community as a whole. Given this volume and rate of generation of biomedical information, the research community must develop methods for robust representation of knowledge in order for individuals, and the community as a whole, to "know what they know." Despite increasing emphasis on "data-driven" research, the fact remains that researchers guide their research using intuitively constructed conceptual models derived from knowledge extracted from publications, knowledge that is generally qualitatively expressed using natural language. Agent-based modeling (ABM) is a computational modeling method that is suited to translating the knowledge expressed in biomedical texts into dynamic representations of the conceptual models generated by researchers. The hierarchical object-class orientation of ABM maps well to biomedical ontological structures, facilitating the translation of ontologies into instantiated models. Furthermore, ABM is suited to producing the nonintuitive behaviors that often "break" conceptual models. Verification in this context is focused at determining the plausibility of a particular conceptual model, and qualitative knowledge representation is often sufficient for this goal. Thus, utilized in this fashion, ABM can provide a powerful adjunct to other computational methods within the research process, as well as providing a metamodeling framework to enhance the evolution of biomedical ontologies.

A framework for intelligent data acquisition and real-time database searching for shotgun proteomics.

Science.gov (United States)

Graumann, Johannes; Scheltema, Richard A; Zhang, Yong; Cox, Jürgen; Mann, Matthias

2012-03-01

In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides "on-the-fly" within 30 ms, well within the time constraints of a shotgun fragmentation "topN" method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available.

SASAgent: an agent based architecture for search, retrieval and composition of scientific models.

Science.gov (United States)

Felipe Mendes, Luiz; Silva, Laryssa; Matos, Ely; Braga, Regina; Campos, Fernanda

2011-07-01

Scientific computing is a multidisciplinary field that goes beyond the use of computer as machine where researchers write simple texts, presentations or store analysis and results of their experiments. Because of the huge hardware/software resources invested in experiments and simulations, this new approach to scientific computing currently adopted by research groups is well represented by e-Science. This work aims to propose a new architecture based on intelligent agents to search, recover and compose simulation models, generated in the context of research projects related to biological domain. The SASAgent architecture is described as a multi-tier, comprising three main modules, where CelO ontology satisfies requirements put by e-science projects mainly represented by the semantic knowledge base. Preliminary results suggest that the proposed architecture is promising to achieve requirements found in e-Science projects, considering mainly the biological domain. Copyright © 2011 Elsevier Ltd. All rights reserved.

Knowledge management impact of information technology Web 2.0/3.0. The case study of agent software technology usability in knowledge management system

Science.gov (United States)

Sołtysik-Piorunkiewicz, Anna

2015-02-01

How we can measure the impact of internet technology Web 2.0/3.0 for knowledge management? How we can use the Web 2.0/3.0 technologies for generating, evaluating, sharing, organizing knowledge in knowledge-based organization? How we can evaluate it from user-centered perspective? Article aims to provide a method for evaluate the usability of web technologies to support knowledge management in knowledge-based organizations of the various stages of the cycle knowledge management, taking into account: generating knowledge, evaluating knowledge, sharing knowledge, etc. for the modern Internet technologies based on the example of agent technologies. The method focuses on five areas of evaluation: GUI, functional structure, the way of content publication, organizational aspect, technological aspect. The method is based on the proposed indicators relating respectively to assess specific areas of evaluation, taking into account the individual characteristics of the scoring. Each of the features identified in the evaluation is judged first point wise, then this score is subject to verification and clarification by means of appropriate indicators of a given feature. The article proposes appropriate indicators to measure the impact of Web 2.0/3.0 technologies for knowledge management and verification them in an example of agent technology usability in knowledge management system.

Is It Possible To Use Intelligent Systems To Design A Profitable Foreign Exchange Trading Agent?

OpenAIRE

Julian, Pomfret-Pudelsky

2009-01-01

In this paper, a trading agent is developed using a basket of intelligent systems with the goal of trading the GBPUSD currency pair profitably in the Foreign Exchange market. The basket of intelligent system consists of two regression models: a radial basis neural network and a TSK-fuzzy inference system; and three classification models: k-nearest neighbour, support vector machine and a decision tree. The trading strategy combines the predictions of each model using a Kalman-type filter to...

Intelligent Agents for Design and Synthesis Environments: My Summary

Science.gov (United States)

Norvig, Peter

1999-01-01

This presentation gives a summary of intelligent agents for design synthesis environments. We'll start with the conclusions, and work backwards to justify them. First, an important assumption is that agents (whatever they are) are good for software engineering. This is especially true for software that operates in an uncertain, changing environment. The "real world" of physical artifacts is like that: uncertain in what we can measure, changing in that things are always breaking down, and we must interact with non-software entities. The second point is that software engineering techniques can contribute to good design. There may have been a time when we wanted to build simple artifacts containing little or no software. But modern aircraft and spacecraft are complex, and rely on a great deal of software. So better software engineering leads to better designed artifacts, especially when we are designing a series of related artifacts and can amortize the costs of software development. The third point is that agents are especially useful for design tasks, above and beyond their general usefulness for software engineering, and the usefulness of software engineering to design.

Artificial intelligence and information-control systems of robots - 87

International Nuclear Information System (INIS)

Plander, I.

1987-01-01

Independent research areas of artificial intelligence represent the following problems: automatic problem solving and new knowledge discovering, automatic program synthesis, natural language, picture and scene recognition and understanding, intelligent control systems of robots equipped with sensoric subsystems, dialogue of two knowledge systems, as well as studying and modelling higher artificial intelligence attributes, such as emotionality and personality. The 4th Conference draws on the problems treated at the preceding Conferences, and presents the most recent knowledge on the following topics: theoretical problems of artificial intelligence, knowledge-based systems, expert systems, perception and pattern recognition, robotics, intelligent computer-aided design, special-purpose computer systems for artificial intelligence and robotics

Intelligent indexing

International Nuclear Information System (INIS)

Farkas, J.

1992-01-01

In this paper we discuss the relevance of artificial intelligence to the automatic indexing of natural language text. We describe the use of domain-specific semantically-based thesauruses and address the problem of creating adequate knowledge bases for intelligent indexing systems. We also discuss the relevance of the Hilbert space ι 2 to the compact representation of documents and to the definition of the similarity of natural language texts. (author). 17 refs., 2 figs

Intelligent indexing

Energy Technology Data Exchange (ETDEWEB)

Farkas, J

1993-12-31

In this paper we discuss the relevance of artificial intelligence to the automatic indexing of natural language text. We describe the use of domain-specific semantically-based thesauruses and address the problem of creating adequate knowledge bases for intelligent indexing systems. We also discuss the relevance of the Hilbert space {iota}{sup 2} to the compact representation of documents and to the definition of the similarity of natural language texts. (author). 17 refs., 2 figs.

ISPE: A knowledge-based system for fluidization studies

Energy Technology Data Exchange (ETDEWEB)

Reddy, S.

1991-01-01

Chemical engineers use mathematical simulators to design, model, optimize and refine various engineering plants/processes. This procedure requires the following steps: (1) preparation of an input data file according to the format required by the target simulator; (2) excecuting the simulation; and (3) analyzing the results of the simulation to determine if all specified goals'' are satisfied. If the goals are not met, the input data file must be modified and the simulation repeated. This multistep process is continued until satisfactory results are obtained. This research was undertaken to develop a knowledge based system, IPSE (Intelligent Process Simulation Environment), that can enhance the productivity of chemical engineers/modelers by serving as an intelligent assistant to perform a variety tasks related to process simulation. ASPEN, a widely used simulator by the US Department of Energy (DOE) at Morgantown Energy Technology Center (METC) was selected as the target process simulator in the project. IPSE, written in the C language, was developed using a number of knowledge-based programming paradigms: object-oriented knowledge representation that uses inheritance and methods, rulebased inferencing (includes processing and propagation of probabilistic information) and data-driven programming using demons. It was implemented using the knowledge based environment LASER. The relationship of IPSE with the user, ASPEN, LASER and the C language is shown in Figure 1.

Study on the E-commerce platform based on the agent

Science.gov (United States)

Fu, Ruixue; Qin, Lishuan; Gao, Yinmin

2011-10-01

To solve problem of dynamic integration in e-commerce, the Multi-Agent architecture of electronic commerce platform system based on Agent and Ontology has been introduced, which includes three major types of agent, Ontology and rule collection. In this architecture, service agent and rule are used to realize the business process reengineering, the reuse of software component, and agility of the electronic commerce platform. To illustrate the architecture, a simulation work has been done and the results imply that the architecture provides a very efficient method to design and implement the flexible, distributed, open and intelligent electronic commerce platform system to solve problem of dynamic integration in ecommerce. The objective of this paper is to illustrate the architecture of electronic commerce platform system, and the approach how Agent and Ontology support the electronic commerce platform system.

Multi-issue Agent Negotiation Based on Fairness

Science.gov (United States)

Zuo, Baohe; Zheng, Sue; Wu, Hong

Agent-based e-commerce service has become a hotspot now. How to make the agent negotiation process quickly and high-efficiently is the main research direction of this area. In the multi-issue model, MAUT(Multi-attribute Utility Theory) or its derived theory usually consider little about the fairness of both negotiators. This work presents a general model of agent negotiation which considered the satisfaction of both negotiators via autonomous learning. The model can evaluate offers from the opponent agent based on the satisfaction degree, learn online to get the opponent's knowledge from interactive instances of history and negotiation of this time, make concessions dynamically based on fair object. Through building the optimal negotiation model, the bilateral negotiation achieved a higher efficiency and fairer deal.

SOME CONCEPTUAL PROPERTIES FOR KNOWLEDGE MANAGEMENT SYSTEMS DESIGN

Directory of Open Access Journals (Sweden)

Vasile MAZILESCU

2005-01-01

Full Text Available Knowledge Management Systems (KMS are important tools by which organizations can better useinformation and, more importantly, manage knowledge. Unlike other strategies, knowledge management (KM isdifficult to define because it encompasses a range of concepts, management tasks, technologies, and organizationalpractices, all of which come under the umbrella of the information management. Semantic approaches alloweasier and more efficient training, maintenance, and support knowledge. Current ICT markets are dominated byrelational databases and document-centric information technologies, procedural algorithmic programmingparadigms, and stack architecture. A key driver of global economic growth in the coming decade is the build-out ofbroadband telecommunications and the deployment of intelligent services bundling. This paper introduces themain characteristics of an Intelligent Knowledge Management System as a multi-agent system used in a LearningControl Problem (IKMSLCP. We describe an intelligent KM framework, allowing the observer (a human agentto learn from experience.

Engineering Knowledge for Automated Planning: Towards a Notion of Quality

OpenAIRE

McCluskey, T.L.; Vaquero, Tiago; Vallati, Mauro

2017-01-01

Automated planning is a prominent Artificial Intelligence challenge, as well as being a common capability requirement for intelligent\\ud autonomous agents. A critical aspect of what is called domain-independent planning, is the application knowledge that must be added to the planner to create a complete planning application. This is made explicit in (i) a domain model, which is a formal representation of the persistent domain knowledge, and (ii) an associated problem instance, containing the ...

A multi-agent based intelligent configuration method for aircraft fleet maintenance personnel

Directory of Open Access Journals (Sweden)

Feng Qiang

2014-04-01

Full Text Available A multi-agent based fleet maintenance personnel configuration method is proposed to solve the mission oriented aircraft fleet maintenance personnel configuration problem. The maintenance process of an aircraft fleet is analyzed first. In the process each aircraft contains multiple parts, and different parts are repaired by personnel with different majors and levels. The factors and their relationship involved in the process of maintenance are analyzed and discussed. Then the whole maintenance process is described as a 3-layer multi-agent system (MAS model. A communication and reasoning strategy among the agents is put forward. A fleet maintenance personnel configuration algorithm is proposed based on contract net protocol (CNP. Finally, a fleet of 10 aircraft is studied for verification purposes. A mission type with 3 waves of continuous dispatch is imaged. Compared with the traditional methods that can just provide configuration results, the proposed method can provide optimal maintenance strategies as well.

The knowledge game - motivating knowledge sharing and testing organization policies in this concern

International Nuclear Information System (INIS)

Barroso, Antonio C.O.; Seixas, Marcelo A.

2011-01-01

The ageing of nuclear experts and operating personnel and the lack of attractiveness of nuclear jobs to younger generation were emphasized as two of the most important factors that could jeopardize the preservation and sustainable development of the present body of nuclear knowledge worldwide. The willingness to share knowledge is at the inner core of any process involving transfer and dissemination of knowledge. This paper deals with the development of a tool to demonstrate the advantages of a culture inductive of knowledge sharing and cooperation from both the organization's and individual's viewpoints and coins the basics of reward policies that foster the development of desirable cultures. The Knowledge Game is a software tool to: (a) show the importance of sharing knowledge to both the individual and the organization; (b) demonstrate the fact that collaborative behaviors achieve higher payoffs in the long run; (c) test organizational rewards policies. It is an agent based modeling tool in which users may play with other humans and/or built in agents with fixed strategies. Payoff rules, simulation speed, number of players and their strategies and number of cycles are set before beginning the simulation. Plots display results in real time and output files can be generated for further analysis. Tests encompassing proof of concept and application confirm the game's great potential as a demonstration and policy testing tool. To test policies more effectively future implementations of intelligent agents coupled with fitness selection of players should be a very key lever. (author)

Intelligent Distributed Computing VI : Proceedings of the 6th International Symposium on Intelligent Distributed Computing

CERN Document Server

Badica, Costin; Malgeri, Michele; Unland, Rainer

2013-01-01

This book represents the combined peer-reviewed proceedings of the Sixth International Symposium on Intelligent Distributed Computing -- IDC~2012, of the International Workshop on Agents for Cloud -- A4C~2012 and of the Fourth International Workshop on Multi-Agent Systems Technology and Semantics -- MASTS~2012. All the events were held in Calabria, Italy during September 24-26, 2012. The 37 contributions published in this book address many topics related to theory and applications of intelligent distributed computing and multi-agent systems, including: adaptive and autonomous distributed systems, agent programming, ambient assisted living systems, business process modeling and verification, cloud computing, coalition formation, decision support systems, distributed optimization and constraint satisfaction, gesture recognition, intelligent energy management in WSNs, intelligent logistics, machine learning, mobile agents, parallel and distributed computational intelligence, parallel evolutionary computing, trus...

Solving Complex Logistics Problems with Multi-Artificial Intelligent System

Directory of Open Access Journals (Sweden)

Y.K. Tse

2009-10-01

Full Text Available The economy, which has become more information intensive, more global and more technologically dependent, is undergoing dramatic changes. The role of logistics is also becoming more and more important. In logistics, the objective of service providers is to fulfill all customers? demands while adapting to the dynamic changes of logistics networks so as to achieve a higher degree of customer satisfaction and therefore a higher return on investment. In order to provide high quality service, knowledge and information sharing among departments becomes a must in this fast changing market environment. In particular, artificial intelligence (AI technologies have achieved significant attention for enhancing the agility of supply chain management, as well as logistics operations. In this research, a multi-artificial intelligence system, named Integrated Intelligent Logistics System (IILS is proposed. The objective of IILS is to provide quality logistics solutions to achieve high levels of service performance in the logistics industry. The new feature of this agile intelligence system is characterized by the incorporation of intelligence modules through the capabilities of the case-based reasoning, multi-agent, fuzzy logic and artificial neural networks, achieving the optimization of the performance of organizations.

The internet and intelligent machines: search engines, agents and robots

International Nuclear Information System (INIS)

Achenbach, S.; Alfke, H.

2000-01-01

The internet plays an important role in a growing number of medical applications. Finding relevant information is not always easy as the amount of available information on the Web is rising quickly. Even the best Search Engines can only collect links to a fraction of all existing Web pages. In addition, many of these indexed documents have been changed or deleted. The vast majority of information on the Web is not searchable with conventional methods. New search strategies, technologies and standards are combined in Intelligent Search Agents (ISA) an Robots, which can retrieve desired information in a specific approach. Conclusion: The article describes differences between ISAs and conventional Search Engines and how communication between Agents improves their ability to find information. Examples of existing ISAs are given and the possible influences on the current and future work in radiology is discussed. (orig.) [de

Semantic Oriented Agent based Approach towards Engineering Data Management, Web Information Retrieval and User System Communication Problems

OpenAIRE

Ahmed, Zeeshan; Gerhard, Detlef

2010-01-01

The four intensive problems to the software rose by the software industry .i.e., User System Communication / Human Machine Interface, Meta Data extraction, Information processing & management and Data representation are discussed in this research paper. To contribute in the field we have proposed and described an intelligent semantic oriented agent based search engine including the concepts of intelligent graphical user interface, natural language based information processing, data management...

A Framework for Agent-based Human Interaction Support

Directory of Open Access Journals (Sweden)

Axel Bürkle

2008-10-01

Full Text Available In this paper we describe an agent-based infrastructure for multimodal perceptual systems which aims at developing and realizing computer services that are delivered to humans in an implicit and unobtrusive way. The framework presented here supports the implementation of human-centric context-aware applications providing non-obtrusive assistance to participants in events such as meetings, lectures, conferences and presentations taking place in indoor "smart spaces". We emphasize on the design and implementation of an agent-based framework that supports "pluggable" service logic in the sense that the service developer can concentrate on coding the service logic independently of the underlying middleware. Furthermore, we give an example of the architecture's ability to support the cooperation of multiple services in a meeting scenario using an intelligent connector service and a semantic web oriented travel service.

Artificial intelligence executive summary

International Nuclear Information System (INIS)

Wamsley, S.J.; Purvis, E.E. III

1984-01-01

Artificial intelligence (AI) is a high technology field that can be used to provide problem solving diagnosis, guidance and for support resolution of problems. It is not a stand alone discipline, but can also be applied to develop data bases for retention of the expertise that is required for its own knowledge base. This provides a way to retain knowledge that otherwise may be lost. Artificial Intelligence Methodology can provide an automated construction management decision support system, thereby restoring the manager's emphasis to project management

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 ...

2015 Chinese Intelligent Automation Conference

CERN Document Server

Li, Hongbo

2015-01-01

Proceedings of the 2015 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’15, held in Fuzhou, China. The topics include adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, reconfigurable control, etc. Engineers and researchers from academia, industry and the government can gain valuable insights into interdisciplinary solutions in the field of intelligent automation.

Intelligent agents in data-intensive computing

CERN Document Server

Correia, Luís; Molina, José

2016-01-01

This book presents new approaches that advance research in all aspects of agent-based models, technologies, simulations and implementations for data intensive applications. The nine chapters contain a review of recent cross-disciplinary approaches in cloud environments and multi-agent systems, and important formulations of data intensive problems in distributed computational environments together with the presentation of new agent-based tools to handle those problems and Big Data in general. This volume can serve as a reference for students, researchers and industry practitioners working in or interested in joining interdisciplinary work in the areas of data intensive computing and Big Data systems using emergent large-scale distributed computing paradigms. It will also allow newcomers to grasp key concepts and potential solutions on advanced topics of theory, models, technologies, system architectures and implementation of applications in Multi-Agent systems and data intensive computing. .

Intelligent Tools for Planning Knowledge base Development and Verification

Science.gov (United States)

Chien, Steve A.

1996-01-01

A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintaining the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems.

The role of knowledge management tools in supporting sustainable forest management

Energy Technology Data Exchange (ETDEWEB)

Vacik, H.; Torresan, C.; Hujala, T.; Khadka, C.; Reynolds, K.

2013-07-01

Aim of study: Knowledge Management (KM) tools facilitate the implementation of knowledge processes by identifying, creating, structuring, and sharing knowledge through use of information technology in order to improve decision-making. In this contribution, we review the way in which KM tools and techniques are used in forest management, and categorize a selected set of them according to their contribution to support decision makers in the phases of problem identification, problem modelling, and problem solving. Material and methods: Existing examples of cognitive mapping tools, web portals, work flow systems, best practices, and expert systems as well as intelligent agents are screened for their applicability and use in the context of decision support for sustainable forest management. Evidence from scientific literature and case studies is utilized to evaluate the contribution of the different KM tools to support problem identification, problem modelling, and problem solving. Main results: Intelligent agents, expert systems and cognitive maps support all phases of the forest planning process strongly. Web based tools have good potential to support participatory forest planning. Based on the needs of forest management decision support and the thus-far under utilized capabilities of KM tools it becomes evident that future decision analysis will have to consider the use of KM more intensively. Research highlights: As the problem-solving process is the vehicle for connecting both knowledge and decision making performance, the next generation of DSS will need to better encapsulate practices that enhance and promote knowledge management. Web based tools will substitute desktop applications by utilizing various model libraries on the internet. (Author)

Knowledge-Based Reinforcement Learning for Data Mining

Science.gov (United States)

Kudenko, Daniel; Grzes, Marek

experts have developed heuristics that help them in planning and scheduling resources in their work place. However, this domain knowledge is often rough and incomplete. When the domain knowledge is used directly by an automated expert system, the solutions are often sub-optimal, due to the incompleteness of the knowledge, the uncertainty of environments, and the possibility to encounter unexpected situations. RL, on the other hand, can overcome the weaknesses of the heuristic domain knowledge and produce optimal solutions. In the talk we propose two techniques, which represent first steps in the area of knowledge-based RL (KBRL). The first technique [1] uses high-level STRIPS operator knowledge in reward shaping to focus the search for the optimal policy. Empirical results show that the plan-based reward shaping approach outperforms other RL techniques, including alternative manual and MDP-based reward shaping when it is used in its basic form. We showed that MDP-based reward shaping may fail and successful experiments with STRIPS-based shaping suggest modifications which can overcome encountered problems. The STRIPSbased method we propose allows expressing the same domain knowledge in a different way and the domain expert can choose whether to define an MDP or STRIPS planning task. We also evaluated the robustness of the proposed STRIPS-based technique to errors in the plan knowledge. In case that STRIPS knowledge is not available, we propose a second technique [2] that shapes the reward with hierarchical tile coding. Where the Q-function is represented with low-level tile coding, a V-function with coarser tile coding can be learned in parallel and used to approximate the potential for ground states. In the context of data mining, our KBRL approaches can also be used for any data collection task where the acquisition of data may incur considerable cost. In addition, observing the data collection agent in specific scenarios may lead to new insights into optimal data

Artificial intelligence and tutoring systems computational and cognitive approaches to the communication of knowledge

CERN Document Server

Wenger, Etienne

2014-01-01

Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge focuses on the cognitive approaches, methodologies, principles, and concepts involved in the communication of knowledge. The publication first elaborates on knowledge communication systems, basic issues, and tutorial dialogues. Concerns cover natural reasoning and tutorial dialogues, shift from local strategies to multiple mental models, domain knowledge, pedagogical knowledge, implicit versus explicit encoding of knowledge, knowledge communication, and practical and theoretic

Accident diagnosis of the Angra-2 nuclear power plant based on intelligent real-time acquisition agents and a logical tree model

Energy Technology Data Exchange (ETDEWEB)

Paiva, Gustavo V.; Schirru, Roberto, E-mail: gustavopaiva@poli.ufrj.br, E-mail: schirru@lmp.ufrj.br [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Departamento de Engenharia Nuclear

2017-07-01

This work aims to create a model and a prototype, using the Python language, which with the application of an Expert System uses production rules to analyze the data obtained in real time from the plant and help the operator to identify the occurrence of transients / accidents. In the event of a transient, the program alerts the operator and indicates which section of the Operation Manual should be consulted to bring the plant back to its normal state. The generic structure used to represent the knowledge of the Expert System was a Fault Tree and the data obtained from the plant was done through intelligent acquisition agents that transform the data obtained from the plant into Boolean values used in the Fault Tree, including the use of Fuzzy Logic. In order to test the program, a simplified model of the Almirante Alvaro Alberto 2 Nuclear Power Plant (Angra-2) manuals was used and with this model, simulations were performed to analyze the program's operation and if it leads to the expected results. The results of the tests presented a quick identification of the events and great accuracy, demonstrating the applicability of the model to the problem. (author)

Accident diagnosis of the Angra-2 nuclear power plant based on intelligent real-time acquisition agents and a logical tree model

International Nuclear Information System (INIS)

Paiva, Gustavo V.; Schirru, Roberto

2017-01-01

This work aims to create a model and a prototype, using the Python language, which with the application of an Expert System uses production rules to analyze the data obtained in real time from the plant and help the operator to identify the occurrence of transients / accidents. In the event of a transient, the program alerts the operator and indicates which section of the Operation Manual should be consulted to bring the plant back to its normal state. The generic structure used to represent the knowledge of the Expert System was a Fault Tree and the data obtained from the plant was done through intelligent acquisition agents that transform the data obtained from the plant into Boolean values used in the Fault Tree, including the use of Fuzzy Logic. In order to test the program, a simplified model of the Almirante Alvaro Alberto 2 Nuclear Power Plant (Angra-2) manuals was used and with this model, simulations were performed to analyze the program's operation and if it leads to the expected results. The results of the tests presented a quick identification of the events and great accuracy, demonstrating the applicability of the model to the problem. (author)

Knowledge-based interpretation of cranial MR images

International Nuclear Information System (INIS)

Kuhn, M.H.; Menhardt, W.; Schmidt, K.H.

1987-01-01

A computerized system is described that can be used to evaluate an MR tomogram automatically to support clinical identification of anatomic and pathologic structures and to aid in planning MR measurements. Knowledge from three domains is used for the interpretation of an MR image: nosologic knowledge, knowledge of MR imaging parameters, and anatomic and morphologic knowledge. Nosologic information is used to generate hypotheses about possible pathologies and their locations, based on the signs and symptoms of the patient. With this information, a sequence of interpretation modules, each able to detect substructures in already detected structures with the aid of techniques from image processing, pattern recognition, and artificial intelligence, is generated and executed

Intelligent model-based diagnostics for vehicle health management

Science.gov (United States)

Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

2003-08-01

The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

Collective Machine Learning: Team Learning and Classification in Multi-Agent Systems

Science.gov (United States)

Gifford, Christopher M.

2009-01-01

This dissertation focuses on the collaboration of multiple heterogeneous, intelligent agents (hardware or software) which collaborate to learn a task and are capable of sharing knowledge. The concept of collaborative learning in multi-agent and multi-robot systems is largely under studied, and represents an area where further research is needed to…

Management of new information technologies in organisations by intelligent software agents

DEFF Research Database (Denmark)

Abolfazlian, Ali Reza Kian

1996-01-01

I denne artikel præsenteres argumenter for, hvorfor den Kartesianske management model baseret på en kognitiv psykologisk forståelse af organisationer, ikke kan beskrive de forandringsprocesser, som indførelsen af ny informationsteknologi i organisationer forårsager. På denne baggrund definerer vi...... Post-Kartesiansk management. Endvidere argumenteres for, hvordan Intelligent Software Agents kan hjælpe managers med at få en bedre forståelse for de førnævnte forandringer i organisationerne....

Space nuclear reactor system diagnosis: Knowledge-based approach

International Nuclear Information System (INIS)

Ting, Y.T.D.

1990-01-01

SP-100 space nuclear reactor system development is a joint effort by the Department of Energy, the Department of Defense and the National Aeronautics and Space Administration. The system is designed to operate in isolation for many years, and is possibly subject to little or no remote maintenance. This dissertation proposes a knowledge based diagnostic system which, in principle, can diagnose the faults which can either cause reactor shutdown or lead to another serious problem. This framework in general can be applied to the fully specified system if detailed design information becomes available. The set of faults considered herein is identified based on heuristic knowledge about the system operation. The suitable approach to diagnostic problem solving is proposed after investigating the most prevalent methodologies in Artificial Intelligence as well as the causal analysis of the system. Deep causal knowledge modeling based on digraph, fault-tree or logic flowgraph methodology would present a need for some knowledge representation to handle the time dependent system behavior. A proposed qualitative temporal knowledge modeling methodology, using rules with specified time delay among the process variables, has been proposed and is used to develop the diagnostic sufficient rule set. The rule set has been modified by using a time zone approach to have a robust system design. The sufficient rule set is transformed to a sufficient and necessary one by searching the whole knowledge base. Qualitative data analysis is proposed in analyzing the measured data if in a real time situation. An expert system shell - Intelligence Compiler is used to develop the prototype system. Frames are used for the process variables. Forward chaining rules are used in monitoring and backward chaining rules are used in diagnosis

Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation.

Science.gov (United States)

An, Gary

2008-05-27

One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM) can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems. A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior in the intensive care setting. The ABMs all utilize cell-level agents

An intelligent service-based layered architecture for e learning and assessment

International Nuclear Information System (INIS)

Javaid, Q.; Arif, F.

2017-01-01

The rapid advancement in ICT (Information and Communication Technology) is causing a paradigm shift in eLearning domain. Traditional eLearning systems suffer from certain shortcomings like tight coupling of system components, lack of personalization, flexibility, and scalability and performance issues. This study aims at addressing these challenges through an MAS (Multi Agent System) based multi-layer architecture supported by web services. The foremost objective of this study is to enhance learning process efficiency by provision of flexibility features for learning and assessment processes. Proposed architecture consists of two sub-system namely eLearning and eAssesssment. This architecture comprises of five distinct layers for each sub-system, with active agents responsible for miscellaneous tasks including content handling, updating, resource optimization, load handling and provision of customized environments for learners and instructors. Our proposed architecture aims at establishment of a facilitation level to learners as well as instructors for convenient acquisition and dissemination of knowledge. Personalization features like customized environments, personalized content retrieval and recommendations, adaptive assessment and reduced response time, are believed to significantly enhance learning and tutoring experience. In essence characteristics like intelligence, personalization, interactivity, usability, laidback accessibility and security, signify aptness of proposed architecture for improving conventional learning and assessment processes. Finally we have evaluated our proposed architecture by means of analytical comparison and survey considering certain quality attributes. (author)

Requirement analysis for autonomous systems and intelligent agents in future Danish electric power systems

DEFF Research Database (Denmark)

Saleem, Arshad; Lind, Morten

2010-01-01

we review innovative control architectures in electric power systems such as Microgrids, Virtual power plants and Cell based systems. We evaluate application of autonomous systems and intelligent agents in each of these control architectures particularly in the context of Denmark's strategic energy...... plans. The second part formulates a flexible control architecture for electric power systems with very high penetration of distributed generation. This control architecture is based upon the requirements identified in the first part. We also present development of a software framework to test......Denmark has already achieved a record of 20% penetration of wind power and now moving towards even higher targets with an increasing part of the electricity produced by distributed generators (DGs). In this paper we report work from a sub activity "subgrid design" of the EcoGrid.dk project. First...

Intelligent Lighting Control System

OpenAIRE

García, Elena; Rodríguez González, Sara; de Paz Santana, Juan F.; Bajo Pérez, Javier

2014-01-01

This paper presents an adaptive architecture that allows centralized control of public lighting and intelligent management, in order to economise on lighting and maintain maximum comfort status of the illuminated areas. To carry out this management, architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA and a Service Oriented Aproach (SOA). It performs optim...

Supporting Multi-agent Coordination and Computational Collective Intelligence in Enterprise 2.0 Platform

Directory of Open Access Journals (Sweden)

Seddik Reguieg

2017-12-01

Full Text Available In this paper, we propose a novel approach utilizing a professional Social network (Pro Social Network and a new coordination protocol (CordiNet. Our motivation behind this article is to convince Small and Medium Enterprises managers that current organizations have chosen to use Enterprise 2.0 tools because these latter have demonstrated remarkable innovation as well as successful collaboration and collective intelligence. The particularity of our work is that is allows employer to share diagnosis and fault repair procedures on the basis of some modeling agents. In fact, each enterprise is represented by a container of agents to ensure a secured and confidential information exchange between intra employers, and a central main container to connect all enterprises’ containers for a social information exchange. Enterprise’s container consists of a Checker Enterprise Agent (ChEA, a Coordinator Enterprise Agent (CoEA and a Search Enterprise Agent (SeEA. Whereas the central main container comprises its proper agents such as Selection Agent (SA, and a Supervisor Agent (SuA. JADE platform is used to allow agents to communicate and collaborate. The FIPA-ACL performatives have been extended for this purpose. We conduct some experiments to demonstrate the feasibility of our approach.

Knowledge based expert system approach to instrumentation selection (INSEL

Directory of Open Access Journals (Sweden)

S. Barai

2004-08-01

Full Text Available The selection of appropriate instrumentation for any structural measurement of civil engineering structure is a complex task. Recent developments in Artificial Intelligence (AI can help in an organized use of experiential knowledge available on instrumentation for laboratory and in-situ measurement. Usually, the instrumentation decision is based on the experience and judgment of experimentalists. The heuristic knowledge available for different types of measurement is domain dependent and the information is scattered in varied knowledge sources. The knowledge engineering techniques can help in capturing the experiential knowledge. This paper demonstrates a prototype knowledge based system for INstrument SELection (INSEL assistant where the experiential knowledge for various structural domains can be captured and utilized for making instrumentation decision. In particular, this Knowledge Based Expert System (KBES encodes the heuristics on measurement and demonstrates the instrument selection process with reference to steel bridges. INSEL runs on a microcomputer and uses an INSIGHT 2+ environment.

Student Modeling in an Intelligent Tutoring System

Science.gov (United States)

1996-12-17

Multi-Agent Architecture." Advances in Artificial Intelligence : Proceedings of the 12 th Brazilian Symposium on Aritificial Intelligence , edited by...STUDENT MODELING IN AN INTELLIGENT TUTORING SYSTEM THESIS Jeremy E. Thompson Captain, USAF AFIT/GCS/ENG/96D-27 DIMTVMON* fCKAJWINT A Appr"v*d t=i...Air Force Base, Ohio AFIT/GCS/ENG/96D-27 STUDENT MODELING IN AN INTELLIGENT TUTORING SYSTEM THESIS Jeremy E. Thompson Captain, USAF AFIT/GCS/ENG/96D

Ambient agents: embedded agents for remote control and monitoring using the PANGEA platform.

Science.gov (United States)

Villarrubia, Gabriel; De Paz, Juan F; Bajo, Javier; Corchado, Juan M

2014-07-31

Ambient intelligence has advanced significantly during the last few years. The incorporation of image processing and artificial intelligence techniques have opened the possibility for such aspects as pattern recognition, thus allowing for a better adaptation of these systems. This study presents a new model of an embedded agent especially designed to be implemented in sensing devices with resource constraints. This new model of an agent is integrated within the PANGEA (Platform for the Automatic Construction of Organiztions of Intelligent Agents) platform, an organizational-based platform, defining a new sensor role in the system and aimed at providing contextual information and interacting with the environment. A case study was developed over the PANGEA platform and designed using different agents and sensors responsible for providing user support at home in the event of incidents or emergencies. The system presented in the case study incorporates agents in Arduino hardware devices with recognition modules and illuminated bands; it also incorporates IP cameras programmed for automatic tracking, which can connect remotely in the event of emergencies. The user wears a bracelet, which contains a simple vibration sensor that can receive notifications about the emergency situation.

Ambient Agents: Embedded Agents for Remote Control and Monitoring Using the PANGEA Platform

Directory of Open Access Journals (Sweden)

Gabriel Villarrubia

2014-07-01

Full Text Available Ambient intelligence has advanced significantly during the last few years. The incorporation of image processing and artificial intelligence techniques have opened the possibility for such aspects as pattern recognition, thus allowing for a better adaptation of these systems. This study presents a new model of an embedded agent especially designed to be implemented in sensing devices with resource constraints. This new model of an agent is integrated within the PANGEA (Platform for the Automatic Construction of Organiztions of Intelligent Agents platform, an organizational-based platform, defining a new sensor role in the system and aimed at providing contextual information and interacting with the environment. A case study was developed over the PANGEA platform and designed using different agents and sensors responsible for providing user support at home in the event of incidents or emergencies. The system presented in the case study incorporates agents in Arduino hardware devices with recognition modules and illuminated bands; it also incorporates IP cameras programmed for automatic tracking, which can connect remotely in the event of emergencies. The user wears a bracelet, which contains a simple vibration sensor that can receive notifications about the emergency situation.

The knowledge game - motivating knowledge sharing and testing organization policies in this concern

Energy Technology Data Exchange (ETDEWEB)

Barroso, Antonio C.O.; Seixas, Marcelo A., E-mail: barroso@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2011-07-01

The ageing of nuclear experts and operating personnel and the lack of attractiveness of nuclear jobs to younger generation were emphasized as two of the most important factors that could jeopardize the preservation and sustainable development of the present body of nuclear knowledge worldwide. The willingness to share knowledge is at the inner core of any process involving transfer and dissemination of knowledge. This paper deals with the development of a tool to demonstrate the advantages of a culture inductive of knowledge sharing and cooperation from both the organization's and individual's viewpoints and coins the basics of reward policies that foster the development of desirable cultures. The Knowledge Game is a software tool to: (a) show the importance of sharing knowledge to both the individual and the organization; (b) demonstrate the fact that collaborative behaviors achieve higher payoffs in the long run; (c) test organizational rewards policies. It is an agent based modeling tool in which users may play with other humans and/or built in agents with fixed strategies. Payoff rules, simulation speed, number of players and their strategies and number of cycles are set before beginning the simulation. Plots display results in real time and output files can be generated for further analysis. Tests encompassing proof of concept and application confirm the game's great potential as a demonstration and policy testing tool. To test policies more effectively future implementations of intelligent agents coupled with fitness selection of players should be a very key lever. (author)

Agent and multi-Agent systems in distributed systems digital economy and e-commerce

CERN Document Server

Hartung, Ronald

2013-01-01

Information and communication technology, in particular artificial intelligence, can be used to support economy and commerce using digital means. This book is about agents and multi-agent distributed systems applied to digital economy and e-commerce to meet, improve, and overcome challenges in the digital economy and e-commerce sphere. Agent and multi-agent solutions are applied in implementing real-life, exciting developments associated with the need to eliminate problems of distributed systems.   The book presents solutions for both technology and applications, illustrating the possible uses of agents in the enterprise domain, covering design and analytic methods, needed to provide a solid foundation required for practical systems. More specifically, the book provides solutions for the digital economy, e-sourcing clusters in network economy, and knowledge exchange between agents applicable to online trading agents, and security solutions to both digital economy and e-commerce. Furthermore, it offers soluti...

A Knowledge-Based Consultant for Financial Marketing

OpenAIRE

Kastner, John; Apte, Chidanand; Griesmer, James

1986-01-01

This article describes an effort to develop a knowledge-based financial marketing consultant system. Financial marketing is an excellent vehicle for both research and application in artificial intelligence (AI). This domain differs from the great majority of previous expert system domains in that there are no well-defined answers (in traditional sense); the goal here is to obtain satisfactory arguments to support the conclusions made. A large OPS5-based system was implemented as an initial pr...

Towards Sustainable Smart Homes by a Hierarchical Hybrid Architecture of an Intelligent Agent

Directory of Open Access Journals (Sweden)

K. Yang

2016-10-01

Full Text Available A smart home can be realized by the provision of services, such as building control, automation and security implemented in accordance with a user’s request. One of the important issues is how to respond quickly and appropriately to a user’s request in a “dynamic environment”. An intelligent agent infers the user’s intention and provides the intact service. This paper proposes a smart home agent system based on a hierarchical hybrid architecture of a user intention model, which models the user intention as a hierarchical structure and implements it in a dynamic environment. The conventional rule-based approach needs to obtain all information before it is executed, which requires a large number of rules and is hardly scalable as the control objects are increasing. On the other hand, the proposed system consists of several modules that construct a hierarchical user intention model. The smart home system needs to take account of the information, such as time, state of device and state of the home, in addition to users’ intention. We evaluate the performance of the proposed system in a dynamic environment and conduct a blind test with seven subjects to measure the satisfaction of service, resulting in the average score of 81.46.

Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

Science.gov (United States)

Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta

2016-06-01

With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.

Conhecimentos dos agentes de endemias: aplicação de bases teóricas sobre saneamento e ambiente / Knowledge agents endemic: applying theoretical bases on sanitation and the environment

Directory of Open Access Journals (Sweden)

Leide Suzana Maia

2013-08-01

Full Text Available Este estudo buscou identifi car o conhecimento dos agentes de controle de endemias sobre saneamento básico e meio ambiente no município de Natal, capital do Rio Grande do Norte, em 2012. Trata-se de um estudo exploratório de abordagem quantitativa, realizado com 209 agentes do Programa Municipal de Controle da Dengue. Os dados foram coletados por meio de questionários e tabulados no programa Statistical Package for Social Sciences, com análise univariada de frequência, média e desvio padrão. Os resultados apontam que cerca de 50,0% dos agentes são constituídos por mulheres, 93,3% dos quais têm conhecimento a respeito de fornecimento de água potável, implantação de rede coletora de esgoto e drenagem, e coleta de lixo. Boa parte apresenta conhecimento adequado sobre o destino final de resíduos (74,1% e 95,2% afirmam que as ações de saneamento básico contribuem para a prevenção de doenças. Ressalta-se que 86,1% referiram adotar medidas contributivas para a preservação ambiental. A maioria dos agentes de controle de endemias (74,0% apresentou um grau de conhecimento entre bom e ótimo. -------------------------------------------------------------------- This study sought to identify the knowledge of the endemic control agents, about sanitation and environment in the city of Natal, capital of Rio Grande do Norte in 2012. This is an exploratory, descriptive and quantitative approach performed with 209 agents from the Municipal Program for Dengue Control. The data collection was conducted through a questionnaires, and tabulated in program Statistical Package for Social Sciences, with univariate analyze of frequency, average and standard deviation. The results show that 50,0% of agents are made up of women, and 93.3% of these have knowledge regarding the drinking water supply, installation of sanitary sewer and drainage, and garbage collection. Much has adequate knowledge about the disposal of waste (74.1%, and 95.2% said that

On the Construction of a Micro-World and the Design of a Path Finding Intelligent Agent with Applications in Robotics and Game Design

Directory of Open Access Journals (Sweden)

Cristian Moldovan

2017-12-01

Full Text Available This paper presents research regarding the behavior of an IA (Intelligent Agent in a MW (Micro-World, a maze-like environment, when it has to find a path from Start to Target position. The IA’s behavior is controlled via an Informed Search Algorithm. Its perception is limited only to one tile in the N, V, S and E direction, it has no prior knowledge of the search space, it has memory on the co-ordinates of already visited path and we implement a heuristic function to direct the IA to the Target.

Multi-Agent System-Based Microgrid Operation Strategy for Demand Response

Directory of Open Access Journals (Sweden)

Hee-Jun Cha

2015-12-01

Full Text Available The microgrid and demand response (DR are important technologies for future power grids. Among the variety of microgrid operations, the multi-agent system (MAS has attracted considerable attention. In a microgrid with MAS, the agents installed on the microgrid components operate optimally by communicating with each other. This paper proposes an operation algorithm for the individual agents of a test microgrid that consists of a battery energy storage system (BESS and an intelligent load. A microgrid central controller to manage the microgrid can exchange information with each agent. The BESS agent performs scheduling for maximum benefit in response to the electricity price and BESS state of charge (SOC through a fuzzy system. The intelligent load agent assumes that the industrial load performs scheduling for maximum benefit by calculating the hourly production cost. The agent operation algorithm includes a scheduling algorithm using day-ahead pricing in the DR program and a real-time operation algorithm for emergency situations using emergency demand response (EDR. The proposed algorithm and operation strategy were implemented both by a hardware-in-the-loop simulation test using OPAL-RT and an actual hardware test by connecting a new distribution simulator.

Agent based simulation on the process of human flesh search-From perspective of knowledge and emotion

Science.gov (United States)

Zhu, Hou; Hu, Bin

2017-03-01

Human flesh search as a new net crowed behavior, on the one hand can help us to find some special information, on the other hand may lead to privacy leaking and offending human right. In order to study the mechanism of human flesh search, this paper proposes a simulation model based on agent-based model and complex networks. The computational experiments show some useful results. Discovered information quantity and involved personal ratio are highly correlated, and most of net citizens will take part in the human flesh search or will not take part in the human flesh search. Knowledge quantity does not influence involved personal ratio, but influences whether HFS can find out the target human. When the knowledge concentrates on hub nodes, the discovered information quantity is either perfect or almost zero. Emotion of net citizens influences both discovered information quantity and involved personal ratio. Concretely, when net citizens are calm to face the search topic, it will be hardly to find out the target; But when net citizens are agitated, the target will be found out easily.

Widening the Knowledge Acquisition Bottleneck for Constraint-Based Tutors

Science.gov (United States)

Suraweera, Pramuditha; Mitrovic, Antonija; Martin, Brent

2010-01-01

Intelligent Tutoring Systems (ITS) are effective tools for education. However, developing them is a labour-intensive and time-consuming process. A major share of the effort is devoted to acquiring the domain knowledge that underlies the system's intelligence. The goal of this research is to reduce this knowledge acquisition bottleneck and better…

BWR shutdown analyzer using artificial intelligence (AI) techniques

International Nuclear Information System (INIS)

Cain, D.G.

1986-01-01

A prototype alarm system for detecting abnormal reactor shutdowns based on artificial intelligence technology is described. The system incorporates knowledge about Boiling Water Reactor (BWR) plant design and component behavior, as well as knowledge required to distinguish normal, abnormal, and ATWS accident conditions. The system was developed using a software tool environment for creating knowledge-based applications on a LISP machine. To facilitate prototype implementation and evaluation, a casual simulation of BWR shutdown sequences was developed and interfaced with the alarm system. An intelligent graphics interface for execution and control is described. System performance considerations and general observations relating to artificial intelligence application to nuclear power plant problems are provided

Developing technology intelligence strategy to access knowledge of innovation clusters. : The case of KODAK in Cambridge

OpenAIRE

Dang , Rani Jeanne; Mortara , Letizia; Thomson , Ruth; Minshall , Tim

2010-01-01

International audience; Current times are characterised by a knowledge-based economy and fast technological change. In this difficult environment, companies compete to maintain a relevant position through innovation. In response to these challenges, many companies are currently adopting an open approach to innovation, pursuing innovation by combining internal and external resources. Technology intelligence (TI) activities support the implementation of open innovation with the systematic captu...

Algorithms and architectures of artificial intelligence

CERN Document Server

Tyugu, E

2007-01-01

This book gives an overview of methods developed in artificial intelligence for search, learning, problem solving and decision-making. It gives an overview of algorithms and architectures of artificial intelligence that have reached the degree of maturity when a method can be presented as an algorithm, or when a well-defined architecture is known, e.g. in neural nets and intelligent agents. It can be used as a handbook for a wide audience of application developers who are interested in using artificial intelligence methods in their software products. Parts of the text are rather independent, so that one can look into the index and go directly to a description of a method presented in the form of an abstract algorithm or an architectural solution. The book can be used also as a textbook for a course in applied artificial intelligence. Exercises on the subject are added at the end of each chapter. Neither programming skills nor specific knowledge in computer science are expected from the reader. However, some p...

SPRINT RA 230: Methodology for knowledge based developments

International Nuclear Information System (INIS)

Wallsgrove, R.; Munro, F.

1991-01-01

SPRINT RA 230: A Methodology for Knowledge Based Developments, funded by the European Commission, was set up to investigate the use of KBS in the engineering industry. Its aim was to find out low KBS were currently used and what people's conceptions of them was, to disseminate current knowledge and to recommend further research into this area. A survey (by post and face to face interviews) was carried out under SPRINT RA 230 to investigate requirements for more intelligent software. In the survey we looked both at how people think about Knowledge Based Systems (KBS), what they find useful and what is not useful, and what current expertise problems or limitations of conventional software might suggest KBS solutions. (orig./DG)

Study on large scale knowledge base with real time operation for autonomous nuclear power plant. 1. Basic concept and expecting performance

International Nuclear Information System (INIS)

Ozaki, Yoshihiko; Suda, Kazunori; Yoshikawa, Shinji; Ozawa, Kenji

1996-04-01

Since it is desired to enhance availability and safety of nuclear power plants operation and maintenance by removing human factor, there are many researches and developments for intelligent operation or diagnosis using artificial intelligence (AI) technique. We have been developing an autonomous operation and maintenance system for nuclear power plants by substituting AI's and intelligent robots. It is indispensable to use various and large scale knowledge relative to plant design, operation, and maintenance, that is, whole life cycle data of the plant for the autonomous nuclear power plant. These knowledge must be given to AI system or intelligent robots adequately and opportunely. Moreover, it is necessary to insure real time operation using the large scale knowledge base for plant control and diagnosis performance. We have been studying on the large scale and real time knowledge base system for autonomous plant. In the report, we would like to present the basic concept and expecting performance of the knowledge base for autonomous plant, especially, autonomous control and diagnosis system. (author)

The structure of surface texture knowledge

International Nuclear Information System (INIS)

Yan Wang; Scott, Paul J; Jiang Xiangqian

2005-01-01

This research aims to create an intelligent knowledge-based system for engineering and bio-medical engineering surface texture, which will provide expert knowledge of surface texture to link surface function, specification of micro- and nano-geometry through manufacture, and verification. The intelligent knowledge base should be capable of incorporating knowledge from multiple sources (standards, books, experts, etc), adding new knowledge from these sources and still remain a coherent reliable system. A new data model based on category theory will be adopted to construct this system

The Relationship between Multiple Intelligences and Iranian EFL Learners’ Level of L2 Lexical Knowledge: The Case of Gender

Directory of Open Access Journals (Sweden)

Reza Biria

2014-06-01

Full Text Available Human cognitive competence represents individuals’ subconscious knowledge of abilities, talents, and mental skills collectively called “multiple intelligences (MIs”, which play a pivotal role in facilitating human learning. Thus, the main objective of the present study was to determine the magnitude of the relationship existing between multiple intelligences and Iranian EFL learners’ level of second language (L2 lexical knowledge on one hand and the partializing impact of gender on the other. For this purpose, from the population of the senior undergraduate students majoring in translation at Islamic Azad University, Khorasgan (Isfahan Branch, Isfahan, Iran, a sample of 88 students, 24 males and 64 females, were randomly selected. First, Mckenzie’s (1999 MIs Inventory was administered to specify the size of individual types of intelligences in each learner’s MIs composite. Then, the learners were provided with Nation’s (2001 receptive level test a week later to gauge their level of L2 lexical knowledge. The findings revealed that the scores on MIs inventory correlated positively with those of L2 lexical knowledge. Alternatively, different types of intelligences served as useful predictors for estimating the quality of learners’ vocabulary knowledge. Finally, it was found out that gender did indeed have a different effect regarding the learners’ vocabulary knowledge.

Knowledge Based Engineering for Spatial Database Management and Use

Science.gov (United States)

Peuquet, D. (Principal Investigator)

1984-01-01

The use of artificial intelligence techniques that are applicable to Geographic Information Systems (GIS) are examined. Questions involving the performance and modification to the database structure, the definition of spectra in quadtree structures and their use in search heuristics, extension of the knowledge base, and learning algorithm concepts are investigated.

Knowledge structure representation and automated updates in intelligent information management systems

Science.gov (United States)

Corey, Stephen; Carnahan, Richard S., Jr.

1990-01-01

A continuing effort to apply rapid prototyping and Artificial Intelligence techniques to problems associated with projected Space Station-era information management systems is examined. In particular, timely updating of the various databases and knowledge structures within the proposed intelligent information management system (IIMS) is critical to support decision making processes. Because of the significantly large amounts of data entering the IIMS on a daily basis, information updates will need to be automatically performed with some systems requiring that data be incorporated and made available to users within a few hours. Meeting these demands depends first, on the design and implementation of information structures that are easily modified and expanded, and second, on the incorporation of intelligent automated update techniques that will allow meaningful information relationships to be established. Potential techniques are studied for developing such an automated update capability and IIMS update requirements are examined in light of results obtained from the IIMS prototyping effort.

A strategy learning model for autonomous agents based on classification

Directory of Open Access Journals (Sweden)

Śnieżyński Bartłomiej

2015-09-01

Full Text Available In this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for strategy generation even if rewards are delayed. We compare the efficiency of the proposed model and reinforcement learning using the farmer-pest domain and configurations of various complexity. In complex environments, supervised learning can improve the performance of agents much faster that reinforcement learning. If an appropriate knowledge representation is used, the learned knowledge may be analyzed by humans, which allows tracking the learning process

A multi-agent decentralized energy management system based on distributed intelligence for the design and control of autonomous polygeneration microgrids

International Nuclear Information System (INIS)

Karavas, Christos-Spyridon; Kyriakarakos, George; Arvanitis, Konstantinos G.; Papadakis, George

2015-01-01

Highlights: • A decentralized energy management system based on multi agent systems theory. • A decentralized energy management system is technically feasible. • A decentralized approach utilizes the devices better than a centralized one. • A decentralized energy management system is economically competitive. - Abstract: The autonomous polygeneration microgrid topology has been developed in order to cover holistically needs in a remote area such as electrical energy, space heating and cooling, potable water through desalination and hydrogen as fuel for transportation. The existence of an advanced energy management system is essential for the operation of an autonomous polygeneration microgrid. So far, energy management systems based on a centralized management and control have been developed for the autonomous polygeneration microgrid topology based on computational intelligence approaches. A decentralized management and control energy management system can have important benefits, when taking into consideration the autonomous character of these microgrids. This paper presents the design and investigation of a decentralized energy management system for the autonomous polygeneration microgrid topology. The decentralized energy management system gives the possibility to control each unit of the microgrid independently. The most important advantage of using a decentralized architecture is that the managed microgrid has much higher chances of partial operation in cases when malfunctions occur at different parts of it, instead of a complete system breakdown. The designed system was based on a multi-agent system and employed Fuzzy Cognitive Maps for its implementation. It was then compared through a case study with an existing centralized energy management system. The technical performance of the decentralized solution performance is on par with the existing centralized one, presenting improvements in financial and operational terms for the implementation and

Hardware-in-the-Loop Simulation of Distributed Intelligent Energy Management System for Microgrids

Directory of Open Access Journals (Sweden)

Dong-Jun Won

2013-07-01

Full Text Available Microgrids are autonomous low-voltage power distribution systems that contain multiple distributed energy resources (DERs and smart loads that can provide power system operation flexibility. To effectively control and coordinate multiple DERs and loads of microgrids, this paper proposes a distributed intelligent management system that employs a multi-agent-based control system so that delicate decision-making functions can be distributed to local intelligent agents. This paper presents the development of a hardware-in-the-loop simulation (HILS system for distributed intelligent management system for microgrids and its promising application to an emergency demand response program. In the developed HILS system, intelligent agents are developed using microcontrollers and ZigBee wireless communication technology. Power system dynamic models are implemented in real-time simulation environments using the Opal-RT system. This paper presents key features of the data communication and management schemes based on multi-agent concepts. The performance of the developed system is tested for emergency demand response program applications.

Investigation of Evolutionary Pheromone Communication Based on External Measurement and Emergence of Swarm Intelligence

OpenAIRE

川村, 秀憲; 山本, 雅人; 大内, 東

2001-01-01

In this paper, we focus on the emergence phenomenon related with artificial pheromone communication and swarm intelligence among many agents in Ants War environment, in which two colonies of artificial ant agents compete for the limited number of food items in order to survive in evolutionary process. The purpose of this research is to clarify the emerging process of communication and the relationship between communication and swarm intelligence. For investigation of communication, we introdu...

Synergy between Software Product Line and Intelligent Mobile Middleware

DEFF Research Database (Denmark)

Zhang, Weishan; Hansen, Klaus Marius

2007-01-01

with OWL ontology reasoning enhanced BDI (belief-desire-intention) agents in an ongoing research project called PLIMM (product line enabled intelligent mobile middleware), in which Frame based software product line techniques are applied. Besides the advantages of a software product line, our approach can...... handle ontology evolution and keep all related assets in a consistent state. Ontology evolution is a problem that has not been addressed by current mobile middleware. Another advantage is the ability to configure Jadex BDI agents for different purpose and enhance agent intelligence by adding logic...

Artificial intelligence in cardiology

OpenAIRE

Bonderman, Diana

2017-01-01

Summary Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiol...

Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation

Directory of Open Access Journals (Sweden)

An Gary

2008-05-01

Full Text Available Abstract Background One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. Results and Discussion ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems Conclusion A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior

Knowledge Management and Problem Solving in Real Time: The Role of Swarm Intelligence

Directory of Open Access Journals (Sweden)

Chris W Callaghan

2016-06-01

Full Text Available Knowledge management research applied to the development of real-time research capability, or capability to solve societal problems in hours and days instead of years and decades, is perhaps increasingly important, given persistent global problems such as the Zika virus and rapidly developing antibiotic resistance. Drawing on swarm intelligence theory, this paper presents an approach to real-time research problem-solving in the form of a framework for understanding the complexity of real-time research and the challenges associated with maximizing collaboration. The objective of this research is to make explicit certain theoretical, methodological, and practical implications deriving from new literature on emerging technologies and new forms of problem solving and to offer a model of real-time problem solving based on a synthesis of the literature. Drawing from ant colony, bee colony, and particle swarm optimization, as well as other population-based metaheuristics, swarm intelligence principles are derived in support of improved effectiveness and efficiency for multidisciplinary human swarm problem-solving. This synthesis seeks to offer useful insights into the research process, by offering a perspective of what maximized collaboration, as a system, implies for real-time problem solving.

Cost-effective implementation of intelligent systems

Science.gov (United States)

Lum, Henry, Jr.; Heer, Ewald

1990-01-01

Significant advances have occurred during the last decade in knowledge-based engineering research and knowledge-based system (KBS) demonstrations and evaluations using integrated intelligent system technologies. Performance and simulation data obtained to date in real-time operational environments suggest that cost-effective utilization of intelligent system technologies can be realized. In this paper the rationale and potential benefits for typical examples of application projects that demonstrate an increase in productivity through the use of intelligent system technologies are discussed. These demonstration projects have provided an insight into additional technology needs and cultural barriers which are currently impeding the transition of the technology into operational environments. Proposed methods which addresses technology evolution and implementation are also discussed.

JOYO operation support system 'JOYCAT' based on intelligent alarm handling

International Nuclear Information System (INIS)

Tamaoki, Tetsuo; Yamamoto, Hiroki; Sato, Masuo; Yoshida, Megumu; Kaneko, Tomoko; Terunuma, Seiichi; Takatsuto, Hiroshi; Morimoto, Makoto.

1992-01-01

An operation support system for the experimental fast reactor 'JOYO' was developed based on an intelligent alarm-handling. A specific feature of this system, called JOYCAT (JOYO Consulting and Analyzing Tool), is in its sequential processing structure that a uniform treatment by using design knowledge base is firstly applied for all activated alarms, and an exceptional treatment by using heuristic knowledge base is then applied only for the former results. This enables us to achieve real-time and flexible alarm-handling. The first alarm-handling determines the candidates of causal alarms, important alarms with which the operator should firstly cope, through identifying the cause-consequence relations among alarms based on the design knowledge base in which importance and activating conditions are described for each of 640 alarms in a frame format. The second alarm-handling makes the final judgement with the candidates by using the heuristic knowledge base described as production rules. Then, operation manuals concerning the most important alarms are displayed to operators. JOYCAT has been in commission since September of 1990, after a wide scope of validation tests by using an on-site full-scope training simulator. (author)

A development framework for artificial intelligence based distributed operations support systems

Science.gov (United States)

Adler, Richard M.; Cottman, Bruce H.

1990-01-01

Advanced automation is required to reduce costly human operations support requirements for complex space-based and ground control systems. Existing knowledge based technologies have been used successfully to automate individual operations tasks. Considerably less progress has been made in integrating and coordinating multiple operations applications for unified intelligent support systems. To fill this gap, SOCIAL, a tool set for developing Distributed Artificial Intelligence (DAI) systems is being constructed. SOCIAL consists of three primary language based components defining: models of interprocess communication across heterogeneous platforms; models for interprocess coordination, concurrency control, and fault management; and for accessing heterogeneous information resources. DAI applications subsystems, either new or existing, will access these distributed services non-intrusively, via high-level message-based protocols. SOCIAL will reduce the complexity of distributed communications, control, and integration, enabling developers to concentrate on the design and functionality of the target DAI system itself.

Social networks a framework of computational intelligence

CERN Document Server

Chen, Shyi-Ming

2014-01-01

This volume provides the audience with an updated, in-depth and highly coherent material on the conceptually appealing and practically sound information technology of Computational Intelligence applied to the analysis, synthesis and evaluation of social networks. The volume involves studies devoted to key issues of social networks including community structure detection in networks, online social networks, knowledge growth and evaluation, and diversity of collaboration mechanisms.  The book engages a wealth of methods of Computational Intelligence along with well-known techniques of linear programming, Formal Concept Analysis, machine learning, and agent modeling.  Human-centricity is of paramount relevance and this facet manifests in many ways including personalized semantics, trust metric, and personal knowledge management; just to highlight a few of these aspects. The contributors to this volume report on various essential applications including cyber attacks detection, building enterprise social network...

2015 Special Sessions of the 13th International Conference on Practical Applications of Agents and Multi-Agent Systems

CERN Document Server

Hernández, Josefa; Mathieu, Philippe; Campbell, Andrew; Fernández-Caballero, Antonio; Moreno, María; Julián, Vicente; Alonso-Betanzos, Amparo; Jiménez-López, María; Botti, Vicente; Trends in Practical Applications of Agents, Multi-Agent Systems and Sustainability : the PAAMS Collection

2015-01-01

This volume presents the papers that have been accepted for the 2015 special sessions of the 13th International Conference on Practical Applications of Agents and Multi-Agent Systems, held at University of Salamanca, Spain, at 3rd-5th June, 2015: Agents Behaviours and Artificial Markets (ABAM); Agents and Mobile Devices (AM); Multi-Agent Systems and Ambient Intelligence (MASMAI); Web Mining and Recommender systems (WebMiRes); Learning, Agents and Formal Languages (LAFLang); Agent-based Modeling of Sustainable Behavior and Green Economies (AMSBGE); Emotional Software Agents (SSESA) and Intelligent Educational Systems (SSIES). The volume also includes the paper accepted for the Doctoral Consortium in PAAMS 2015. 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 develo...

Application of model-based and knowledge-based measuring methods as analytical redundancy

International Nuclear Information System (INIS)

Hampel, R.; Kaestner, W.; Chaker, N.; Vandreier, B.

1997-01-01

The safe operation of nuclear power plants requires the application of modern and intelligent methods of signal processing for the normal operation as well as for the management of accident conditions. Such modern and intelligent methods are model-based and knowledge-based ones being founded on analytical knowledge (mathematical models) as well as experiences (fuzzy information). In addition to the existing hardware redundancies analytical redundancies will be established with the help of these modern methods. These analytical redundancies support the operating staff during the decision-making. The design of a hybrid model-based and knowledge-based measuring method will be demonstrated by the example of a fuzzy-supported observer. Within the fuzzy-supported observer a classical linear observer is connected with a fuzzy-supported adaptation of the model matrices of the observer model. This application is realized for the estimation of the non-measurable variables as steam content and mixture level within pressure vessels with water-steam mixture during accidental depressurizations. For this example the existing non-linearities will be classified and the verification of the model will be explained. The advantages of the hybrid method in comparison to the classical model-based measuring methods will be demonstrated by the results of estimation. The consideration of the parameters which have an important influence on the non-linearities requires the inclusion of high-dimensional structures of fuzzy logic within the model-based measuring methods. Therefore methods will be presented which allow the conversion of these high-dimensional structures to two-dimensional structures of fuzzy logic. As an efficient solution of this problem a method based on cascaded fuzzy controllers will be presented. (author). 2 refs, 12 figs, 5 tabs

An agent architecture with on-line learning of both procedural and declarative knowledge

Energy Technology Data Exchange (ETDEWEB)

Sun, R.; Peterson, T.; Merrill, E. [Univ. of Alabama, Tuscaloosa, AL (United States)

1996-12-31

In order to develop versatile cognitive agents that learn in situated contexts and generalize resulting knowledge to different environments, we explore the possibility of learning both declarative and procedural knowledge in a hybrid connectionist architecture. The architecture is based on the two-level idea proposed earlier by the author. Declarative knowledge is represented symbolically, while procedural knowledge is represented subsymbolically. The architecture integrates reactive procedures, rules, learning, and decision-making in a unified framework, and structures different learning components (including Q-learning and rule induction) in a synergistic way to perform on-line and integrated learning.

Agent Based Control of Electric Power Systems with Distributed Generation

DEFF Research Database (Denmark)

Saleem, Arshad

and subsystems that are able to coordinate, communicate, cooperate, adapt to emerging situations and self organize in an intelligent way. At the same time, rapid development in information and and communication technologies (ICT) have brought new opportunities and elucidations. New Technologies and standards...... control strategies. The results have been discussed from case studies of multiagent based distributed control scenarios in electric power systems. The main contribution of this work is a proposal for system design methodology for application of intelligent agent technology in power systems....... Situation in Denmark is even more interesting, with a current 20% penetration of wind energy it is moving towards an ambitious goal of 50% penetration by the year 2050. Realization of these concepts requires that power systems should be of distributed nature { consisting of autonomous components...

Combined Intelligent Control (CIC an Intelligent Decision Making Algorithm

Directory of Open Access Journals (Sweden)

Moteaal Asadi Shirzi

2007-03-01

Full Text Available The focus of this research is to introduce the concept of combined intelligent control (CIC as an effective architecture for decision-making and control of intelligent agents and multi-robot sets. Basically, the CIC is a combination of various architectures and methods from fields such as artificial intelligence, Distributed Artificial Intelligence (DAI, control and biological computing. Although any intelligent architecture may be very effective for some specific applications, it could be less for others. Therefore, CIC combines and arranges them in a way that the strengths of any approach cover the weaknesses of others. In this paper first, we introduce some intelligent architectures from a new aspect. Afterward, we offer the CIC by combining them. CIC has been executed in a multi-agent set. In this set, robots must cooperate to perform some various tasks in a complex and nondeterministic environment with a low sensory feedback and relationship. In order to investigate, improve, and correct the combined intelligent control method, simulation software has been designed which will be presented and considered. To show the ability of the CIC algorithm as a distributed architecture, a central algorithm is designed and compared with the CIC.

A Proposed Intelligent Policy-Based Interface for a Mobile eHealth Environment

Science.gov (United States)

Tavasoli, Amir; Archer, Norm

Users of mobile eHealth systems are often novices, and the learning process for them may be very time consuming. In order for systems to be attractive to potential adopters, it is important that the interface should be very convenient and easy to learn. However, the community of potential users of a mobile eHealth system may be quite varied in their requirements, so the system must be able to adapt easily to suit user preferences. One way to accomplish this is to have the interface driven by intelligent policies. These policies can be refined gradually, using inputs from potential users, through intelligent agents. This paper develops a framework for policy refinement for eHealth mobile interfaces, based on dynamic learning from user interactions.

Knowledge based economy in European Union

Directory of Open Access Journals (Sweden)

Ecaterina Stănculescu

2012-04-01

Full Text Available Nowadays we assist at a fundamental change from the economy based mainly on resources to the one based mostly on knowledge. The concept has been launched in the last decade of the past century. The knowledge became a production agent and a value creation instrument for whatever country and of course for an entire community like European Union which is constantly concerned by its development and competitiveness. This paper presents the principal characteristics of the present EU preoccupations with the expansion of a knowledge based economy through the 2020 European Development Strategy for smart, sustainable and inclusive economy, and especially for the Framework Programs (Framework Programme 7 and Competitiveness and Innovation Framework Programme.

Knowledge management: An abstraction of knowledge base and database management systems

Science.gov (United States)

Riedesel, Joel D.

1990-01-01

Artificial intelligence application requirements demand powerful representation capabilities as well as efficiency for real-time domains. Many tools exist, the most prevalent being expert systems tools such as ART, KEE, OPS5, and CLIPS. Other tools just emerging from the research environment are truth maintenance systems for representing non-monotonic knowledge, constraint systems, object oriented programming, and qualitative reasoning. Unfortunately, as many knowledge engineers have experienced, simply applying a tool to an application requires a large amount of effort to bend the application to fit. Much work goes into supporting work to make the tool integrate effectively. A Knowledge Management Design System (KNOMAD), is described which is a collection of tools built in layers. The layered architecture provides two major benefits; the ability to flexibly apply only those tools that are necessary for an application, and the ability to keep overhead, and thus inefficiency, to a minimum. KNOMAD is designed to manage many knowledge bases in a distributed environment providing maximum flexibility and expressivity to the knowledge engineer while also providing support for efficiency.

Cognitive logical systems with artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Liss, E

1983-09-01

The simulation of cognitive processes for the purpose of the technical development of learning systems with intelligent behavior is a basic object of the young interdisciplinary cognition science which is based upon artificial intelligence, cognitive psychology, computer science, linguistics and pedagogics. Cognitive systems may be described as knowledge-based logical systems. Based on structural and functional principles of intelligent automata and elementary information processing systems with structural learning capability the future process, machine and robot controls, advising units and fifth generation computers may be developed.

2013 Chinese Intelligent Automation Conference

CERN Document Server

Deng, Zhidong

2013-01-01

Proceedings of the 2013 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’13, held in Yangzhou, China. The topics include e.g. adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control. Engineers and researchers from academia, industry, and government can gain an inside view of new solutions combining ideas from multiple disciplines in the field of intelligent automation.   Zengqi Sun and Zhidong Deng are professors at the Department of Computer Science, Tsinghua University, China.

2013 Chinese Intelligent Automation Conference

CERN Document Server

Deng, Zhidong

2013-01-01

Proceedings of the 2013 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’13, held in Yangzhou, China. The topics include e.g. adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control. Engineers and researchers from academia, industry, and government can gain an inside view of new solutions combining ideas from multiple disciplines in the field of intelligent automation. Zengqi Sun and Zhidong Deng are professors at the Department of Computer Science, Tsinghua University, China.

Contribution of artificial intelligence to operation

International Nuclear Information System (INIS)

Malvache, P.; Mourlevat, J.L.

1993-01-01

Artificial Intelligence techniques are already used in nuclear plants for assistance to operation: synthesis from numerous information sources may be then derived, based on expert knowledge. Artificial intelligence may be used also for quality and reliability assessment of software-based control-command systems. Various expert systems developed by CEA, EDF and Framatome are presented

ARTIFICIAL INTELLIGENCE IN DETERMINATION OF MARKETING CUSTOMER STRATEGY

OpenAIRE

Markić, Brano; Bijakšić, Sanja; Šantić, Marko

2015-01-01

Artificial intelligence is a computer-based analytical process that tends to create computational systems which we would incline to be called intelligent. Expert systems are the most important part of the artificial intelligence from economic perspective. Expert systems attempt to mimic the human thought process including reasoning and optimization. “Knowledge” is represented by a set of “if-then” rules in a form of knowledge base. The results of artificial intelligence system implementation ...

ARTIFICIAL INTELLIGENCE IN DETERMINATION OF MARKETING CUSTOMER STRATEGY

OpenAIRE

Markić, Brano; Bijakšić, Sanja; Šantić, Marko

2016-01-01

Artificial intelligence is a computer-based analytical process that tends to create computational systems which we would incline to be called intelligent. Expert systems are the most important part of the artificial intelligence from economic perspective. Expert systems attempt to mimic the human thought process including reasoning and optimization. “Knowledge” is represented by a set of “if-then” rules in a form of knowledge base. The results of artificial intelligence system implementation ...

Fault detection and reliability, knowledge based and other approaches

International Nuclear Information System (INIS)

Singh, M.G.; Hindi, K.S.; Tzafestas, S.G.

1987-01-01

These proceedings are split up into four major parts in order to reflect the most significant aspects of reliability and fault detection as viewed at present. The first part deals with knowledge-based systems and comprises eleven contributions from leading experts in the field. The emphasis here is primarily on the use of artificial intelligence, expert systems and other knowledge-based systems for fault detection and reliability. The second part is devoted to fault detection of technological systems and comprises thirteen contributions dealing with applications of fault detection techniques to various technological systems such as gas networks, electric power systems, nuclear reactors and assembly cells. The third part of the proceedings, which consists of seven contributions, treats robust, fault tolerant and intelligent controllers and covers methodological issues as well as several applications ranging from nuclear power plants to industrial robots to steel grinding. The fourth part treats fault tolerant digital techniques and comprises five contributions. Two papers, one on reactor noise analysis, the other on reactor control system design, are indexed separately. (author)

Modeling of Agile Intelligent Manufacturing-oriented Production Scheduling System

Institute of Scientific and Technical Information of China (English)

Zhong-Qi Sheng; Chang-Ping Tang; Ci-Xing Lv

2010-01-01

Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed the scope of individual enterprise and embodied some new features including complexity, dynamicity, distributivity, and compatibility. The agile intelligent manufacturing paradigm calls for a production scheduling system that can support the cooperation among various production sectors, the distribution of various resources to achieve rational organization, scheduling and management of production activities. This paper uses multi-agents technology to build an agile intelligent manufacturing-oriented production scheduling system. Using the hybrid modeling method, the resources and functions of production system are encapsulated, and the agent-based production system model is established. A production scheduling-oriented multi-agents architecture is constructed and a multi-agents reference model is given in this paper.

The representation of knowledge within model-based control systems

International Nuclear Information System (INIS)

Weygand, D.P.; Koul, R.

1987-01-01

Representation of knowledge in artificially intelligent systems is discussed. Types of knowledge that might need to be represented in AI systems are listed, and include knowledge about objects, events, knowledge about how to do things, and knowledge about what human beings know (meta-knowledge). The use of knowledge in AI systems is discussed in terms of acquiring and retrieving knowledge and reasoning about known facts. Different kinds of reasonings or representations are ghen described with some examples given. These include formal reasoning or logical representation, which is related to mathematical logic, production systems, which are based on the idea of condition-action pairs (production), procedural reasoning, which uses pre-formed plans to solve problems, frames, which provide a structure for representing knowledge in an organized manner, direct analogical representations, which represent knowledge in such a manner that permits some observation without deduction

Intelligent Digitized Design Systems for the Management of Design Knowledge Related to Nuclear R&D Institutes

International Nuclear Information System (INIS)

Zheng, M.; Minglu, W.

2016-01-01

Full text: Nuclear R&D is highly knowledge-intensive. With the rapid advent and development of modern information technology, knowledge management in nuclear industry has been provided with new approaches and possibilities. This article introduces a framework of intelligent digitized design system in nuclear R&D phase and finds answer to knowledge application, internal process optimization, experience feedback and further innovation. This framework utilizing digitalization and informatization finds a way to incorporate the process of the “Socialization, Externalization, Combination, Internalization” (SECI) model which include intelligent design process, integrated design software, smart verification and validation simulation platform, experiment data management platform, online monitoring platform and digital twin nuclear power plant, etc. The following case study gives a clear picture of what and how knowledge management has been performed under this framework. Furthermore, important lessons have been summarized. (author

The Epistemic Status of Intelligence

DEFF Research Database (Denmark)

Rønn, Kira Vrist; Høffding, Simon

2012-01-01

We argue that the majority of intelligence definitions fail to recognize that the normative epistemic status of intelligence is knowledge and not an inferior alternative. We refute the counter-arguments that intelligence ought not to be seen as knowledge because of 1) its action-oriented scope...... and robustness of claims to intelligence-knowledge can be assessed....

Extension agents' technical knowledge requirements for effective ...

African Journals Online (AJOL)

Technical knowledge requirements of extension agents were investigated in this study. Data for the study was collected with the aid of structured questionnaire administered to the 78 respondents. It was found that respondents were mainly males, were married, were in the middle age category, had BSc/HND, made ...

Enhancing SAT Based Planning with Landmark Knowledge

NARCIS (Netherlands)

Elffers, J.; Konijnenberg, D.; Walraven, E.M.P.; Spaan, M.T.J.

2013-01-01

Several approaches exist to solve Artificial Intelligence planning problems, but little attention has been given to the combination of using landmark knowledge and satisfiability (SAT). Landmark knowledge has been exploited successfully in the heuristics of classical planning. Recently it was also

Multi-agent control system with information fusion based comfort model for smart buildings

International Nuclear Information System (INIS)

Wang, Zhu; Wang, Lingfeng; Dounis, Anastasios I.; Yang, Rui

2012-01-01

Highlights: ► Proposed a model to manage indoor energy and comfort for smart buildings. ► Developed a control system to maximize comfort with minimum energy consumption. ► Information fusion with ordered weighted averaging aggregation is used. ► Multi-agent technology and heuristic intelligent optimization are deployed in developing the control system. -- Abstract: From the perspective of system control, a smart and green building is a large-scale dynamic system with high complexity and a huge amount of information. Proper combination of the available information and effective control of the overall building system turns out to be a big challenge. In this study, we proposed a building indoor energy and comfort management model based on information fusion using ordered weighted averaging (OWA) aggregation. A multi-agent control system with heuristic intelligent optimization is developed to achieve a high level of comfort with the minimum power consumption. Case studies and simulation results are presented and discussed in this paper.

Multi-Agent System-Based Microgrid Operation Strategy for Demand Response

OpenAIRE

Cha, Hee-Jun; Won, Dong-Jun; Kim, Sang-Hyuk; Chung, Il-Yop; Han, Byung-Moon

2015-01-01

The microgrid and demand response (DR) are important technologies for future power grids. Among the variety of microgrid operations, the multi-agent system (MAS) has attracted considerable attention. In a microgrid with MAS, the agents installed on the microgrid components operate optimally by communicating with each other. This paper proposes an operation algorithm for the individual agents of a test microgrid that consists of a battery energy storage system (BESS) and an intelligent load. A...

A new intrusion prevention model using planning knowledge graph

Science.gov (United States)

Cai, Zengyu; Feng, Yuan; Liu, Shuru; Gan, Yong

2013-03-01

Intelligent plan is a very important research in artificial intelligence, which has applied in network security. This paper proposes a new intrusion prevention model base on planning knowledge graph and discuses the system architecture and characteristics of this model. The Intrusion Prevention based on plan knowledge graph is completed by plan recognition based on planning knowledge graph, and the Intrusion response strategies and actions are completed by the hierarchical task network (HTN) planner in this paper. Intrusion prevention system has the advantages of intelligent planning, which has the advantage of the knowledge-sharing, the response focused, learning autonomy and protective ability.

Cooperative research and development for artificial intelligence based reactor diagnostic system

International Nuclear Information System (INIS)

Reifman, J.; Wei, T.Y.C.; Abboud, R.G.; Chasensky, T.M.

1994-01-01

Artificial Intelligence (AI) techniques in the form of knowledge-based Expert Systems (ESs) have been proposed to provide on-line decision-making support for plant operators during both normal and emergency conditions. However, in spite of the great interest in these advanced techniques, their application in the diagnosis of large-scale processes has not yet reached its full potential because of limitations of the knowledge base. These limitations include problems with knowledge acquisition and the use of an event-oriented approach for process diagnosis. The knowledge base of process diagnosis ESs is generally acquired in a heuristic fashion through empirical associations between plant symptoms and component malfunctions with no reliance on fundamental physical principles. This nonsystematic construction of the knowledge base causes, among other problems, the encoded information to be biased and limited towards the developer's own experience and judgmental knowledge. The use of an event-oriented approach for process diagnosis requires the developer of the knowledge base to anticipate and formulate rules to cover every conceivable plant situation. In addition to yielding a large knowledge base, an undesirable characteristic for an on-line real-time advisory system, an event-oriented approach for diagnosis of large and complex thermal-hydraulic (T-H) based processes cannot guarantee functional completeness and is likely to fail under unanticipated circumstances. Hence, these limitations preclude an effective verification and validation of the knowledge base which is required in industrial applications. In contrast to the heuristic construction of a rigid knowledge base that uses an event-oriented approach for process diagnosis, the authors propose a different approach that involves the systematic construction of a hierarchical knowledge base with two levels

Modeling and Simulation for the Knowledge Management for Distributed Tracking (KMDT) Program

National Research Council Canada - National Science Library

Ceruti, Marion G; Wright, Tedd L; Wilcox, Dwight R; McGirr, Scott C

2005-01-01

.... The focus of the simulation effort is on a hypothetical scenario designed to simulate how knowledge management technologies, such as ontologies and intelligent agents can be used to improve battle space awareness...

Intelligent interaction based on holographic personalized portal

Directory of Open Access Journals (Sweden)

Yadong Huang

2017-06-01

Full Text Available Purpose – The purpose of this paper is to study the architecture of holographic personalized portal, user modeling, commodity modeling and intelligent interaction. Design/methodology/approach – In this paper, the authors propose crowd-science industrial ecological system based on holographic personalized portal and its interaction. The holographic personality portal is based on holographic enterprises, commodities and consumers, and the personalized portal consists of accurate ontology, reliable supply, intelligent demand and smart cyberspace. Findings – The personalized portal can realize the information acquisition, characteristic analysis and holographic presentation. Then, the intelligent interaction, e.g. demand decomposition, personalized search, personalized presentation and demand prediction, will be implemented within the personalized portal. Originality/value – The authors believe that their work on intelligent interaction based on holographic personalized portal, which has been first proposed in this paper, is innovation focusing on the interaction between intelligence and convenience.

Agent autonomy approach to probabilistic physics-of-failure modeling of complex dynamic systems with interacting failure mechanisms

Science.gov (United States)

Gromek, Katherine Emily

A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.

Importance of the Alternative Five and Trait Emotional Intelligence for Agentic and Communal Domains of Satisfaction

Directory of Open Access Journals (Sweden)

Andreja Avsec

2011-12-01

Full Text Available Many studies supported the importance of trait emotional intelligence (EI for subjective well-being but specific domains of life-satisfaction were rarely of interest. Our study investigated whether emotional intelligence is more important for interpersonal or communal-related domains (e.g. satisfaction with friends, intimate partners than for agentic domains of satisfaction (e.g. satisfaction with finances, work. Due to the problematic differential validity of trait EI from personality, the relationship between trait EI and domains of satisfaction was controlled for by personality. Slovene students and young adults (N=442 completed the Emotional Skills and Competence Questionnaire and the Zuckerman-Kuhlman Personality Questionnaire, and rated their satisfaction with 12 aspects of life. Principal component analysis of these domains revealed three components, explaining 62% of total variance. The communal domains included self-reported satisfaction with popularity, respect, influence on others, family relationships, and intimate relationship. The agentic domains included satisfaction with professional carrier, financial situation, academic education, and achieved goals. The physical domains component was comprised of satisfaction with appearance, fitness, and health. After accounting for personality, trait EI explained 16% of variance in communal domain and 10% of variance in agentic domain, thus suggesting greater importance of trait EI for interpersonal domains. However, trait EI seems to play an important role for satisfaction in the agentic domains also, as successful management of our emotions can help us reach our goals and thus be more satisfied.

A Case Study of the Link between Artificial Intelligence and Knowledge Creation in Emerging Technology in China

DEFF Research Database (Denmark)

Søberg, Peder Veng

2017-01-01

in much knowledge creation research, the empirical insights come from a case study in a Chinese startup SME (small and medium-sized enterprise) within the emerging industry of visual intelligence/surveillance systems. The findings, extracted from semi-structured interviews as well as observations, suggest...... of consent requirements when collecting information and a willing population makes China an ideal test bed for visual intelligence technologies. The chapter exposes the shortcomings of the existing knowledge creation theory and bridges these with insights on how to overcome them in different contexts...

Energy Logic (EL): a novel fusion engine of multi-modality multi-agent data/information fusion for intelligent surveillance systems

Science.gov (United States)

Rababaah, Haroun; Shirkhodaie, Amir

2009-04-01

The rapidly advancing hardware technology, smart sensors and sensor networks are advancing environment sensing. One major potential of this technology is Large-Scale Surveillance Systems (LS3) especially for, homeland security, battlefield intelligence, facility guarding and other civilian applications. The efficient and effective deployment of LS3 requires addressing number of aspects impacting the scalability of such systems. The scalability factors are related to: computation and memory utilization efficiency, communication bandwidth utilization, network topology (e.g., centralized, ad-hoc, hierarchical or hybrid), network communication protocol and data routing schemes; and local and global data/information fusion scheme for situational awareness. Although, many models have been proposed to address one aspect or another of these issues but, few have addressed the need for a multi-modality multi-agent data/information fusion that has characteristics satisfying the requirements of current and future intelligent sensors and sensor networks. In this paper, we have presented a novel scalable fusion engine for multi-modality multi-agent information fusion for LS3. The new fusion engine is based on a concept we call: Energy Logic. Experimental results of this work as compared to a Fuzzy logic model strongly supported the validity of the new model and inspired future directions for different levels of fusion and different applications.

Knowledge-based information systems in practice

CERN Document Server

Jain, Lakhmi; Watada, Junzo; Howlett, Robert

2015-01-01

This book contains innovative research from leading researchers who presented their work at the 17th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2013, held in Kitakyusha, Japan, in September 2013. The conference provided a competitive field of 236 contributors, from which 38 authors expanded their contributions and only 21 published. A plethora of techniques and innovative applications are represented within this volume. The chapters are organized using four themes. These topics include: data mining, knowledge management, advanced information processes and system modelling applications. Each topic contains multiple contributions and many offer case studies or innovative examples. Anyone that wants to work with information repositories or process knowledge should consider reading one or more chapters focused on their technique of choice. They may also benefit from reading other chapters to assess if an alternative technique represents a more suitable app...

Artificial Intelligence in Civil Engineering

Directory of Open Access Journals (Sweden)

Pengzhen Lu

2012-01-01

Full Text Available Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks, fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing. The main research trends are also pointed out in the end. The paper provides an overview of the advances of artificial intelligence applied in civil engineering.

Emotional intelligence education in pre-registration nursing programmes: an integrative review.

Science.gov (United States)

Foster, Kim; McCloughen, Andrea; Delgado, Cynthia; Kefalas, Claudia; Harkness, Emily

2015-03-01

To investigate the state of knowledge on emotional intelligence (EI) education in pre-registration nursing programmes. Integrative literature review. CINAHL, Medline, Scopus, ERIC, and Web of Knowledge electronic databases were searched for abstracts published in English between 1992-2014. Data extraction and constant comparative analysis of 17 articles. Three categories were identified: Constructs of emotional intelligence; emotional intelligence curricula components; and strategies for emotional intelligence education. A wide range of emotional intelligence constructs were found, with a predominance of trait-based constructs. A variety of strategies to enhance students' emotional intelligence skills were identified, but limited curricula components and frameworks reported in the literature. An ability-based model for curricula and learning and teaching approaches is recommended. Copyright © 2014. Published by Elsevier Ltd.

Knowledge management of eco-industrial park for efficient energy utilization through ontology-based approach

International Nuclear Information System (INIS)

Zhang, Chuan; Romagnoli, Alessandro; Zhou, Li; Kraft, Markus

2017-01-01

Highlights: •An intelligent energy management system for Eco-Industrial Park (EIP) is proposed. •An explicit domain ontology for EIP energy management is designed. •Ontology-based approach can increase knowledge interoperability within EIP. •Ontology-based approach can allow self-optimization without human intervention in EIP. •The proposed system harbours huge potential in the future scenario of Internet of Things. -- Abstract: An ontology-based approach for Eco-Industrial Park (EIP) knowledge management is proposed in this paper. The designed ontology in this study is formalized conceptualization of EIP. Based on such an ontological representation, a Knowledge-Based System (KBS) for EIP energy management named J-Park Simulator (JPS) is developed. By applying JPS to the solution of EIP waste heat utilization problem, the results of this study show that ontology is a powerful tool for knowledge management of complex systems such as EIP. The ontology-based approach can increase knowledge interoperability between different companies in EIP. The ontology-based approach can also allow intelligent decision making by using disparate data from remote databases, which implies the possibility of self-optimization without human intervention scenario of Internet of Things (IoT). It is shown through this study that KBS can bridge the communication gaps between different companies in EIP, sequentially more potential Industrial Symbiosis (IS) links can be established to improve the overall energy efficiency of the whole EIP.

Intelligent assembly time analysis, using a digital knowledge based approach

NARCIS (Netherlands)

Jin, Y.; Curran, R.; Butterfield, J.; Burke, R.; Welch, B.

2009-01-01

The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for

Intelligent Decision Technologies : Proceedings of the 4th International Conference on Intelligent Decision Technologies

CERN Document Server

Watanabe, Toyohide; Phillips-Wren, Gloria; Howlett, Robert; Jain, Lakhmi

2012-01-01

The Intelligent Decision Technologies (IDT) International Conference encourages an interchange of research on intelligent systems and intelligent technologies that enhance or improve decision making. The focus of IDT is interdisciplinary and includes research on all aspects of intelligent decision technologies, from fundamental development to real applications. IDT has the potential to expand their support of decision making in such areas as finance, accounting, marketing, healthcare, medical and diagnostic systems, military decisions, production and operation, networks, traffic management, crisis response, human-machine interfaces, financial and stock market monitoring and prediction, and robotics. Intelligent decision systems implement advances in intelligent agents, fuzzy logic, multi-agent systems, artificial neural networks, and genetic algorithms, among others.  Emerging areas of active research include virtual decision environments, social networking, 3D human-machine interfaces, cognitive interfaces,...

ISPE: A knowledge-based system for fluidization studies. 1990 Annual report

Energy Technology Data Exchange (ETDEWEB)

Reddy, S.

1991-01-01

Chemical engineers use mathematical simulators to design, model, optimize and refine various engineering plants/processes. This procedure requires the following steps: (1) preparation of an input data file according to the format required by the target simulator; (2) excecuting the simulation; and (3) analyzing the results of the simulation to determine if all ``specified goals`` are satisfied. If the goals are not met, the input data file must be modified and the simulation repeated. This multistep process is continued until satisfactory results are obtained. This research was undertaken to develop a knowledge based system, IPSE (Intelligent Process Simulation Environment), that can enhance the productivity of chemical engineers/modelers by serving as an intelligent assistant to perform a variety tasks related to process simulation. ASPEN, a widely used simulator by the US Department of Energy (DOE) at Morgantown Energy Technology Center (METC) was selected as the target process simulator in the project. IPSE, written in the C language, was developed using a number of knowledge-based programming paradigms: object-oriented knowledge representation that uses inheritance and methods, rulebased inferencing (includes processing and propagation of probabilistic information) and data-driven programming using demons. It was implemented using the knowledge based environment LASER. The relationship of IPSE with the user, ASPEN, LASER and the C language is shown in Figure 1.

Integration of design and manufacturing in a virtual enterprise using enterprise rules, intelligent agents, STEP, and work flow

Science.gov (United States)

Gilman, Charles R.; Aparicio, Manuel; Barry, J.; Durniak, Timothy; Lam, Herman; Ramnath, Rajiv

1997-12-01

An enterprise's ability to deliver new products quickly and efficiently to market is critical for competitive success. While manufactureres recognize the need for speed and flexibility to compete in this market place, companies do not have the time or capital to move to new automation technologies. The National Industrial Information Infrastructure Protocols Consortium's Solutions for MES Adaptable Replicable Technology (NIIIP SMART) subgroup is developing an information infrastructure to enable the integration and interoperation among Manufacturing Execution Systems (MES) and Enterprise Information Systems within an enterprise or among enterprises. The goal of these developments is an adaptable, affordable, reconfigurable, integratable manufacturing system. Key innovative aspects of NIIIP SMART are: (1) Design of an industry standard object model that represents the diverse aspects of MES. (2) Design of a distributed object network to support real-time information sharing. (3) Product data exchange based on STEP and EXPRESS (ISO 10303). (4) Application of workflow and knowledge management technologies to enact manufacturing and business procedures and policy. (5) Application of intelligent agents to support emergent factories. This paper illustrates how these technologies have been incorporated into the NIIIP SMART system architecture to enable the integration and interoperation of existing tools and future MES applications in a 'plug and play' environment.

STRUTEX: A prototype knowledge-based system for initially configuring a structure to support point loads in two dimensions

Science.gov (United States)

Rogers, James L.; Feyock, Stefan; Sobieszczanski-Sobieski, Jaroslaw

1988-01-01

The purpose of this research effort is to investigate the benefits that might be derived from applying artificial intelligence tools in the area of conceptual design. Therefore, the emphasis is on the artificial intelligence aspects of conceptual design rather than structural and optimization aspects. A prototype knowledge-based system, called STRUTEX, was developed to initially configure a structure to support point loads in two dimensions. This system combines numerical and symbolic processing by the computer with interactive problem solving aided by the vision of the user by integrating a knowledge base interface and inference engine, a data base interface, and graphics while keeping the knowledge base and data base files separate. The system writes a file which can be input into a structural synthesis system, which combines structural analysis and optimization.

Speech Intelligibility Prediction Based on Mutual Information

DEFF Research Database (Denmark)

Jensen, Jesper; Taal, Cees H.

2014-01-01

This paper deals with the problem of predicting the average intelligibility of noisy and potentially processed speech signals, as observed by a group of normal hearing listeners. We propose a model which performs this prediction based on the hypothesis that intelligibility is monotonically related...... to the mutual information between critical-band amplitude envelopes of the clean signal and the corresponding noisy/processed signal. The resulting intelligibility predictor turns out to be a simple function of the mean-square error (mse) that arises when estimating a clean critical-band amplitude using...... a minimum mean-square error (mmse) estimator based on the noisy/processed amplitude. The proposed model predicts that speech intelligibility cannot be improved by any processing of noisy critical-band amplitudes. Furthermore, the proposed intelligibility predictor performs well ( ρ > 0.95) in predicting...

Soft computing in artificial intelligence

CERN Document Server

Matson, Eric

2014-01-01

This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, ind...

Modelling intelligent behavior

Science.gov (United States)

Green, H. S.; Triffet, T.

1993-01-01

An introductory discussion of the related concepts of intelligence and consciousness suggests criteria to be met in the modeling of intelligence and the development of intelligent materials. Methods for the modeling of actual structure and activity of the animal cortex have been found, based on present knowledge of the ionic and cellular constitution of the nervous system. These have led to the development of a realistic neural network model, which has been used to study the formation of memory and the process of learning. An account is given of experiments with simple materials which exhibit almost all properties of biological synapses and suggest the possibility of a new type of computer architecture to implement an advanced type of artificial intelligence.

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...

Reviewing Microgrids from a Multi-Agent Systems Perspective

Directory of Open Access Journals (Sweden)

Jorge J. Gomez-Sanz

2014-05-01

Full Text Available The construction of Smart Grids leads to the main question of what kind of intelligence such grids require and how to build it. Some authors choose an agent based solution to realize this intelligence. However, there may be some misunderstandings in the way this technology is being applied. This paper exposes some considerations of this subject, focusing on the Microgrid level, and shows a practical example through INGENIAS methodology, which is a methodology for the development of Agent Oriented systems that applies Model Driven Development techniques to produce fully functional Multi-Agent Systems.

Multi-Agent Based Microscopic Simulation Modeling for Urban Traffic Flow

Directory of Open Access Journals (Sweden)

Xianyan Kuang

2014-10-01

Full Text Available Traffic simulation plays an important role in the evaluation of traffic decisions. The movement of vehicles essentially is the operating process of drivers, in order to reproduce the urban traffic flow from the micro-aspect on computer, this paper establishes an urban traffic flow microscopic simulation system (UTFSim based on multi-agent. The system is seen as an intelligent virtual environment system (IVES, and the four-layer structure of it is built. The road agent, vehicle agent and signal agent are modeled. The concept of driving trajectory which is divided into LDT (Lane Driving Trajectory and VDDT (Vehicle Dynamic Driving Trajectory is introduced. The “Link-Node” road network model is improved. The driving behaviors including free driving, following driving, lane changing, slowing down, vehicle stop, etc. are analyzed. The results of the signal control experiments utilizing the UTFSim developed in the platform of Visual Studio. NET indicates that it plays a good performance and can be used in the evaluation of traffic management and control.

Artificial intelligence based decision support for trumpeter swan management

Science.gov (United States)

Sojda, Richard S.

2002-01-01

The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988

Artificial Intelligence Techniques: Applications for Courseware Development.

Science.gov (United States)

Dear, Brian L.

1986-01-01

Introduces some general concepts and techniques of artificial intelligence (natural language interfaces, expert systems, knowledge bases and knowledge representation, heuristics, user-interface metaphors, and object-based environments) and investigates ways these techniques might be applied to analysis, design, development, implementation, and…

Modelling the Interaction Levels in HCI Using an Intelligent Hybrid System with Interactive Agents: A Case Study of an Interactive Museum Exhibition Module in Mexico

Directory of Open Access Journals (Sweden)

Ricardo Rosales

2018-03-01

Full Text Available Technology has become a necessity in our everyday lives and essential for completing activities we typically take for granted; technologies can assist us by completing set tasks or achieving desired goals with optimal affect and in the most efficient way, thereby improving our interactive experiences. This paper presents research that explores the representation of user interaction levels using an intelligent hybrid system approach with agents. We evaluate interaction levels of Human-Computer Interaction (HCI with the aim of enhancing user experiences. We consider the description of interaction levels using an intelligent hybrid system to provide a decision-making system to an agent that evaluates interaction levels when using interactive modules of a museum exhibition. The agents represent a high-level abstraction of the system, where communication takes place between the user, the exhibition and the environment. In this paper, we provide a means to measure the interaction levels and natural behaviour of users, based on museum user-exhibition interaction. We consider that, by analysing user interaction in a museum, we can help to design better ways to interact with exhibition modules according to the properties and behaviour of the users. An interaction-evaluator agent is proposed to achieve the most suitable representation of the interaction levels with the aim of improving user interactions to offer the most appropriate directions, services, content and information, thereby improving the quality of interaction experienced between the user-agent and exhibition-agent.

Expertik: Experience with Artificial Intelligence and Mobile Computing

Directory of Open Access Journals (Sweden)

José Edward Beltrán Lozano

2013-06-01

Full Text Available This article presents the experience in the development of services based in Artificial Intelligence, Service Oriented Architecture, mobile computing. It aims to combine technology offered by mobile computing provides techniques and artificial intelligence through a service provide diagnostic solutions to problems in industrial maintenance. It aims to combine technology offered by mobile computing and the techniques artificial intelligence through a service to provide diagnostic solutions to problems in industrial maintenance. For service creation are identified the elements of an expert system, the knowledge base, the inference engine and knowledge acquisition interfaces and their consultation. The applications were developed in ASP.NET under architecture three layers. The data layer was developed conjunction in SQL Server with data management classes; business layer in VB.NET and the presentation layer in ASP.NET with XHTML. Web interfaces for knowledge acquisition and query developed in Web and Mobile Web. The inference engine was conducted in web service developed for the fuzzy logic model to resolve requests from applications consulting knowledge (initially an exact rule-based logic within this experience to resolve requests from applications consulting knowledge. This experience seeks to strengthen a technology-based company to offer services based on AI for service companies Colombia.

Agent Based Model of Livestock Movements

Science.gov (United States)

Miron, D. J.; Emelyanova, I. V.; Donald, G. E.; Garner, G. M.

The modelling of livestock movements within Australia is of national importance for the purposes of the management and control of exotic disease spread, infrastructure development and the economic forecasting of livestock markets. In this paper an agent based model for the forecasting of livestock movements is presented. This models livestock movements from farm to farm through a saleyard. The decision of farmers to sell or buy cattle is often complex and involves many factors such as climate forecast, commodity prices, the type of farm enterprise, the number of animals available and associated off-shore effects. In this model the farm agent's intelligence is implemented using a fuzzy decision tree that utilises two of these factors. These two factors are the livestock price fetched at the last sale and the number of stock on the farm. On each iteration of the model farms choose either to buy, sell or abstain from the market thus creating an artificial supply and demand. The buyers and sellers then congregate at the saleyard where livestock are auctioned using a second price sealed bid. The price time series output by the model exhibits properties similar to those found in real livestock markets.

The Jekyll and Hyde of emotional intelligence: emotion-regulation knowledge facilitates both prosocial and interpersonally deviant behavior.

Science.gov (United States)

Côté, Stéphane; Decelles, Katherine A; McCarthy, Julie M; Van Kleef, Gerben A; Hideg, Ivona

2011-08-01

Does emotional intelligence promote behavior that strictly benefits the greater good, or can it also advance interpersonal deviance? In the investigation reported here, we tested the possibility that a core facet of emotional intelligence--emotion-regulation knowledge--can promote both prosocial and interpersonally deviant behavior. Drawing from research on how the effective regulation of emotion promotes goal achievement, we predicted that emotion-regulation knowledge would strengthen the effects of other-oriented and self-oriented personality traits on prosocial behavior and interpersonal deviance, respectively. Two studies supported our predictions. Among individuals with higher emotion-regulation knowledge, moral identity exhibited a stronger positive association with prosocial behavior in a social dilemma (Study 1), and Machiavellianism exhibited a stronger positive association with interpersonal deviance in the workplace (Study 2). Thus, emotion-regulation knowledge has a positive side and a dark side.

Knowledge Prediction of Different Students’ Categories Trough an Intelligent Testing

Directory of Open Access Journals (Sweden)

Irina Zheliazkova

2015-02-01

Full Text Available Student’s modelling, prediction, and grouping have remained open research issues in the multi-disciplinary area of educational data mining. The purpose of this study is to predict the correct knowledge of different categories of tested students: good, very good, and all. The experimental data set was gathered from an intelligent post-test performance containing student’s correct, missing, and wrong knowledge, time undertaken, and final mark. The proposed procedure applies consequently correlation analysis, simple and multiple liner regression using a power specialized tool for programming by the teacher. The finding is that the accuracy of the procedure is satisfactory for the three students’ categories. The experiment also confirms some findings of other researchers and previous authors’ team studies.

Interactive analysis of geodata based intelligence

Science.gov (United States)

Wagner, Boris; Eck, Ralf; Unmüessig, Gabriel; Peinsipp-Byma, Elisabeth

2016-05-01

When a spatiotemporal events happens, multi-source intelligence data is gathered to understand the problem, and strategies for solving the problem are investigated. The difficulties arising from handling spatial and temporal intelligence data represent the main problem. The map might be the bridge to visualize the data and to get the most understand model for all stakeholders. For the analysis of geodata based intelligence data, a software was developed as a working environment that combines geodata with optimized ergonomics. The interaction with the common operational picture (COP) is so essentially facilitated. The composition of the COP is based on geodata services, which are normalized by international standards of the Open Geospatial Consortium (OGC). The basic geodata are combined with intelligence data from images (IMINT) and humans (HUMINT), stored in a NATO Coalition Shared Data Server (CSD). These intelligence data can be combined with further information sources, i.e., live sensors. As a result a COP is generated and an interaction suitable for the specific workspace is added. This allows the users to work interactively with the COP, i.e., searching with an on board CSD client for suitable intelligence data and integrate them into the COP. Furthermore, users can enrich the scenario with findings out of the data of interactive live sensors and add data from other sources. This allows intelligence services to contribute effectively to the process by what military and disaster management are organized.

Intelligent Assistants for Distributed Knowledge Acquisition, Integration, Validation, and Maintenance

National Research Council Canada - National Science Library

Tecuci, Gheorghe; Boicu, Mihai

2008-01-01

This research has developed an integrated set of tools, called Disciple 2008 learning agent shell, for continuous acquisition of knowledge directly from subject matter experts, and for the integration...

An intelligent human-machine system based on an ecological interface design concept