WorldWideScience

Sample records for artificial intelligence applied

  1. Artificial intelligence technologies applied to terrain analysis

    Energy Technology Data Exchange (ETDEWEB)

    Wright, J.C. (Army Training and Doctrine Command, Fort Monroe, VA (USA)); Powell, D.R. (Los Alamos National Lab., NM (USA))

    1990-01-01

    The US Army Training and Doctrine Command is currently developing, in cooperation with Los Alamos National Laboratory, a Corps level combat simulation to support military analytical studies. This model emphasizes high resolution modeling of the command and control processes, with particular attention to architectural considerations that enable extension of the model. A planned future extension is the inclusion of an computer based planning capability for command echelons that can be dynamical invoked during the execution of then model. Command and control is the process through which the activities of military forces are directed, coordinated, and controlled to achieve the stated mission. To perform command and control the commander must understand the mission, perform terrain analysis, understand his own situation and capabilities as well as the enemy situation and his probable actions. To support computer based planning, data structures must be available to support the computer's ability to understand'' the mission, terrain, own capabilities, and enemy situation. The availability of digitized terrain makes it feasible to apply artificial intelligence technologies to emulate the terrain analysis process, producing data structures for uses in planning. The work derived thus for to support the understanding of terrain is the topic of this paper. 13 refs., 5 figs., 6 tabs.

  2. Artificial intelligence applied to process signal analysis

    Energy Technology Data Exchange (ETDEWEB)

    Corsberg, D.

    1986-01-01

    Many space station processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect of the human/machine interface is the analysis and display of process information. Human operators can be overwhelmed by large clusters of alarms that inhibit their ability to diagnose and respond to a disturbance. Using artificial intelligence techniques and a knowledge-based appraoch to this problem, the power of the computer can be used to filter and analyze plant sensor data. This will provide operators with a better description of the process state. Once a process state is recognized, automatic action could be initiated and proper system response monitored. 8 refs.

  3. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

    Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

  4. Artificial intelligence applied to fuel management in BWR type reactors

    International Nuclear Information System (INIS)

    In this work two techniques of artificial intelligence, neural networks and genetic algorithms were applied to a practical problem of nuclear fuel management; the determination of the optimal fuel reload for a BWR type reactor. This is an important problem in the design of the operation cycle of the reactor. As a result of the application of these techniques, comparable or even better reloads proposals than those given by expert companies in the subject were obtained. Additionally, two other simpler problems in reactor physics were solved: the determination of the axial power profile and the prediction of the value of some variables of interest at the end of the operation cycle of the reactor. Neural networks and genetic algorithms have been applied to solve many problems of engineering because of their versatility but they have been rarely used in the area of fuel management. The results obtained in this thesis indicates the convenience of undertaking further work on this area and suggest the application of these techniques of artificial intelligence to the solution of other problems in nuclear reactor physics. (Author)

  5. Artificial Intelligence and Systems Theory: Applied to Cooperative Robots

    OpenAIRE

    Lima, Pedro U.; Custodio, Luis M. M.

    2004-01-01

    This paper describes an approach to the design of a population of cooperative robots based on concepts borrowed from Systems Theory and Artificial Intelligence. The research has been developed under the SocRob project, carried out by the Intelligent Systems Laboratory at the Institute for Systems and Robotics - Instituto Superior T?cnico (ISR/IST) in Lisbon. The acronym of the project stands both for "Society of Robots" and "Soccer Robots", the case study where we are test...

  6. APPLYING ARTIFICIAL INTELLIGENCE TECHNIQUES TO HUMAN-COMPUTER INTERFACES

    DEFF Research Database (Denmark)

    Sonnenwald, Diane H.

    1988-01-01

    A description is given of UIMS (User Interface Management System), a system using a variety of artificial intelligence techniques to build knowledge-based user interfaces combining functionality and information from a variety of computer systems that maintain, test, and configure customer telephone...... and data networks. Three artificial intelligence (AI) techniques used in UIMS are discussed, namely, frame representation, object-oriented programming languages, and rule-based systems. The UIMS architecture is presented, and the structure of the UIMS is explained in terms of the AI techniques....

  7. Artificial Intelligence Applied to Project Success: A Literature Review

    OpenAIRE

    Daniel Magaña Martínez; Juan Carlos Fernandez-Rodriguez

    2015-01-01

    Project control and monitoring tools are based on expert judgement and parametric tools. Projects are the means by which companies implement their strategies. However project success rates are still very low. This is a worrying situation that has a great economic impact so alternative tools for project success prediction must be proposed in order to estimate project success or identify critical factors of success. Some of these tools are based on Artificial Intelligence. In this paper we will...

  8. Artificial intelligence

    CERN Document Server

    Ennals, J R

    1987-01-01

    Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

  9. Artificial intelligence in medicine: humans need not apply?

    Science.gov (United States)

    Diprose, William; Buist, Nicholas

    2016-01-01

    Artificial intelligence (AI) is a rapidly growing field with a wide range of applications. Driven by economic constraints and the potential to reduce human error, we believe that over the coming years AI will perform a significant amount of the diagnostic and treatment decision-making traditionally performed by the doctor. Humans would continue to be an important part of healthcare delivery, but in many situations, less expensive fit-for-purpose healthcare workers could be trained to 'fill the gaps' where AI are less capable. As a result, the role of the doctor as an expensive problem-solver would become redundant. PMID:27349266

  10. Artificial Intelligence

    CERN Document Server

    Warwick, Kevin

    2011-01-01

    if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

  11. Artificial Intelligence and Systems Theory: Applied to Cooperative Robots

    Directory of Open Access Journals (Sweden)

    Pedro U. Lima

    2008-11-01

    Full Text Available This paper describes an approach to the design of a population of cooperative robots based on concepts borrowed from Systems Theory and Artificial Intelligence. The research has been developed under the SocRob project, carried out by the Intelligent Systems Laboratory at the Institute for Systems and Robotics - Instituto Superior T?cnico (ISR/IST in Lisbon. The acronym of the project stands both for "Society of Robots" and "Soccer Robots", the case study where we are testing our population of robots. Designing soccer robots is a very challenging problem, where the robots must act not only to shoot a ball towards the goal, but also to detect and avoid static (walls, stopped robots and dynamic (moving robots obstacles. Furthermore, they must cooperate to defeat an opposing team. Our past and current research in soccer robotics includes cooperative sensor fusion for world modeling, object recognition and tracking, robot navigation, multi-robot distributed task planning and coordination, including cooperative reinforcement learning in cooperative and adversarial environments, and behavior-based architectures for real time task execution of cooperating robot teams.

  12. Artificial intelligence

    International Nuclear Information System (INIS)

    A vivid example of the growing need for frontier physics experiments to make use of frontier technology is in the field of artificial intelligence and related themes. This was reflected in the second international workshop on 'Software Engineering, Artificial Intelligence and Expert Systems in High Energy and Nuclear Physics' which took place from 13-18 January at France Telecom's Agelonde site at La Londe des Maures, Provence. It was the second in a series, the first having been held at Lyon in 1990

  13. Artificial Intelligence.

    Science.gov (United States)

    Lawrence, David R; Palacios-González, César; Harris, John

    2016-04-01

    It seems natural to think that the same prudential and ethical reasons for mutual respect and tolerance that one has vis-à-vis other human persons would hold toward newly encountered paradigmatic but nonhuman biological persons. One also tends to think that they would have similar reasons for treating we humans as creatures that count morally in our own right. This line of thought transcends biological boundaries-namely, with regard to artificially (super)intelligent persons-but is this a safe assumption? The issue concerns ultimate moral significance: the significance possessed by human persons, persons from other planets, and hypothetical nonorganic persons in the form of artificial intelligence (AI). This article investigates why our possible relations to AI persons could be more complicated than they first might appear, given that they might possess a radically different nature to us, to the point that civilized or peaceful coexistence in a determinate geographical space could be impossible to achieve. PMID:26957450

  14. Applying artificial intelligence technology to support decision-making in nursing: A case study in Taiwan.

    Science.gov (United States)

    Liao, Pei-Hung; Hsu, Pei-Ti; Chu, William; Chu, Woei-Chyn

    2015-06-01

    This study applied artificial intelligence to help nurses address problems and receive instructions through information technology. Nurses make diagnoses according to professional knowledge, clinical experience, and even instinct. Without comprehensive knowledge and thinking, diagnostic accuracy can be compromised and decisions may be delayed. We used a back-propagation neural network and other tools for data mining and statistical analysis. We further compared the prediction accuracy of the previous methods with an adaptive-network-based fuzzy inference system and the back-propagation neural network, identifying differences in the questions and in nurse satisfaction levels before and after using the nursing information system. This study investigated the use of artificial intelligence to generate nursing diagnoses. The percentage of agreement between diagnoses suggested by the information system and those made by nurses was as much as 87 percent. When patients are hospitalized, we can calculate the probability of various nursing diagnoses based on certain characteristics. PMID:26021669

  15. Artificial intelligence methods applied for quantitative analysis of natural radioactive sources

    International Nuclear Information System (INIS)

    Highlights: ► Basic description of artificial neural networks. ► Natural gamma ray sources and problem of detections. ► Application of neural network for peak detection and activity determination. - Abstract: Artificial neural network (ANN) represents one of artificial intelligence methods in the field of modeling and uncertainty in different applications. The objective of the proposed work was focused to apply ANN to identify isotopes and to predict uncertainties of their activities of some natural radioactive sources. The method was tested for analyzing gamma-ray spectra emitted from natural radionuclides in soil samples detected by a high-resolution gamma-ray spectrometry based on HPGe (high purity germanium). The principle of the suggested method is described, including, relevant input parameters definition, input data scaling and networks training. It is clear that there is satisfactory agreement between obtained and predicted results using neural network.

  16. Artificial intelligence

    OpenAIRE

    Duda, Antonín

    2009-01-01

    Abstract : Issue of this work is to acquaint the reader with the history of artificial inteligence, esspecialy branch of chess computing. Main attention is given to progress from fifties to the present. The work also deals with fighting chess programs against each other, and against human opponents. The greatest attention is focused on 1997 and duel Garry Kasparov against chess program Deep Blue. The work is divided into chapters according to chronological order.

  17. 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...

  18. Intelligence: Real or artificial?

    OpenAIRE

    Schlinger, Henry D

    1992-01-01

    Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally r...

  19. Quo Vadis, Artificial Intelligence?

    OpenAIRE

    Alfons Schuster; Daniel Berrar; Naoyuki Sato

    2010-01-01

    Since its conception in the mid 1950s, artificial intelligence with its great ambition to understand and emulate intelligence in natural and artificial environments alike is now a truly multidisciplinary field that reaches out and is inspired by a great diversity of other fields. Rapid advances in research and technology in various fields have created environments into which artificial intelligence could embed itself naturally and comfortably. Neuroscience with its desire to understand nervou...

  20. 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.

  1. Principles of artificial intelligence

    CERN Document Server

    Nilsson, Nils J

    1980-01-01

    A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of th

  2. Bayesian artificial intelligence

    CERN Document Server

    Korb, Kevin B

    2010-01-01

    Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.New to the Second EditionNew chapter on Bayesian network classifiersNew section on object-oriente

  3. The systems approach for applying artificial intelligence to space station automation (Invited Paper)

    Science.gov (United States)

    Grose, Vernon L.

    1985-12-01

    The progress of technology is marked by fragmentation -- dividing research and development into ever narrower fields of specialization. Ultimately, specialists know everything about nothing. And hope for integrating those slender slivers of specialty into a whole fades. Without an integrated, all-encompassing perspective, technology becomes applied in a lopsided and often inefficient manner. A decisionary model, developed and applied for NASA's Chief Engineer toward establishment of commercial space operations, can be adapted to the identification, evaluation, and selection of optimum application of artificial intelligence for space station automation -- restoring wholeness to a situation that is otherwise chaotic due to increasing subdivision of effort. Issues such as functional assignments for space station task, domain, and symptom modules can be resolved in a manner understood by all parties rather than just the person with assigned responsibility -- and ranked by overall significance to mission accomplishment. Ranking is based on the three basic parameters of cost, performance, and schedule. This approach has successfully integrated many diverse specialties in situations like worldwide terrorism control, coal mining safety, medical malpractice risk, grain elevator explosion prevention, offshore drilling hazards, and criminal justice resource allocation -- all of which would have otherwise been subject to "squeaky wheel" emphasis and support of decision-makers.

  4. Natural or Artificial Intelligence?

    Czech Academy of Sciences Publication Activity Database

    Havlík, Vladimír

    Plzeň: University of West Bohemia, 2013 - (Romportl, J.; Ircing, P.; Zackova, E.; Polak, M.; Schuster, R.), s. 15-27 ISBN 978-80-261-0275-5. [International Conference Beyond AI 2013. Plzeň (CZ), 12.11.2013-14.11.2013] Institutional support: RVO:67985955 Keywords : artificial intelligence * natural intelligence * artifact * natural process * intrinsic intentionality Subject RIV: AA - Philosophy ; Religion

  5. Artificial intelligence in nanotechnology

    International Nuclear Information System (INIS)

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines. (topical review)

  6. Artificial intelligence in hematology.

    Science.gov (United States)

    Zini, Gina

    2005-10-01

    Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems. PMID:16203606

  7. Readings in artificial intelligence and software engineering

    CERN Document Server

    Rich, Charles

    1986-01-01

    Readings in Artificial Intelligence and Software Engineering covers the main techniques and application of artificial intelligence and software engineering. The ultimate goal of artificial intelligence applied to software engineering is automatic programming. Automatic programming would allow a user to simply say what is wanted and have a program produced completely automatically. This book is organized into 11 parts encompassing 34 chapters that specifically tackle the topics of deductive synthesis, program transformations, program verification, and programming tutors. The opening parts p

  8. Swarm intelligence of artificial bees applied to In-Core Fuel Management Optimization

    International Nuclear Information System (INIS)

    Research highlights: → We present Artificial Bee Colony with Random Keys (ABCRK) for In-Core Fuel Management Optimization. → Its performance is examined through the optimization of a Brazilian '2-loop' PWR. → Feasibility of using ABCRK is shown against some well known population-based algorithms. → Additional advantage includes the utilization of fewer control parameters. - Abstract: Artificial Bee Colony (ABC) algorithm is a relatively new member of swarm intelligence. ABC tries to simulate the intelligent behavior of real honey bees in food foraging and can be used for solving continuous optimization and multi-dimensional numeric problems. This paper introduces the Artificial Bee Colony with Random Keys (ABCRK), a modified ABC algorithm for solving combinatorial problems such as the In-Core Fuel Management Optimization (ICFMO). The ICFMO is a hard combinatorial optimization problem in Nuclear Engineering which during many years has been solved by expert knowledge. It aims at getting the best arrangement of fuel in the nuclear reactor core that leads to a maximization of the operating time. As a consequence, the operation cost decreases and money is saved. In this study, ABCRK is used for optimizing the ICFMO problem of a Brazilian '2-loop' Pressurized Water Reactor (PWR) Nuclear Power Plant (NPP) and the results obtained with the proposed algorithm are compared with those obtained by Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The results show that the performance of the ABCRK algorithm is better than or similar to that of other population-based algorithms, with the advantage of employing fewer control parameters.

  9. Swarm intelligence of artificial bees applied to In-Core Fuel Management Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Santos de Oliveira, Iona Maghali, E-mail: ioliveira@con.ufrj.br [Nuclear Engineering Program, Federal University of Rio de Janeiro, P.O. Box 68509, Zip Code 21945-970, Rio de Janeiro, RJ (Brazil); Schirru, Roberto, E-mail: schirru@lmp.ufrj.br [Nuclear Engineering Program, Federal University of Rio de Janeiro, P.O. Box 68509, Zip Code 21945-970, Rio de Janeiro, RJ (Brazil)

    2011-05-15

    Research highlights: > We present Artificial Bee Colony with Random Keys (ABCRK) for In-Core Fuel Management Optimization. > Its performance is examined through the optimization of a Brazilian '2-loop' PWR. > Feasibility of using ABCRK is shown against some well known population-based algorithms. > Additional advantage includes the utilization of fewer control parameters. - Abstract: Artificial Bee Colony (ABC) algorithm is a relatively new member of swarm intelligence. ABC tries to simulate the intelligent behavior of real honey bees in food foraging and can be used for solving continuous optimization and multi-dimensional numeric problems. This paper introduces the Artificial Bee Colony with Random Keys (ABCRK), a modified ABC algorithm for solving combinatorial problems such as the In-Core Fuel Management Optimization (ICFMO). The ICFMO is a hard combinatorial optimization problem in Nuclear Engineering which during many years has been solved by expert knowledge. It aims at getting the best arrangement of fuel in the nuclear reactor core that leads to a maximization of the operating time. As a consequence, the operation cost decreases and money is saved. In this study, ABCRK is used for optimizing the ICFMO problem of a Brazilian '2-loop' Pressurized Water Reactor (PWR) Nuclear Power Plant (NPP) and the results obtained with the proposed algorithm are compared with those obtained by Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The results show that the performance of the ABCRK algorithm is better than or similar to that of other population-based algorithms, with the advantage of employing fewer control parameters.

  10. Web Intelligence and Artificial Intelligence in Education

    Science.gov (United States)

    Devedzic, Vladan

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

  11. Artificial intelligence within AFSC

    Science.gov (United States)

    Gersh, Mark A.

    1990-01-01

    Information on artificial intelligence research in the Air Force Systems Command is given in viewgraph form. Specific research that is being conducted at the Rome Air Development Center, the Space Technology Center, the Human Resources Laboratory, the Armstrong Aerospace Medical Research Laboratory, the Armamant Laboratory, and the Wright Research and Development Center is noted.

  12. Artificial Intelligence and CALL.

    Science.gov (United States)

    Underwood, John H.

    The potential application of artificial intelligence (AI) to computer-assisted language learning (CALL) is explored. Two areas of AI that hold particular interest to those who deal with language meaning--knowledge representation and expert systems, and natural-language processing--are described and examples of each are presented. AI contribution…

  13. Artificial Intelligence and Information Retrieval.

    Science.gov (United States)

    Teodorescu, Ioana

    1987-01-01

    Compares artificial intelligence and information retrieval paradigms for natural language understanding, reviews progress to date, and outlines the applicability of artificial intelligence to question answering systems. A list of principal artificial intelligence software for database front end systems is appended. (CLB)

  14. Artificial intelligence applied to atomistic kinetic Monte Carlo simulations in Fe-Cu alloys

    International Nuclear Information System (INIS)

    Vacancy migration energies as functions of the local atomic configuration (LAC) in Fe-Cu alloys have been systematically tabulated using an appropriate interatomic potential for the alloy of interest. Subsets of these tabulations have been used to train an artificial neural network (ANN) to predict all vacancy migration energies depending on the LAC. The error in the prediction of the ANN has been evaluated by a fuzzy logic system (FLS), allowing a feedback to be introduced for further training, to improve the ANN prediction. This artificial intelligence (AI) system is used to develop a novel approach to atomistic kinetic Monte Carlo (AKMC) simulations, aimed at providing a better description of the kinetic path followed by the system through diffusion of solute atoms in the alloy via vacancy mechanism. Fe-Cu has been chosen because of the importance of Cu precipitation in Fe in connection with the embrittlement of reactor pressure vessels of existing nuclear power plants. In this paper the method is described in some detail and the first results of its application are presented and briefly discussed

  15. Integrating artificial intelligence into organizational intelligence

    OpenAIRE

    Florin LEON; Atanasiu, Gabriela M.

    2008-01-01

    Organizational intelligence is the capability of an organization to create knowledge and to use it in order to strategically adapt to its environment. Intelligence of an organization is more than the aggregated intelligence of its members – it is an emergent property of the complex interactions of its subsystems and the way they are aggregated. Processes analyse related to organizational intelligence can be achieved by means of agent-based simulations. Distributed artificial intelligence addr...

  16. Impacts of Artificial Intelligence

    OpenAIRE

    Trappl, R.

    1986-01-01

    This book, which is intended to serve as the first stage in an iterative process of detecting, predicting, and assessing the impacts of Artificial Intelligence opens with a short "one-hour course" in AI, which is intended to provide a nontechnical informative introduction to the material which follows. Next comes an overview chapter which is based on an extensive literature search, the position papers, and discussions. The next section of the book contains position papers whose richness...

  17. Artificial Intelligence in Transition

    OpenAIRE

    Hart, Peter E.

    1984-01-01

    In the past fifteen years artificial intelligence has changed from being the preoccupation of a handful of scientists to a thriving enterprise that has captured the imagination of world leaders and ordinary citizens alike. While corporate and government officials organize new projects whose potential impact is widespread, to date few people have been more affected by the transition than those already in the field. I review here some aspects of this transition, and pose some issues that it rai...

  18. Intelligence, Artificial and Otherwise

    OpenAIRE

    Chace, William M.

    1984-01-01

    I rise now to speak with the assumption that all of you know very well what I am going to say. I am the humanist here, the professor of English. We humanists, when asked to speak on questions of science and technology, are notorious for offering an embarrassed and ignorant respect toward those matters, a respect, however, which can all too quickly degenerate into insolent condescension. Face to face with the reality of computer technology, say, or with "artificial intelligence," we humanists ...

  19. Economic modeling using artificial intelligence methods

    CERN Document Server

    Marwala, Tshilidzi

    2013-01-01

    This book examines the application of artificial intelligence methods to model economic data. It addresses causality and proposes new frameworks for dealing with this issue. It also applies evolutionary computing to model evolving economic environments.

  20. Artificial intelligence applied to fuel management in BWR type reactors; Inteligencia artificial aplicada a la administracion de combustible en reactores BWR

    Energy Technology Data Exchange (ETDEWEB)

    Ortiz S, J.J

    1998-10-01

    In this work two techniques of artificial intelligence, neural networks and genetic algorithms were applied to a practical problem of nuclear fuel management; the determination of the optimal fuel reload for a BWR type reactor. This is an important problem in the design of the operation cycle of the reactor. As a result of the application of these techniques, comparable or even better reloads proposals than those given by expert companies in the subject were obtained. Additionally, two other simpler problems in reactor physics were solved: the determination of the axial power profile and the prediction of the value of some variables of interest at the end of the operation cycle of the reactor. Neural networks and genetic algorithms have been applied to solve many problems of engineering because of their versatility but they have been rarely used in the area of fuel management. The results obtained in this thesis indicates the convenience of undertaking further work on this area and suggest the application of these techniques of artificial intelligence to the solution of other problems in nuclear reactor physics. (Author)

  1. Uncertainty in artificial intelligence

    CERN Document Server

    Kanal, LN

    1986-01-01

    How to deal with uncertainty is a subject of much controversy in Artificial Intelligence. This volume brings together a wide range of perspectives on uncertainty, many of the contributors being the principal proponents in the controversy.Some of the notable issues which emerge from these papers revolve around an interval-based calculus of uncertainty, the Dempster-Shafer Theory, and probability as the best numeric model for uncertainty. There remain strong dissenting opinions not only about probability but even about the utility of any numeric method in this context.

  2. Artificial intelligence applied to the automatic analysis of absorption spectra. Objective measurement of the fine structure constant

    CERN Document Server

    Bainbridge, Matthew B

    2016-01-01

    A new and fully-automated method is presented for the analysis of high-resolution absorption spectra (GVPFIT). The method has broad application but here we apply it specifically to the problem of measuring the fine structure constant at high redshift. For this we need objectivity and reproducibility. GVPFIT is also motivated by the importance of obtaining a large statistical sample of measurements of $\\Delta\\alpha/\\alpha$. Interactive analyses are both time consuming and complex and automation makes obtaining a large sample feasible. Three numerical methods are unified into one artificial intelligence process: a genetic algorithm that emulates the Darwinian processes of reproduction, mutation and selection, non-linear least-squares with parameter constraints (VPFIT), and Bayesian model averaging. In contrast to previous methodologies, which relied on a particular solution as being the most likely model, GVPFIT plus Bayesian model averaging derives results from a large set of models, and helps overcome systema...

  3. A Primer on Artificial Intelligence.

    Science.gov (United States)

    Leal, Ralph A.

    A survey of literature on recent advances in the field of artificial intelligence provides a comprehensive introduction to this field for the non-technical reader. Important areas covered are: (1) definitions, (2) the brain and thinking, (3) heuristic search, and (4) programing languages used in the research of artificial intelligence. Some…

  4. The handbook of artificial intelligence

    CERN Document Server

    Barr, Avron

    1982-01-01

    The Handbook of Artificial Intelligence, Volume II focuses on the improvements in artificial intelligence (AI) and its increasing applications, including programming languages, intelligent CAI systems, and the employment of AI in medicine, science, and education. The book first elaborates on programming languages for AI research and applications-oriented AI research. Discussions cover scientific applications, teiresias, applications in chemistry, dependencies and assumptions, AI programming-language features, and LISP. The manuscript then examines applications-oriented AI research in medicine

  5. Artificial intelligence techniques for rational decision making

    CERN Document Server

    Marwala, Tshilidzi

    2014-01-01

    Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon's bounded rationality theory are flexible due to advanced signal processing techniques, Moore's Law and artificial intellig

  6. Artificial intelligence methods applied in the controlled synthesis of polydimethilsiloxane - poly (methacrylic acid) copolymer networks with imposed properties

    Science.gov (United States)

    Rusu, Teodora; Gogan, Oana Marilena

    2016-05-01

    This paper describes the use of artificial intelligence method in copolymer networks design. In the present study, we pursue a hybrid algorithm composed from two research themes in the genetic design framework: a Kohonen neural network (KNN), path (forward problem) combined with a genetic algorithm path (backward problem). The Tabu Search Method is used to improve the performance of the genetic algorithm path.

  7. Development of a diagnostic expert system for eddy current data analysis using applied artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Upadhyaya, B.R.; Yan, W. [Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering; Behravesh, M.M. [Electric Power Research Institute, Palo Alto, CA (United States); Henry, G. [EPRI NDE Center, Charlotte, NC (United States)

    1999-09-01

    A diagnostic expert system that integrates database management methods, artificial neural networks, and decision-making using fuzzy logic has been developed for the automation of steam generator eddy current test (ECT) data analysis. The new system, known as EDDYAI, considers the following key issues: (1) digital eddy current test data calibration, compression, and representation; (2) development of robust neural networks with low probability of misclassification for flaw depth estimation; (3) flaw detection using fuzzy logic; (4) development of an expert system for database management, compilation of a trained neural network library, and a decision module; and (5) evaluation of the integrated approach using eddy current data. The implementation to field test data includes the selection of proper feature vectors for ECT data analysis, development of a methodology for large eddy current database management, artificial neural networks for flaw depth estimation, and a fuzzy logic decision algorithm for flaw detection. A large eddy current inspection database from the Electric Power Research Institute NDE Center is being utilized in this research towards the development of an expert system for steam generator tube diagnosis. The integration of ECT data pre-processing as part of the data management, fuzzy logic flaw detection technique, and tube defect parameter estimation using artificial neural networks are the fundamental contributions of this research. (orig.)

  8. Development of a diagnostic expert system for eddy current data analysis using applied artificial intelligence methods

    International Nuclear Information System (INIS)

    A diagnostic expert system that integrates database management methods, artificial neural networks, and decision-making using fuzzy logic has been developed for the automation of steam generator eddy current test (ECT) data analysis. The new system, known as EDDYAI, considers the following key issues: (1) digital eddy current test data calibration, compression, and representation; (2) development of robust neural networks with low probability of misclassification for flaw depth estimation; (3) flaw detection using fuzzy logic; (4) development of an expert system for database management, compilation of a trained neural network library, and a decision module; and (5) evaluation of the integrated approach using eddy current data. The implementation to field test data includes the selection of proper feature vectors for ECT data analysis, development of a methodology for large eddy current database management, artificial neural networks for flaw depth estimation, and a fuzzy logic decision algorithm for flaw detection. A large eddy current inspection database from the Electric Power Research Institute NDE Center is being utilized in this research towards the development of an expert system for steam generator tube diagnosis. The integration of ECT data pre-processing as part of the data management, fuzzy logic flaw detection technique, and tube defect parameter estimation using artificial neural networks are the fundamental contributions of this research. (orig.)

  9. Applying artificial intelligence to astronomical databases - A survey of applicable technology

    Science.gov (United States)

    Rosenthal, Donald A.

    1988-01-01

    AI technologies which are relevant to astronomical data bases are reviewed, including intelligent interfaces, internal representations, and data analysis. The natural language query system developed for the Hubble Space Telescope and the technique of goal directed queries are considered. Two technologies which might lead to the development of pictorial interfaces are presented: one based on Bayesian probabilities, the other on associative memories. The development of a data analysis system which can discover classes of data within a data base without any information other than the data itself is examined. A prototype data analysis assistant to automatically develop and implement plans for data reduction is described.

  10. Artificial intelligence applied to assigned merchandise location in retail sales systems

    Directory of Open Access Journals (Sweden)

    Cruz-Domínguez, O.

    2016-05-01

    Full Text Available This paper presents an option for improving the process of assigning storage locations for merchandise in a warehouse. A disadvantage of policies in the literature is that the merchandise is assigned allocation only according to the volume of sales and the rotation it presents. However, in some cases it is necessary to deal with other aspects such as family group membership, the physical characteristics of the products, and their sales pattern to design an integral policy. This paper presents an alternative to the afore- mentioned process using Flexsim®, artificial neural networks, and genetic algorithms.

  11. Artificial Intelligence in Canada: A Review

    OpenAIRE

    Mccalla, Gordon; Cercone, Nick

    1984-01-01

    Canadians have made many contributions to artificial intelligence over the years. This article presents a summary of current research in artificial intelligence in Canada and acquaints readers with the Canadian organization for artificial intelligence -- the Canadian Society for the Computational Studies of Intelligence / Societe Canadienne pour l' Etude de l'Intelligence par Ordinateur (CSCSI/ SCEIO).

  12. Medical applications of artificial intelligence

    CERN Document Server

    Agah, Arvin

    2013-01-01

    Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Ap

  13. Artificial intelligence and intelligent tutoring systems

    Energy Technology Data Exchange (ETDEWEB)

    Livergood, N.D.

    1989-01-01

    As a species we have evolved by increasing our mental and physical powers through the deliberate development and use of instruments that amplify our inherent capabilities. Whereas hereditarily given instincts predetermine the actions of lower animal forms, human existence begins with freedom. As humans we can choose what actions we will perform. We have invented a technology called education to prepare ourselves for life. At present, our educational structures and procedures are failing to prepare us efficiently for the demands of modern life. One of the most important new technologies, in relation to human development, is the digital computer. This dissertation proposes that artificial intelligence maintain a highly critical technological awareness. Artificial intelligence, because of its origin as a politically sponsored field of investigation, must strive for constant awareness of its place within the larger political-economic world and its possible misuse by factions intent on manipulation and control. Computerized models of the human mind could be used in developing progressively more sophisticated brainwashing systems. Intelligent tutoring systems comprise an important new technology within the field of artificial intelligence. This dissertation explores specification and design procedures, functions and issues in developing intelligent tutoring systems.

  14. Computer automation and artificial intelligence

    International Nuclear Information System (INIS)

    Rapid advances in computing, resulting from micro chip revolution has increased its application manifold particularly for computer automation. Yet the level of automation available, has limited its application to more complex and dynamic systems which require an intelligent computer control. In this paper a review of Artificial intelligence techniques used to augment automation is presented. The current sequential processing approach usually adopted in artificial intelligence has succeeded in emulating the symbolic processing part of intelligence, but the processing power required to get more elusive aspects of intelligence leads towards parallel processing. An overview of parallel processing with emphasis on transputer is also provided. A Fuzzy knowledge based controller for amination drug delivery in muscle relaxant anesthesia on transputer is described. 4 figs. (author)

  15. Artificial intelligence and process management

    International Nuclear Information System (INIS)

    Techniques derived from work in artificial intelligence over the past few decades are beginning to change the approach in applying computers to process management. To explore this new approach and gain real practical experience of its potential a programme of experimental applications was initiated by Sira in collaboration with the process industry. This programme encompassed a family of experimental applications ranging from process monitoring, through supervisory control and troubleshooting to planning and scheduling. The experience gained has led to a number of conclusions regarding the present level of maturity of the technology, the potential for further developments and the measures required to secure the levels of system integrity necessary in on-line applications to critical processes. (author)

  16. Progress and Challenge of Artificial Intelligence

    Institute of Scientific and Technical Information of China (English)

    Zhong-Zhi Shi; Nan-Ning Zheng

    2006-01-01

    Artificial Intelligence (AI) is generally considered to be a subfield of computer science, that is concerned to attempt simulation, extension and expansion of human intelligence. Artificial intelligence has enjoyed tremendous success over the last fifty years. In this paper we only focus on visual perception, granular computing, agent computing, semantic grid. Human-level intelligence is the long-term goal of artificial intelligence. We should do joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. A new cross discipline intelligence science is undergoing a rapid development. Future challenges are given in final section.

  17. Computational aerodynamics and artificial intelligence

    Science.gov (United States)

    Mehta, U. B.; Kutler, P.

    1984-01-01

    The general principles of artificial intelligence are reviewed and speculations are made concerning how knowledge based systems can accelerate the process of acquiring new knowledge in aerodynamics, how computational fluid dynamics may use expert systems, and how expert systems may speed the design and development process. In addition, the anatomy of an idealized expert system called AERODYNAMICIST is discussed. Resource requirements for using artificial intelligence in computational fluid dynamics and aerodynamics are examined. Three main conclusions are presented. First, there are two related aspects of computational aerodynamics: reasoning and calculating. Second, a substantial portion of reasoning can be achieved with artificial intelligence. It offers the opportunity of using computers as reasoning machines to set the stage for efficient calculating. Third, expert systems are likely to be new assets of institutions involved in aeronautics for various tasks of computational aerodynamics.

  18. 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.

  19. A Definition of Artificial Intelligence

    OpenAIRE

    Dobrev, Dimiter

    2012-01-01

    In this paper we offer a formal definition of Artificial Intelligence and this directly gives us an algorithm for construction of this object. Really, this algorithm is useless due to the combinatory explosion. The main innovation in our definition is that it does not include the knowledge as a part of the intelligence. So according to our definition a newly born baby also is an Intellect. Here we differs with Turing's definition which suggests that an Intellect is a person with knowledge gai...

  20. Artificial Intelligence Techniques for Steam Generator Modelling

    CERN Document Server

    Wright, Sarah

    2008-01-01

    This paper investigates the use of different Artificial Intelligence methods to predict the values of several continuous variables from a Steam Generator. The objective was to determine how the different artificial intelligence methods performed in making predictions on the given dataset. The artificial intelligence methods evaluated were Neural Networks, Support Vector Machines, and Adaptive Neuro-Fuzzy Inference Systems. The types of neural networks investigated were Multi-Layer Perceptions, and Radial Basis Function. Bayesian and committee techniques were applied to these neural networks. Each of the AI methods considered was simulated in Matlab. The results of the simulations showed that all the AI methods were capable of predicting the Steam Generator data reasonably accurately. However, the Adaptive Neuro-Fuzzy Inference system out performed the other methods in terms of accuracy and ease of implementation, while still achieving a fast execution time as well as a reasonable training time.

  1. Artificial intelligence techniques in Prolog

    CERN Document Server

    Shoham, Yoav

    1993-01-01

    Artificial Intelligence Techniques in Prolog introduces the reader to the use of well-established algorithmic techniques in the field of artificial intelligence (AI), with Prolog as the implementation language. The techniques considered cover general areas such as search, rule-based systems, and truth maintenance, as well as constraint satisfaction and uncertainty management. Specific application domains such as temporal reasoning, machine learning, and natural language are also discussed.Comprised of 10 chapters, this book begins with an overview of Prolog, paying particular attention to Prol

  2. Artificial Intelligence and Information Management

    Science.gov (United States)

    Fukumura, Teruo

    After reviewing the recent popularization of the information transmission and processing technologies, which are supported by the progress of electronics, the authors describe that by the introduction of the opto-electronics into the information technology, the possibility of applying the artificial intelligence (AI) technique to the mechanization of the information management has emerged. It is pointed out that althuogh AI deals with problems in the mental world, its basic methodology relies upon the verification by evidence, so the experiment on computers become indispensable for the study of AI. The authors also describe that as computers operate by the program, the basic intelligence which is concerned in AI is that expressed by languages. This results in the fact that the main tool of AI is the logical proof and it involves an intrinsic limitation. To answer a question “Why do you employ AI in your problem solving”, one must have ill-structured problems and intend to conduct deep studies on the thinking and the inference, and the memory and the knowledge-representation. Finally the authors discuss the application of AI technique to the information management. The possibility of the expert-system, processing of the query, and the necessity of document knowledge-base are stated.

  3. Developing Creativity: Artificial Barriers in Artificial Intelligence

    OpenAIRE

    Jennings, Kyle E.

    2010-01-01

    The greatest rhetorical challenge to developers of creative artificial intelligence systems is convincingly arguing that their software is more than just an extension of their own creativity. This paper suggests that “creative autonomy,” which exists when a system not only evaluates creations on its own, but also changes its standards without explicit direction, is a necessary condition for making this argument. Rather than requiring that the system be hermetically sealed to avoid perceptions...

  4. Event tree analysis using artificial intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Dixon, B.W.; Hinton, M.F.

    1985-01-01

    Artificial Intelligence (AI) techniques used in Expert Systems and Object Oriented Programming are discussed as they apply to Event Tree Analysis. A SeQUence IMPortance calculator, SQUIMP, is presented to demonstrate the implementation of these techniques. Benefits of using AI methods include ease of programming, efficiency of execution, and flexibility of application. The importance of an appropriate user interface is stressed. 5 figs.

  5. Artificial Intelligence Databases: A Survey and Comparison.

    Science.gov (United States)

    Stern, David

    1990-01-01

    Identifies and describes online databases containing references to materials on artificial intelligence, robotics, and expert systems, and compares them in terms of scope and usage. Recommendations for conducting online searches on artificial intelligence and related fields are offered. (CLB)

  6. 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...

  7. Artificial Intelligence Assists Ultrasonic Inspection

    Science.gov (United States)

    Schaefer, Lloyd A.; Willenberg, James D.

    1992-01-01

    Subtle indications of flaws extracted from ultrasonic waveforms. Ultrasonic-inspection system uses artificial intelligence to help in identification of hidden flaws in electron-beam-welded castings. System involves application of flaw-classification logic to analysis of ultrasonic waveforms.

  8. Impact of Artificial Intelligence on Economic Theory

    OpenAIRE

    Tshilidzi Marwala

    2015-01-01

    Artificial intelligence has impacted many aspects of human life. This paper studies the impact of artificial intelligence on economic theory. In particular we study the impact of artificial intelligence on the theory of bounded rationality, efficient market hypothesis and prospect theory.

  9. How to Improve Artificial Intelligence through Web

    OpenAIRE

    Adrian LUPASC

    2005-01-01

    Intelligent agents, intelligent software applications and artificial intelligent applications from artificial intelligence service providers may make their way onto the Web in greater number as adaptive software, dynamic programming languages and Learning Algorithms are introduced into Web Services. The evolution of Web architecture may allow intelligent applications to run directly on the Web by introducing XML, RDF and logic layer. The Intelligent Wireless Web’s significant potential for ra...

  10. Uncertainty in artificial intelligence

    CERN Document Server

    Levitt, TS; Lemmer, JF; Shachter, RD

    1990-01-01

    Clearly illustrated in this volume is the current relationship between Uncertainty and AI.It has been said that research in AI revolves around five basic questions asked relative to some particular domain: What knowledge is required? How can this knowledge be acquired? How can it be represented in a system? How should this knowledge be manipulated in order to provide intelligent behavior? How can the behavior be explained? In this volume, all of these questions are addressed. From the perspective of the relationship of uncertainty to the basic questions of AI, the book divides naturally i

  11. Psychological Studies and Artificial Intelligence

    OpenAIRE

    Ringle, Martin

    1983-01-01

    This paper argues for the position that experimental human studies are relevant to most facets of AI research and that closer ties between AI and experimental psychology will enhance the development of booth the principles of artificial intelligence and their implementation in computers. Raising psychological assumptions from the level of ad hoc intuitions to the level of systematic empirical observation, in the long run, will improve the quality of AI research and help to integrate it with r...

  12. Automated Scheduling Via Artificial Intelligence

    Science.gov (United States)

    Biefeld, Eric W.; Cooper, Lynne P.

    1991-01-01

    Artificial-intelligence software that automates scheduling developed in Operations Mission Planner (OMP) research project. Software used in both generation of new schedules and modification of existing schedules in view of changes in tasks and/or available resources. Approach based on iterative refinement. Although project focused upon scheduling of operations of scientific instruments and other equipment aboard spacecraft, also applicable to such terrestrial problems as scheduling production in factory.

  13. Educational Advances in Artificial Intelligence

    OpenAIRE

    Brown, Laura E.; Michigan Technological University; Kauchak, David; University of California, San Diego

    2013-01-01

    The emergence of massive open online courses has initiated a broad national-wide discussion on higher education practices, models, and pedagogy.  Artificial intelligence and machine learning courses were at the forefront of this trend and are also being used to serve personalized, managed content in the back-end systems. Massive open online courses are just one example of the sorts of pedagogical innovations being developed to better teach AI. This column will discuss and share innovative ed...

  14. Introducing artificial intelligence into structural optimization programs

    International Nuclear Information System (INIS)

    Artificial Intelligence /AI/ is defined as the branch of the computer science concerned with the study of the ideas that enable computers to be intelligent. The main purpose of the application of AI in engineering is to develop computer programs which function better as tools for engineers and designers. Many computer programs today have properties which make them inconvenient to their final users and the research carried within the field of AI provides tools and techniques so that these restriction can be removed. The continuous progress in computer technology has lead to developing efficient computer systems which can be applied to more than simple solving sets of equations. (orig.)

  15. Readings in artificial intelligence and software engineering

    Energy Technology Data Exchange (ETDEWEB)

    Rich, C.; Waters, R.C.

    1986-01-01

    Research at the intersection of artificial intelligence and software engineering is important to both AI researchers and software engineers. For AI, programming is a domain that stimulates research in knowledge representation and automated reasoning. In software engineering, AI techniques are being applied to a new generation of programming tools. This book covers a wide spectrum of work in this area. Some of the topics covered include deductive synthesis, program verification, and transformational approaches.

  16. Artificial Intelligence, Knowledge Extraction and the Study of Human Intelligence.

    Science.gov (United States)

    d'Ydewalle, Gery; Delhaye, Patrick

    1988-01-01

    Describes artificial intelligence (AI) as the study of intelligence with the ideas and methods of computation. States that the goal is to make computers more intelligent and thereby uncover the principles that make intelligent behavior possible. Discusses knowledge representations, production (if-then) systems, and expert systems as forms of AI.…

  17. Uncertainty in artificial intelligence

    CERN Document Server

    Shachter, RD; Henrion, M; Lemmer, JF

    1990-01-01

    This volume, like its predecessors, reflects the cutting edge of research on the automation of reasoning under uncertainty.A more pragmatic emphasis is evident, for although some papers address fundamental issues, the majority address practical issues. Topics include the relations between alternative formalisms (including possibilistic reasoning), Dempster-Shafer belief functions, non-monotonic reasoning, Bayesian and decision theoretic schemes, and new inference techniques for belief nets. New techniques are applied to important problems in medicine, vision, robotics, and natural language und

  18. Artificial symbols and the essence of intelligent computing

    Science.gov (United States)

    Magnus, Amy L.; Oxley, Mark E.

    2003-08-01

    A challenge for intelligent computing is translating the skills of innovation into mathematical theory and persistent learning algorithms. Computational intelligence differs from artificial intelligence in that artificial intelligence reasons over symbols while computational intelligence reasons over sub-symbolic data and information. Natural symbos arise from shared human experiences. The creative quality of human interaction suggests symbol generation involves a collection of cooperative agents capable of representing relative experience, negotiating innovation, and---finally---building consensus. As hybrids of sub-symbolic and symbolic reasoning become the norm, it is necessary to formalize the design and evaluation of artificial symbols. In this paper, we delineate the difference between sub-symbolic patterns and symbolic experience. Further, we propose fundamental theory supporting the autonomous construction of artificial symbols which---we assert---is the ultimate culmination of an intelligent computation. We apply this theory to model selection among neural networks.

  19. Epistemology and artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Pratt, I.E.

    1987-01-01

    This study examines the concept of epistemic justification, with particular reference to establishing conditions under which this concept can be applied to computer reasoning systems: what is it, we ask, to say of a computer that it has arrived at an unjustified conclusion-that it has reasoned as it (rationally) ought not to have reasoned. This problem is important because of its relevance to the relations between the two conceptual schemes of mind, thought, and reasoning on the one hand, and of computers, programs, and computation on the other. The main findings are: (i) Certain epistemological concepts find natural application to some types of computer-reasoning systems. (ii) Such reasoning systems will themselves require these concepts to articulate the principles of reasoning they accept. (iii) Judgments involving the concept of epistemic justification can be explained in terms of the concepts thus identified. The present account of justification has a noncognitivist flavor: A theory is given of what it is to have certain beliefs involving the concept of epistemic justification by saying how such beliefs function; we remain silent as to what, if anything, those beliefs are about.

  20. Of Artificial Intelligence and Legal Reasoning

    OpenAIRE

    Sunstein, Cass Robert

    2014-01-01

    Can computers, or artificial intelligence, reason by analogy? This essay urges that they cannot, because they are unable to engage in the crucial task of identifying the normative principle that links or separates cases. Current claims, about the ability of artificial intelligence to reason analogically, rest on an inadequate picture of what legal reasoning actually is. For the most part, artificial intelligence now operates as a kind of advanced version of LEXIS, offering research assistance...

  1. Artificial intelligence in nuclear power plants

    International Nuclear Information System (INIS)

    The IAEA Specialists' Meeting on Artificial Intelligence in Nuclear Power Plants was arranged in Helsink/Vantaa, Finland, on October 10-12, 1989, under auspices of the International Working Group of Nuclear Power Plant Control and Instrumentation of the International Atomic Energy Agency (IAEA/IWG NPPCI). Technical Research Centre of Finland together with Imatran Voima Oy and Teollisuuden Voima Oy answered for the practical arrangements of the meeting. 105 participants from 17 countries and 2 international organizations took part in the meeting and 58 papers were submitted for presentation. These papers gave a comprehensive picture of the recent status and further trends in applying the rapidly developing techniques of artificial intelligence and expert systems to improve the quality and safety in designing and using of nuclear power worldwide

  2. Innovative applications of artificial intelligence

    Science.gov (United States)

    Schorr, Herbert; Rappaport, Alain

    Papers concerning applications of artificial intelligence are presented, covering applications in aerospace technology, banking and finance, biotechnology, emergency services, law, media planning, music, the military, operations management, personnel management, retail packaging, and manufacturing assembly and design. Specific topics include Space Shuttle telemetry monitoring, an intelligent training system for Space Shuttle flight controllers, an expert system for the diagnostics of manufacturing equipment, a logistics management system, a cooling systems design assistant, and a knowledge-based integrated circuit design critic. Additional topics include a hydraulic circuit design assistant, the use of a connector assembly specification expert system to harness detailed assembly process knowledge, a mixed initiative approach to airlift planning, naval battle management decision aids, an inventory simulation tool, a peptide synthesis expert system, and a system for planning the discharging and loading of container ships.

  3. Epistasis analysis using artificial intelligence.

    Science.gov (United States)

    Moore, Jason H; Hill, Doug P

    2015-01-01

    Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of expert knowledge as a guide. The methodology presented here is based on computational evolution, which is a type of genetic programming. The ability to generate interesting solutions while at the same time learning how to solve the problem at hand distinguishes computational evolution from other genetic programming approaches. We provide a general overview of this approach and then present a few examples of its application to real data. PMID:25403541

  4. Artificial intelligence methods for diagnostic

    International Nuclear Information System (INIS)

    To assist in diagnosis of its nuclear power plants, the Research and Development Division of Electricite de France has been developing skills in Artificial Intelligence for about a decade. Different diagnostic expert systems have been designed. Among them, SILEX for control rods cabinet troubleshooting, DIVA for turbine generator diagnosis, DIAPO for reactor coolant pump diagnosis. This know how in expert knowledge modeling and acquisition is direct result of experience gained during developments and of a more general reflection on knowledge based system development. We have been able to reuse this results for other developments such as a guide for auxiliary rotating machines diagnosis. (authors)

  5. Logical Foundations Of Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2010-04-01

    Full Text Available The procedures of searching solutions to problems, in Artificial Intelligence, can be brought about, in many occasions, without knowledge of the Domain, and in other situations, with knowledge of it. This last procedure is usually called Heuristic Search. In such methods the matrix techniques reveal themselves as essential. Their introduction can give us an easy and precise way in the search of solution. Our paper explains how the matrix theory appears and fruitfully participates in A I, with feasible applications to Game Theory.

  6. Artificial intelligence a beginner's guide

    CERN Document Server

    Whitby, Blay

    2012-01-01

    Tomorrow begins right here as we embark on an enthralling and jargon-free journey into the world of computers and the inner recesses of the human mind. Readers encounter everything from the nanotechnology used to make insect-like robots, to computers that perform surgery, in addition to discovering the biggest controversies to dog the field of AI. Blay Whitby is a Lecturer on Cognitive Science and Artificial Intelligence at the University of Sussex UK. He is the author of two books and numerous papers.

  7. Advanced Artificial Intelligence Technology Testbed

    Science.gov (United States)

    Anken, Craig S.

    1993-01-01

    The Advanced Artificial Intelligence Technology Testbed (AAITT) is a laboratory testbed for the design, analysis, integration, evaluation, and exercising of large-scale, complex, software systems, composed of both knowledge-based and conventional components. The AAITT assists its users in the following ways: configuring various problem-solving application suites; observing and measuring the behavior of these applications and the interactions between their constituent modules; gathering and analyzing statistics about the occurrence of key events; and flexibly and quickly altering the interaction of modules within the applications for further study.

  8. Improving designer productivity. [artificial intelligence

    Science.gov (United States)

    Hill, Gary C.

    1992-01-01

    Designer and design team productivity improves with skill, experience, and the tools available. The design process involves numerous trials and errors, analyses, refinements, and addition of details. Computerized tools have greatly speeded the analysis, and now new theories and methods, emerging under the label Artificial Intelligence (AI), are being used to automate skill and experience. These tools improve designer productivity by capturing experience, emulating recognized skillful designers, and making the essence of complex programs easier to grasp. This paper outlines the aircraft design process in today's technology and business climate, presenting some of the challenges ahead and some of the promising AI methods for meeting these challenges.

  9. Economic reasoning and artificial intelligence.

    Science.gov (United States)

    Parkes, David C; Wellman, Michael P

    2015-07-17

    The field of artificial intelligence (AI) strives to build rational agents capable of perceiving the world around them and taking actions to advance specified goals. Put another way, AI researchers aim to construct a synthetic homo economicus, the mythical perfectly rational agent of neoclassical economics. We review progress toward creating this new species of machine, machina economicus, and discuss some challenges in designing AIs that can reason effectively in economic contexts. Supposing that AI succeeds in this quest, or at least comes close enough that it is useful to think about AIs in rationalistic terms, we ask how to design the rules of interaction in multi-agent systems that come to represent an economy of AIs. Theories of normative design from economics may prove more relevant for artificial agents than human agents, with AIs that better respect idealized assumptions of rationality than people, interacting through novel rules and incentive systems quite distinct from those tailored for people. PMID:26185245

  10. DEALING MEDICAL DATA WITH FUNDAMENTALS OF NEW ARTIFICIAL INTELLIGENCE

    OpenAIRE

    ALI SAKR,; DIANA MOSA

    2010-01-01

    This work applies rough sets and artificial intelligent to analyze and reduce medical data without affecting the information to construct an expert system. The ROSETTA software is applied for analyzing some medical data and deducing rules. This paper discusses fundamentals of Rough Set Theory (RST); uses this theorem to extract decision rules for medical data and drive results by Artificial Neural Network (ANN).

  11. Applying Computational Intelligence

    CERN Document Server

    Kordon, Arthur

    2010-01-01

    Offers guidelines on creating value from the application of computational intelligence methods. This work introduces a methodology for effective real-world application of computational intelligence while minimizing development cost, and outlines the critical, underestimated technology marketing efforts required

  12. Contribution of artificial intelligence to operation

    International Nuclear Information System (INIS)

    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

  13. APPLICATION OF ARTIFICIAL INTELLIGENCE IN MECHATRONIC SYSTEMS

    Directory of Open Access Journals (Sweden)

    A.P. Sobchak

    2013-06-01

    Full Text Available This article discusses the main issues of artificial intelligence and its implementation in daily life in the form of control systems for mechatronic systems. Due to intensive application of the latest scientific and technological achievements and a new element base, there spring up new technologies of artificial intelligence creation principles and laws realization, examples of which given in the article

  14. A Study on Artificial Intelligence IQ and Standard Intelligent Model

    OpenAIRE

    Liu, Feng; Shi, Yong

    2015-01-01

    Currently, potential threats of artificial intelligence (AI) to human have triggered a large controversy in society, behind which, the nature of the issue is whether the artificial intelligence (AI) system can be evaluated quantitatively. This article analyzes and evaluates the challenges that the AI development level is facing, and proposes that the evaluation methods for the human intelligence test and the AI system are not uniform; and the key reason for which is that none of the models ca...

  15. A DISTRIBUTED SMART HOME ARTIFICIAL INTELLIGENCE SYSTEM

    DEFF Research Database (Denmark)

    Lynggaard, Per

    2013-01-01

    A majority of the research performed today explore artificial intelligence in smart homes by using a centralized approach where a smart home server performs the necessary calculations. This approach has some disadvantages that can be overcome by shifting focus to a distributed approach where...... the artificial intelligence system is implemented as distributed as agents running parts of the artificial intelligence system. This paper presents a distributed smart home architecture that distributes artificial intelligence in smart homes and discusses the pros and cons of such a concept. The presented...... distributed model is a layered model. Each layer offers a different complexity level of the embedded distributed artificial intelligence. At the lowest layer smart objects exists, they are small cheap embedded microcontroller based smart devices that are powered by batteries. The next layer contains a more...

  16. Artificial Intelligence Research and Development: Proc. of the 11th International Conference of the Catalan Association for Artificial Intelligence

    OpenAIRE

    Alsinet, Teresa; Puyol-Gruart, Josep; Torras, Carme

    2008-01-01

    Artificial Intelligence Research and Development. Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence. Volume 184 Frontiers in Artificial Intelligence and Applications Peer Reviewed

  17. Interaction between Software Engineering and Artificial Intelligence- A Review

    OpenAIRE

    Prince Jain

    2011-01-01

    Software engineering and artificial intelligence is the two field of the computer science. During the last decades, the disciplines of Artificial Intelligence and Software Engineering have developedseparately without the much exchange of research outcomes. However, both fields of computer science have different characteristics, benefits and limitations. This statement opens many possibilities and ideas for research. One idea is that the researcher applies the available methods, tools and tech...

  18. Text Classification using Artificial Intelligence

    CERN Document Server

    Kamruzzaman, S M

    2010-01-01

    Text classification is the process of classifying documents into predefined categories based on their content. It is the automated assignment of natural language texts to predefined categories. Text classification is the primary requirement of text retrieval systems, which retrieve texts in response to a user query, and text understanding systems, which transform text in some way such as producing summaries, answering questions or extracting data. Existing supervised learning algorithms for classifying text need sufficient documents to learn accurately. This paper presents a new algorithm for text classification using artificial intelligence technique that requires fewer documents for training. Instead of using words, word relation i.e. association rules from these words is used to derive feature set from pre-classified text documents. The concept of na\\"ive Bayes classifier is then used on derived features and finally only a single concept of genetic algorithm has been added for final classification. A syste...

  19. Applying Multiple Intelligences

    Science.gov (United States)

    Christodoulou, Joanna A.

    2009-01-01

    The ideas of multiple intelligences introduced by Howard Gardner of Harvard University more than 25 years ago have taken form in many ways, both in schools and in other sometimes-surprising settings. The silver anniversary of Gardner's learning theory provides an opportunity to reflect on the ways multiple intelligences theory has taken form and…

  20. Use of artificial intelligence in nuclear power plants

    International Nuclear Information System (INIS)

    The application of artificial intelligence, in the form of expert systems and neural networks, to the control room activities in a nuclear power plant has the potential to reduce operator error and increase plant safety, reliability, and efficiency. Furthermore, there are a large number of non-operating activities (testing, routine maintenance, outage planning, equipment diagnostics, and fuel management) in which artificial intelligence can increase the efficiency and effectiveness of overall plant and corporate operations. This paper reviews the state-of-the-art of artificial intelligence techniques, specifically, expert systems and neural networks, to nuclear power plants. This paper has reviewed the state-of-the-art of artificial intelligence, specifically expert systems and neural networks that are applied to problems in nuclear power plants

  1. Artificial intelligence in power system optimization

    CERN Document Server

    Ongsakul, Weerakorn

    2013-01-01

    With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This book covers the current level of applications of artificial intelligence to the optimization problems in power systems. This book serves as a textbook for graduate students in electric power system management and is also be useful for those who are interested in using artificial intelligence in power system optimization.

  2. Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA Southeastearn University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  3. Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA southeastern University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  4. The importance of artificial intelligence for Naval intelligence training simulations

    OpenAIRE

    Sweat, Patricia A.

    2006-01-01

    Agent technology is widely deployed in numerous commercial areas such as networking, modeling, and software; however, this technology remains under-utilized by operational organizations within the United States Navy. This thesis will investigate the importance of artificial intelligence (AI) for military training simulations, particularly in the training of intelligence personnel in the Navy. The Computer Generated Forces (CGF) of the current Intelligence Team Trainer's (ITT) system initiate ...

  5. Artificial Intelligence and Spacecraft Power Systems

    Science.gov (United States)

    Dugel-Whitehead, Norma R.

    1997-01-01

    This talk will present the work which has been done at NASA Marshall Space Flight Center involving the use of Artificial Intelligence to control the power system in a spacecraft. The presentation will include a brief history of power system automation, and some basic definitions of the types of artificial intelligence which have been investigated at MSFC for power system automation. A video tape of one of our autonomous power systems using co-operating expert systems, and advanced hardware will be presented.

  6. Artificial Intelligence for Controlling Robotic Aircraft

    Science.gov (United States)

    Krishnakumar, Kalmanje

    2005-01-01

    A document consisting mostly of lecture slides presents overviews of artificial-intelligence-based control methods now under development for application to robotic aircraft [called Unmanned Aerial Vehicles (UAVs) in the paper] and spacecraft and to the next generation of flight controllers for piloted aircraft. Following brief introductory remarks, the paper presents background information on intelligent control, including basic characteristics defining intelligent systems and intelligent control and the concept of levels of intelligent control. Next, the paper addresses several concepts in intelligent flight control. The document ends with some concluding remarks, including statements to the effect that (1) intelligent control architectures can guarantee stability of inner control loops and (2) for UAVs, intelligent control provides a robust way to accommodate an outer-loop control architecture for planning and/or related purposes.

  7. Improving Tools in Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2010-01-01

    Full Text Available The historical origin of the Artificial Intelligence (AI is usually established in the Dartmouth Conference, of 1956. But we can find many more arcane origins [1]. Also, we can consider, in more recent times, very great thinkers, as Janos Neumann (then, John von Neumann, arrived in USA, Norbert Wiener, Alan Mathison Turing, or Lofti Zadeh, for instance [12, 14]. Frequently AI requires Logic. But its Classical version shows too many insufficiencies. So, it was necessary to introduce more sophisticated tools, as Fuzzy Logic, Modal Logic, Non-Monotonic Logic and so on [1, 2]. Among the things that AI needs to represent are categories, objects, properties, relations between objects, situations, states, time, events, causes and effects, knowledge about knowledge, and so on. The problems in AI can be classified in two general types [3, 5], search problems and representation problems. On this last "peak", there exist different ways to reach their summit. So, we have [4] Logics, Rules, Frames, Associative Nets, Scripts, and so on, many times connected among them. We attempt, in this paper, a panoramic vision of the scope of application of such representation methods in AI. The two more disputable questions of both modern philosophy of mind and AI will be perhaps the Turing Test and the Chinese Room Argument. To elucidate these very difficult questions, see our final note.

  8. Developing a Reading Concentration Monitoring System by Applying an Artificial Bee Colony Algorithm to E-Books in an Intelligent Classroom

    Directory of Open Access Journals (Sweden)

    Yueh-Min Huang

    2012-10-01

    Full Text Available A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students’ reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students’ reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC optimization approach is applied to the data gathered from these sensors to help instructors understand their students’ reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students.

  9. Developing a reading concentration monitoring system by applying an artificial bee colony algorithm to e-books in an intelligent classroom.

    Science.gov (United States)

    Hsu, Chia-Cheng; Chen, Hsin-Chin; Su, Yen-Ning; Huang, Kuo-Kuang; Huang, Yueh-Min

    2012-01-01

    A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students' reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students' reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC) optimization approach is applied to the data gathered from these sensors to help instructors understand their students' reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students. PMID:23202042

  10. Subjective Reality and Strong Artificial Intelligence

    OpenAIRE

    Serov, Alexander

    2013-01-01

    The main prospective aim of modern research related to Artificial Intelligence is the creation of technical systems that implement the idea of Strong Intelligence. According our point of view the path to the development of such systems comes through the research in the field related to perceptions. Here we formulate the model of the perception of external world which may be used for the description of perceptual activity of intelligent beings. We consider a number of issues related to the dev...

  11. Marine litter prediction by artificial intelligence

    International Nuclear Information System (INIS)

    Artificial intelligence techniques of neural network and fuzzy systems were applied as alternative methods to determine beach litter grading, based on litter surveys of the Antalya coastline (the Turkish Riviera). Litter measurements were categorized and assessed by artificial intelligence techniques, which lead to a new litter categorization system. The constructed neural network satisfactorily predicted the grading of the Antalya beaches and litter categories based on the number of litter items in the general litter category. It has been concluded that, neural networks could be used for high-speed predictions of litter items and beach grading, when the characteristics of the main litter category was determined by field studies. This can save on field effort when fast and reliable estimations of litter categories are required for management or research studies of beaches--especially those concerned with health and safety, and it has economic implications. The main advantages in using fuzzy systems are that they consider linguistic adjectival definitions, e.g. many/few, etc. As a result, additional information inherent in linguistic comments/refinements and judgments made during field studies can be incorporated in grading systems

  12. Applications of artificial intelligence, including expert systems

    International Nuclear Information System (INIS)

    When Artificial Intelligence is applied to a complex physical system like a nuclear plant it is useful to distinguish between two rather distinct and different intelligent views of such a plant. The first view may be characterised as ''the designer's view''. This is the view of the plant as it was originally conceived and designed; it is essentially a once-and-for-all static view, corresponding to the implicit assumption of an ''ageless plant'', or at most a plant which ages in a preconceived, preset manner. The second view, which may be characterised as ''the operators view'', has to do more with a real-world, ageing plant. It is a more dynamic view, which sees the ageing process as one in which unforeseen, and possibly unforeseeable events may occur at equally unforeseen, and possibly unforeseeable times. The first view is predominantly a way of thinking about the plant, while the second is very often more a way of feeling about it. It should be emphasized that both ways are ways of intelligence. (author)

  13. One Decade of Universal Artificial Intelligence

    CERN Document Server

    Hutter, Marcus

    2012-01-01

    The first decade of this century has seen the nascency of the first mathematical theory of general artificial intelligence. This theory of Universal Artificial Intelligence (UAI) has made significant contributions to many theoretical, philosophical, and practical AI questions. In a series of papers culminating in book (Hutter, 2005), an exciting sound and complete mathematical model for a super intelligent agent (AIXI) has been developed and rigorously analyzed. While nowadays most AI researchers avoid discussing intelligence, the award-winning PhD thesis (Legg, 2008) provided the philosophical embedding and investigated the UAI-based universal measure of rational intelligence, which is formal, objective and non-anthropocentric. Recently, effective approximations of AIXI have been derived and experimentally investigated in JAIR paper (Veness et al. 2011). This practical breakthrough has resulted in some impressive applications, finally muting earlier critique that UAI is only a theory. For the first time, wit...

  14. Techniques of artificial intelligence applied to the electric power expansion distribution system planning problem; Tecnicas de inteligencia artificial aplicadas ao problema de planejamento da expansao do sistema de distribuicao de energia eletrica

    Energy Technology Data Exchange (ETDEWEB)

    Froes, Salete Maria

    1996-07-01

    A tool named Constrained Decision Problem (CDP), which is based on Artificial Intelligence and a specific application to Distribution System Planning is described. The CDP allows multiple objective optimization that does not, necessarily, result in a single optimal solution. First, a literature review covers published works related to Artificial Intelligence applications to Electric Power Distribution Systems, emphasizing feeder restoration and reconfiguration. Some concepts related to Artificial Intelligence are described, with particular attention to Planning and to Constrained Decision Problems. Following, an Electric Power System planning model is addressed by using the CDP tool. Some case studies illustrate the Distribution Planning model, which are compared with standard optimization models. Concluding, some comments establishing the possibilities of CDP applications are followed by a view on future developments. (author)

  15. Performance support systems and artificial intelligent considerations

    International Nuclear Information System (INIS)

    Intelligent performance support systems (PSS) for reactor operations have been discussed, but none is operating yet. The features desired are human-centred design, intelligent behaviour, and real-time performance. PSS derive their origins from the realization that intelligent open-loop complex plant control involves consideration of the human component as well as the machine part of the system. Also , for the PSS to be effective, real-time operating capability is necessary. In this context, the present paper examines the role of artificial intelligence in PSS. 22 refs., 3 figs

  16. Artificial Intelligence Research at the Artificial Intelligence Laboratory, Massachusetts Institute of Technology

    OpenAIRE

    Winston, Patrick H.

    1983-01-01

    The primary goal of the Artificial Intelligence Laboratory is to understand how computers can be made to exhibit intelligence. Two corollary goals are to make computers more useful and to understand certain aspects of human intelligence. Current research includes work on computer robotics and vision, expert systems, learning and commonsense reasoning, natural language understanding, and computer architecture.

  17. Artificial Intelligence and Robotic From the Past to Present

    OpenAIRE

    Elnaz Asgarifar; Bashir Golchin

    2013-01-01

    This paper overviews the basic principles and recent advances in the Artificial Intelligent robotics and the utilization of robots in nowadays life and the various compass. The aim of the paper is to introduce the basic concepts of artificial intelligent techniques and present a survey about robots. In first section we have a survey on the concept of artificial intelligence and intelligence life; also we introduce two important factors in artificial intelligence. In the next section, we have ...

  18. Artificial Intelligence In Computational Fluid Dynamics

    Science.gov (United States)

    Vogel, Alison Andrews

    1991-01-01

    Paper compares four first-generation artificial-intelligence (Al) software systems for computational fluid dynamics. Includes: Expert Cooling Fan Design System (EXFAN), PAN AIR Knowledge System (PAKS), grid-adaptation program MITOSIS, and Expert Zonal Grid Generation (EZGrid). Focuses on knowledge-based ("expert") software systems. Analyzes intended tasks, kinds of knowledge possessed, magnitude of effort required to codify knowledge, how quickly constructed, performances, and return on investment. On basis of comparison, concludes Al most successful when applied to well-formulated problems solved by classifying or selecting preenumerated solutions. In contrast, application of Al to poorly understood or poorly formulated problems generally results in long development time and large investment of effort, with no guarantee of success.

  19. Minimum DNBR Prediction Using Artificial Intelligence

    International Nuclear Information System (INIS)

    The minimum DNBR (MDNBR) for prevention of the boiling crisis and the fuel clad melting is very important factor that should be consistently monitored in safety aspects. Artificial intelligence methods have been extensively and successfully applied to nonlinear function approximation such as the problem in question for predicting DNBR values. In this paper, support vector regression (SVR) model and fuzzy neural network (FNN) model are developed to predict the MDNBR using a number of measured signals from the reactor coolant system. Also, two models are trained using a training data set and verified against test data set, which does not include training data. The proposed MDNBR estimation algorithms were verified by using nuclear and thermal data acquired from many numerical simulations of the Yonggwang Nuclear Power Plant Unit 3 (YGN-3)

  20. Using Artificial Intelligence Models in System Identification

    OpenAIRE

    Elshamy, Wesam

    2013-01-01

    Artificial Intelligence (AI) techniques are known for its ability in tackling problems found to be unyielding to traditional mathematical methods. A recent addition to these techniques are the Computational Intelligence (CI) techniques which, in most cases, are nature or biologically inspired techniques. Different CI techniques found their way to many control engineering applications, including system identification, and the results obtained by many researchers were encouraging. However, most...

  1. Artificial Intelligence-The Emerging Technology

    OpenAIRE

    R.P. Shenoy

    1985-01-01

    Artificial Intelligence (AI), once considered as an obscure branch of computer science, is now having a growing number of adherents in a wide variety of fields. AI is particularly useful for combat automation in defence. The combined works of computer scientists and technologists and cognitive scientists have brought out for intelligent information processing knowledge is the key factor. In the last few years, AI has been tried out with a high degree of success in certain areas such as the Ex...

  2. Application Of Artificial Intelligence To Wind Tunnels

    Science.gov (United States)

    Lo, Ching F.; Steinle, Frank W., Jr.

    1989-01-01

    Report discusses potential use of artificial-intelligence systems to manage wind-tunnel test facilities at Ames Research Center. One of goals of program to obtain experimental data of better quality and otherwise generally increase productivity of facilities. Another goal to increase efficiency and expertise of current personnel and to retain expertise of former personnel. Third goal to increase effectiveness of management through more efficient use of accumulated data. System used to improve schedules of operation and maintenance of tunnels and other equipment, assignment of personnel, distribution of electrical power, and analysis of costs and productivity. Several commercial artificial-intelligence computer programs discussed as possible candidates for use.

  3. 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

  4. Machine learning an artificial intelligence approach

    CERN Document Server

    Banerjee, R; Bradshaw, Gary; Carbonell, Jaime Guillermo; Mitchell, Tom Michael; Michalski, Ryszard Spencer

    1983-01-01

    Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs-particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV a

  5. Fundamental research in artificial intelligence at NASA

    Science.gov (United States)

    Friedland, Peter

    1990-01-01

    This paper describes basic research at NASA in the field of artificial intelligence. The work is conducted at the Ames Research Center and the Jet Propulsion Laboratory, primarily under the auspices of the NASA-wide Artificial Intelligence Program in the Office of Aeronautics, Exploration and Technology. The research is aimed at solving long-term NASA problems in missions operations, spacecraft autonomy, preservation of corporate knowledge about NASA missions and vehicles, and management/analysis of scientific and engineering data. From a scientific point of view, the research is broken into the categories of: planning and scheduling; machine learning; and design of and reasoning about large-scale physical systems.

  6. Applications of artificial intelligence technology to wastewater treatment fields in China

    Institute of Scientific and Technical Information of China (English)

    QING Xiao-xia; WANG Bo; MENG De-tao

    2005-01-01

    Current applications of artificial intelligence technology to wastewater treatment in China are summarized. Wastewater treatment plants use expert system mainly in the operation decision-making and fault diagnosis of system operation, use artificial neuron network for system modeling, water quality forecast and soft measure, and use fuzzy control technology for the intelligence control of wastewater treatment process. Finally, the main problems in applying artificial intelligence technology to wastewater treatment in China are analyzed.

  7. Some Notes About Artificial Intelligence as New Mathematical Tool

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2010-04-01

    Full Text Available Mathematics is a mere instance of First-Order Predicate Calculus. Therefore it belongs to applied Monotonic Logic. So, we found the limitations of classical logic reasoning and the clear advantages of Fuzzy Logic and many other new interesting tools. We present here some of the more usefulness tools of this new field of Mathematics so-called Artificial Intelligence.

  8. Nature inspired algorithms and artificial intelligence

    Directory of Open Access Journals (Sweden)

    Elisa Valentina Onet

    2008-05-01

    Full Text Available Artificial intelligence has been very muchinterested in studying the characteristics ofintelligent agent, mainly planning, learning,reasoning (making decisions and perception.Biological processes and methods have beeninfluencing science from many decades. Naturalsystems have many properties that inspiredapplications - self-organisation, simplicity of basicelements, dynamics, flexibility. This paper is a surveyof nature inspired algorithms, like Particle SwarmOptimization (PSO, Ant Colony Optimization (ACOand Artificial Bee Colony(ABC.

  9. Report on the 1986 Artificial Intelligence and Simulation Workshop

    OpenAIRE

    Modjeski, Richard B.

    1987-01-01

    The first Artificial Intelligence (AI) and simulation workshop was held during the National Conference on Artificial Intelligence (AAAI-86) on 11 August 1986 at Wharton Hall, the University of Pennsylvania.

  10. Abstraction in artificial intelligence and complex systems

    CERN Document Server

    Saitta, Lorenza

    2013-01-01

    Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences.  After discussing the characterizing properties of abstraction, a formal model, the K

  11. Employing Artificial Intelligence To Minimise Internet Fraud

    Directory of Open Access Journals (Sweden)

    Edward Wong Sek Khin

    2009-12-01

    Full Text Available Internet fraud is increasing on a daily basis with new methods for extracting funds from government, corporations, businesses in general, and persons appearing almost hourly. The increases in on-line purchasing and the constant vigilance of both seller and buyer have meant that the criminal seems to be one-step ahead at all times. To pre-empt or to stop fraud before it can happen occurs in the non-computer based daily transactions of today because of the natural intelligence of the players, both seller and buyer. Currently, even with advances in computing techniques, intelligence is not the current strength of any computing system of today, yet techniques are available which may reduce the occurrences of fraud, and are usually referred to as artificial intelligence systems.This paper provides an overview of the use of current artificial intelligence (AI techniques as a means of combating fraud.Initially the paper describes how artificial intelligence techniques are employed in systems for detecting credit card fraud (online and offline fraud and insider trading.Following this, an attempt is made to propose the using of MonITARS (Monitoring Insider Trading and Regulatory Surveillance Systems framework which use a combination of genetic algorithms, neural nets and statistical analysis in detecting insider dealing. Finally, the paper discusses future research agenda to the role of using MonITARS system.

  12. Nature inspired algorithms and artificial intelligence

    OpenAIRE

    Elisa Valentina Onet; Ecaterina Vladu

    2008-01-01

    Artificial intelligence has been very muchinterested in studying the characteristics ofintelligent agent, mainly planning, learning,reasoning (making decisions) and perception.Biological processes and methods have beeninfluencing science from many decades. Naturalsystems have many properties that inspiredapplications - self-organisation, simplicity of basicelements, dynamics, flexibility. This paper is a surveyof nature inspired algorithms, like Particle SwarmOptimization (PSO), Ant Colony Op...

  13. Dynamic Restructuring Of Problems In Artificial Intelligence

    Science.gov (United States)

    Schwuttke, Ursula M.

    1992-01-01

    "Dynamic tradeoff evaluation" (DTE) denotes proposed method and procedure for restructuring problem-solving strategies in artificial intelligence to satisfy need for timely responses to changing conditions. Detects situations in which optimal problem-solving strategies cannot be pursued because of real-time constraints, and effects tradeoffs among nonoptimal strategies in such way to minimize adverse effects upon performance of system.

  14. Yale Artificial Intelligence Project (Research in Progress)

    OpenAIRE

    Collins, Gregg

    1981-01-01

    The Yale Artificial Intelligence Project, under the direction of Professor Roger C. Schank, supports a number of research projects. Most of this research is in the02-02 area of attempting to model the processes involved in human understanding, with a current emphasis on memory models and the processes involved in learning.

  15. Artificial Intelligence Applications to Videodisc Technology

    OpenAIRE

    Vries, John K.; Banks, Gordon; McLinden, Sean; Moossy, John; Brown, Melanie

    1985-01-01

    Much of medical information is visual in nature. Since it is not easy to describe pictorial information in linguistic terms, it has been difficult to store and retrieve this type of information. Coupling videodisc technology with artificial intelligence programming techniques may provide a means for solving this problem.

  16. A Starter's Guide to Artificial Intelligence.

    Science.gov (United States)

    McConnell, Barry A.; McConnell, Nancy J.

    1988-01-01

    Discussion of the history and development of artificial intelligence (AI) highlights a bibliography of introductory books on various aspects of AI, including AI programing; problem solving; automated reasoning; game playing; natural language; expert systems; machine learning; robotics and vision; critics of AI; and representative software. (LRW)

  17. Algorithmic Game Theory and Artificial Intelligence

    OpenAIRE

    Elkind, Edith; Nanyang Technological University; Leyton-Brown, Kevin; University of British Columbia

    2010-01-01

    We briefly survey the rise of game theory as a topic of study in artificial intelligence, and explain the term algorithmic game theory. We then de- scribe three broad areas of current inquiry by AI researchers in algorithmic game theory: game playing, social choice, and mechanism design. Finally, we give short summaries of each of the six articles appearing in this issue.

  18. Application of Artificial Intelligence to operator assistance

    International Nuclear Information System (INIS)

    This paper describes an application of Artificial Intelligence to nuclear power plant control. An expert system is proposed in which the experience of NRC certified instructors, as represented in a knowledge base by a series of production rules, is used to recommend control sequences to the operator based on the state of the plant at the time

  19. A Characterization of the Utility of Using Artificial Intelligence to Test Two Artificial Intelligence Systems

    OpenAIRE

    Jeremy Straub; Justin Huber

    2013-01-01

    An artificial intelligence system, designed for operations in a real-world environment faces a nearly infinite set of possible performance scenarios. Designers and developers, thus, face the challenge of validating proper performance across both foreseen and unforeseen conditions, particularly when the artificial intelligence is controlling a robot that will be operating in close proximity, or may represent a danger, to humans. While the manual creation of test cases allows limited testing (p...

  20. Artificial Intelligence A New Synthesis

    CERN Document Server

    Nilsson, Nils J

    1998-01-01

    Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. The book provides a refreshing and motivating new synthesis of the field by one of AI's master expositors and leading re

  1. Applied intelligent control of induction motor drives

    CERN Document Server

    Chan, Tze Fun

    2011-01-01

    Induction motors are the most important workhorses in industry. They are mostly used as constant-speed drives when fed from a voltage source of fixed frequency. Advent of advanced power electronic converters and powerful digital signal processors, however, has made possible the development of high performance, adjustable speed AC motor drives.This book aims to explore new areas of induction motor control based on artificial intelligence (AI) techniques in order to make the controller less sensitive to parameter changes. Selected AI techniques are applied for different induction motor control s.

  2. Artificial intelligence and nuclear power. Report by the Technology Transfer Artificial Intelligence Task Team

    International Nuclear Information System (INIS)

    The Artificial Intelligence Task Team was organized to review the status of Artificial Intelligence (AI) technology, identify guidelines for AI work, and to identify work required to allow the nuclear industry to realize maximum benefit from this technology. The state of the nuclear industry was analyzed to determine where the application of AI technology could be of greatest benefit. Guidelines and criteria were established to focus on those particular problem areas where AI could provide the highest possible payoff to the industry. Information was collected from government, academic, and private organizations. Very little AI work is now being done to specifically support the nuclear industry. The AI Task Team determined that the establishment of a Strategic Automation Initiative (SAI) and the expansion of the DOE Technology Transfer program would ensure that AI technology could be used to develop software for the nuclear industry that would have substantial financial payoff to the industry. The SAI includes both long and short term phases. The short-term phase includes projects which would demonstrate that AI can be applied to the nuclear industry safely, and with substantial financial benefit. The long term phase includes projects which would develop AI technologies with specific applicability to the nuclear industry that would not be developed by people working in any other industry

  3. Artificial intelligence and information-control systems of robots - 87

    International Nuclear Information System (INIS)

    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

  4. Artificial intelligence and CAD/CAM

    Energy Technology Data Exchange (ETDEWEB)

    Iwata, K.

    1983-10-01

    In recent years CAD/CAM technology has improved industrial productivity. It is a significant step towards the design of the factory of the future. CAD/CAM in conjunction with artificial intelligence will become paramount. Workers in this field are attempting to produce systems of ever-increasing intelligence and independence for everyday use in factories, schools and elsewhere. A computer system which could understand natural language in both spoken and handwritten form and communicate in natural language would have considerable advantage in practical situations over one of the present generation of computers and computer programs. 2 references.

  5. The potential of artificial intelligence toys

    DEFF Research Database (Denmark)

    Dai, Zheng

    2008-01-01

    Artificial intelligence is moving to a next step of development and application areas. From electronic games to human-like robots, AI toy is a good choice for next step during this process. Technology-based design is fit to the development of AI toy. It can exert the advantages and explore more...... value for existing resources. It combines AI programs and common sensors to realize the function of intelligence input and output. Designers can use technology-based criteria to design and need to consider the possible issues in this new field. All of these aspects can be referenced from electronic game...

  6. Seventh Scandinavian Conference on Artificial Intelligence

    DEFF Research Database (Denmark)

    Lund, Henrik Hautop; Mayoh, Brian Henry; Perram, John

    2001-01-01

    The book covers the seventh Scandinavian Conference on Artificial Intelligence, held at the Maersk Mc-Kinney Moller Institute for Production Technology at the University of Southern Denmark during the period 20-21 February, 2001. It continues the tradition established by SCAI of being one...... of the most important regional AI conferences in Europe, attracting high quality submissions from Scandinavia and the rest of the world, including the Baltic countries. The contents include robotics, sensor/motor intelligence, evolutionary robotics, behaviour-based systems, multi-agent systems, applications...

  7. Philosophy of Logic and Artificial Intelligence

    OpenAIRE

    Karavasileiadis, Christos; O'Bryan, Stephan

    2009-01-01

    For many years, scientists have been trying to implement human intelligence in machines without being able to make a complete model of human mind. Some people connect this failure to theorems proved by Kurt Gödel in 1931 and they are called Gödel’s Incompleteness Theorems. The results of Gödel’s Incompleteness Theorem caused many philosophical debates between the “believers” of Artificial Intelligence (A.I) and those who find it impossible. The purpose of this project is to examine how Gödel’...

  8. Developing a Reading Concentration Monitoring System by Applying an Artificial Bee Colony Algorithm to E-Books in an Intelligent Classroom

    OpenAIRE

    Yueh-Min Huang; Chia-Cheng Hsu; Hsin-Chin Chen; Yen-Ning Su; Kuo-Kuang Huang

    2012-01-01

    A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students’ reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students’ reading concentration rates. The p...

  9. Interaction between Software Engineering and Artificial Intelligence- A Review

    Directory of Open Access Journals (Sweden)

    Prince Jain

    2011-12-01

    Full Text Available Software engineering and artificial intelligence is the two field of the computer science. During the last decades, the disciplines of Artificial Intelligence and Software Engineering have developedseparately without the much exchange of research outcomes. However, both fields of computer science have different characteristics, benefits and limitations. This statement opens many possibilities and ideas for research. One idea is that the researcher applies the available methods, tools and techniques of Artificial Intelligence to Software Engineering and Software Engineering to Artificial Intelligence in a manner that good things, feature, characteristic and advantages of the both fields is taken up, and the limitations will reduces. During applicability, an intersection area is found between AI and SE, which forms the relation between AI and SE. The work in this paper discusses the factor that come while communicating between AI and SE such as Communication, objective, Problem and reasons for adopting. This work explores the framework of interaction on which both fields are communicate with each other. This framework has four major classes of interaction such as software support environment, AI tools and techniques in conventional software, Use of conventional software technology and Methodological considerations. This paper introduces the relation between AI and SE, and varioustechniques evolved while merging.

  10. Projective simulation for artificial intelligence

    Science.gov (United States)

    Briegel, Hans J.; de Las Cuevas, Gemma

    2012-05-01

    We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation.

  11. Artificial intelligence techniques in power systems

    Energy Technology Data Exchange (ETDEWEB)

    Laughton, M.A.

    1997-12-31

    Since the early to mid 1980s much of the effort in power systems analysis has turned away from the methodology of formal mathematical modelling which came from the fields of operations research, control theory and numerical analysis to the less rigorous techniques of artificial intelligence (AI). Today the main AI techniques found in power systems applications are those utilising the logic and knowledge representations of expert systems, fuzzy systems, artificial neural networks (ANN) and, more recently, evolutionary computing. These techniques will be outlined in this chapter and the power system applications indicated. (Author)

  12. Artificial intelligence - NASA. [robotics for Space Station

    Science.gov (United States)

    Erickson, J. D.

    1985-01-01

    Artificial Intelligence (AI) represents a vital common space support element needed to enable the civil space program and commercial space program to perform their missions successfully. It is pointed out that advances in AI stimulated by the Space Station Program could benefit the U.S. in many ways. A fundamental challenge for the civil space program is to meet the needs of the customers and users of space with facilities enabling maximum productivity and having low start-up costs, and low annual operating costs. An effective way to meet this challenge may involve a man-machine system in which artificial intelligence, robotics, and advanced automation are integrated into high reliability organizations. Attention is given to the benefits, NASA strategy for AI, candidate space station systems, the Space Station as a stepping stone, and the commercialization of space.

  13. Differing Methodological Perspectives in Artificial Intelligence Research

    OpenAIRE

    Hall, Rogers P.; Kibler, Dennis F.

    1985-01-01

    A variety of proposals for preferred methodological approaches has been advanced in the recent artificial intelligence (AI) literature. Rather than advocating a particular approach, this article attempts to explain the apparent confusion of efforts in the field in terms of differences among underlying methodological perspectives held by practicing researchers. The article presents a review of such perspectives discussed in the existing literature and then considers a descriptive and relativel...

  14. Answering Curious Questions about Artificial Intelligence

    Czech Academy of Sciences Publication Activity Database

    Wiedermann, Jiří

    Cham: Springer, 2015 - (Romportl, J.; Zackova, E.; Kelemen, J.), s. 187-199. (Topics in Intelligent Engineering and Informatics. 9). ISBN 978-3-319-09667-4. ISSN 2193-9411. [Artificial Dreams. International Conference. Pilsen (CZ), 05.11.2012-06.11.2012] R&D Projects: GA ČR GAP202/10/1333 Institutional support: RVO:67985807 Keywords : cognitive systems * computational models * non-uniform evolving automaton Subject RIV: IN - Informatics, Computer Science

  15. The Road to Quantum Artificial Intelligence

    OpenAIRE

    Sgarbas, Kyriakos N

    2007-01-01

    This paper overviews the basic principles and recent advances in the emerging field of Quantum Computation (QC), highlighting its potential application to Artificial Intelligence (AI). The paper provides a very brief introduction to basic QC issues like quantum registers, quantum gates and quantum algorithms and then it presents references, ideas and research guidelines on how QC can be used to deal with some basic AI problems, such as search and pattern matching, as soon as quantum computers...

  16. Coordination Techniques for Distributed Artificial Intelligence

    OpenAIRE

    Jennings, N. R.

    1996-01-01

    Coordination, the process by which an agent reasons about its local actions and the (anticipated) actions of others to try and ensure the community acts in a coherent manner, is perhaps the key problem of the discipline of Distributed Artificial Intelligence (DAI). In order to make advances it is important that the theories and principles which guide this central activity are uncovered and analysed in a systematic and rigourous manner. To this end, this paper models agent communities using a ...

  17. Parallel processing for artificial intelligence 1

    CERN Document Server

    Kanal, LN; Kumar, V; Suttner, CB

    1994-01-01

    Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic, constraint satisfaction, parsing of natural language, data filtering and data mining. The publication is divided into six sections. The first addresses parallel computing for processing and understanding images. The second discus

  18. A (Very) Brief History of Artificial Intelligence

    OpenAIRE

    Buchanan, Bruce G.

    2005-01-01

    In this brief history, the beginnings of artificial intelligence are traced to philosophy, fiction, and imagination. Early inventions in electronics, engineering, and many other disciplines have influenced AI. Some early milestones include work in problems solving which included basic work in learning, knowledge representation, and inference as well as demonstration programs in language understanding, translation, theorem proving, associative memory, and knowledge-based systems. The article e...

  19. Empirical Methods in Artificial Intelligence: A Review

    OpenAIRE

    Langley, Pat

    1996-01-01

    Paul Cohen's book Empirical Methods for Artificial Intelligence aims to encourage this trend by providing AI practitioners with the knowledge and tools needed for careful empirical evaluation. The volume provides broad coverage of experimental design and statistics, ranging from a gentle introduction of basic ideas to a detailed presentation of advanced techniques, often combined with illustrative examples of their application to the empirical study of AI. The book is generally well written, ...

  20. Artificial Intelligence Research at General Electric

    OpenAIRE

    Sweet, Larry

    1985-01-01

    General Electric is engaged in a broad range of research and development activities in artificial intelligence, with the dual objectives of improving the productivity of its internal operations and of enhancing future products and services in its aerospace, industrial, aircraft engine, commercial, and service sectors. Many of the applications projected for AI within GE will require significant advances in the state of the art in advanced inference, formal logic, and architectures for real-tim...

  1. Experimental Realization of Quantum Artificial Intelligence

    OpenAIRE

    Zhaokai, Li; Xiaomei, Liu; Nanyang, Xu; Jiangfeng, Du

    2014-01-01

    Machines are possible to have some artificial intelligence like human beings owing to particular algorithms or software. Such machines could learn knowledge from what people taught them and do works according to the knowledge. In practical learning cases, the data is often extremely complicated and large, thus classical learning machines often need huge computational resources. Quantum machine learning algorithm, on the other hand, could be exponentially faster than classical machines using q...

  2. Friendly Artificial Intelligence: the Physics Challenge

    OpenAIRE

    Tegmark, Max

    2014-01-01

    Relentless progress in artificial intelligence (AI) is increasingly raising concerns that machines will replace humans on the job market, and perhaps altogether. Eliezer Yudkowski and others have explored the possibility that a promising future for humankind could be guaranteed by a superintelligent "Friendly AI", designed to safeguard humanity and its values. I argue that, from a physics perspective where everything is simply an arrangement of elementary particles, this might be even harder ...

  3. Artificial intelligence approach to legal reasoning

    International Nuclear Information System (INIS)

    For artificial intelligence, understanding the forms of human reasoning is a central goal. Legal reasoning is a form that makes a new set of demands on artificial intelligence methods. Most importantly, a computer program that reasons about legal problems must be able to distinguish between questions it is competent to answer and questions that human lawyers could seriously argue either way. In addition, a program for analyzing legal problems should be able to use both general legal rules and decisions in past cases; and it should be able to work with technical concepts that are only partly defined and subject to shifts of meaning. Each of these requirements has wider applications in artificial intelligence, beyond the legal domain. This dissertation presents a computational framework for legal reasoning, within which such requirements can be accommodated. The development of the framework draws significantly on the philosophy of law, in which the elucidation of legal reasoning is an important topic. A key element of the framework is the legal distinction between hard cases and clear cases. In legal writing, this distinction has been taken for granted more often than it has been explored. Here, some initial heuristics are proposed by which a program might make the distinction

  4. Artificial intelligence approach to accelerator control systems

    International Nuclear Information System (INIS)

    An experiment was recently started at LAMPF to evaluate the power and limitations of using artificial intelligence techniques to solve problems in accelerator control and operation. A knowledge base was developed to describe the characteristics and the relationships of the first 30 devices in the LAMPF H+ beam line. Each device was categorized and pertinent attributes for each category defined. Specific values were assigned in the knowledge base to represent each actual device. Relationships between devices are modeled using the artificial intelligence techniques of rules, active values, and object-oriented methods. This symbolic model, built using the Knowledge Engineering Environment (KEE) system, provides a framework for analyzing faults, tutoring trainee operators, and offering suggestions to assist in beam tuning. Based on information provided by the domain expert responsible for tuning this portion of the beam line, additional rules were written to describe how he tunes, how he analyzes what is actually happening, and how he deals with failures. Initial results have shown that artificial intelligence techniques can be a useful adjunct to traditional methods of numerical simulation. Successful and efficient operation of future accelerators may depend on the proper merging of symbolic reasoning and conventional numerical control algorithms

  5. E-LEARNING EXPERIENCE WITH ARTIFICIAL INTELLIGENCE SUPPORTED SOFTWARE: An International Application on English Language Courses

    OpenAIRE

    Kose, Utku; Arslan, Ahmet

    2015-01-01

    Nowadays, artificial intelligence supported e-learning scenarios are widely employed by educational institutions in order to ensure better teaching and learning experiences along educational activities. In the context of performed scientific studies, positive results often encourage such institutions to apply their intelligent e-learning systems on different types of courses and report advantages of artificial intelligent in especially education field. It seems that the future of education w...

  6. Artificial Intelligence and Computer Assisted Instruction. CITE Report No. 4.

    Science.gov (United States)

    Elsom-Cook, Mark

    The purpose of the paper is to outline some of the major ways in which artificial intelligence research and techniques can affect usage of computers in an educational environment. The role of artificial intelligence is defined, and the difference between Computer Aided Instruction (CAI) and Intelligent Computer Aided Instruction (ICAI) is…

  7. Application of artificial intelligence to improve aircraft survivability

    OpenAIRE

    Decker, William Leecraft

    1985-01-01

    Approved for public release; distribution is unlimited The hazards associated with the critical flight phases of civil as well as military flight operations can seriously degrade pilot efficiency, and therefore aircraft survivability, if the number or complexity of tasks that the pilot must manage exceeds his/her capabilities. This thesis explores the feasibility of applying artificial intelligence (AI) research to the construction of a Survivability Manager (SM) knowledge based system (K...

  8. An Artificial Intelligence Environment for Information Retrieval Research

    OpenAIRE

    France, Robert K.; Edward A Fox

    1988-01-01

    The CODER (COmposite Document Expert/Extended/Effective Retrieval) project is a multi-year effort to investigate how best to apply artificial intelligence methods to increase the effectiveness of information retrieval systems. Particular attention is being given to analysis and representation of heterogeneous documents, such as electronic mail digests or messages, which vary widely in style, length, topic,and structure. In order to ensure system adaptability and to allow reconfiguration for c...

  9. Artificial Intelligence in Video Games: Towards a Unified Framework

    OpenAIRE

    Safadi, Firas

    2015-01-01

    The work presented in this dissertation revolves around the problem of designing artificial intelligence (AI) for video games. This problem becomes increasingly challenging as video games grow in complexity. With modern video games frequently featuring sophisticated and realistic environments, the need for smart and comprehensive agents that understand the various aspects of these environments is pressing. Although machine learning techniques are being successfully applied in a multitude of d...

  10. Artificial Intelligence at Advanced Information and Decision Systems

    OpenAIRE

    McCune, Brian P.

    1981-01-01

    Advanced Information and Decision Systems (AI-DS) is a relatively new, employee-owned company that does basic and applied research, product development, and consulting in the fields of artificial intelligence, computer science, decision analysis, operations research, control theory, estimation theory, and signal processing. AI&DS performs studies, analyses, systems design and evaluation, and software development for a variety of industrial clients and government agencies, including the Depart...

  11. ARCHON: A Distributed Artificial Intelligence System for Industrial Applications

    OpenAIRE

    Cockburn, D; Jennings, N. R.

    1996-01-01

    ARCHON™ (ARchitecture for Cooperative Heterogeneous ON-line systems) is Europe’s largest project in the area of Distributed Artificial Intelligence (DAI). It has devised a general-purpose architecture, software framework and methodology which has been used to support the development of DAI systems in a number of industrial domains. Some examples of the applications to which it has been successfully applied include: electricity distribution and supply, electricity transmission and distribution...

  12. Micromechanics as a testbed for artificial intelligence methods evaluation

    OpenAIRE

    Kussul, Ernst; Baidyk, Tatiana; Lara Rosano, Felipe; Makeyev, Oleksandr; Martín, Anabel; Wunsch, Donald

    2006-01-01

    Some of the artificial intelligence (AI) methods could be used to improve the performance of automation systems in manufacturing processes. However, the application of these methods in the industry is not widespread because of the high cost of the experiments with the AI systems applied to the conventional manufacturing systems. To reduce the cost of such experiments, we have developed a special micromechanical equipment, similar to conventional mechanical equipment, but of a lot smaller o...

  13. Artificial Intelligence and Marine Design

    OpenAIRE

    Amarel, Saul; Steinberg, Louis

    1990-01-01

    In the last few years, interest has grown in exploring AI approaches to design problems, both because of the enormous potential impact on productivity of improved design tools and because of the interesting basic AI issues that these problems raise. In particular, a number of ship designers and AI researchers recently became interested in applying AI to the hydrodynamic design of ship hulls. A typical problem here is to design the shape of a ship's hull in response to desired hydrodynamic pro...

  14. Artificial Intelligence and Robotic From the Past to Present

    Directory of Open Access Journals (Sweden)

    Elnaz Asgarifar

    2013-04-01

    Full Text Available This paper overviews the basic principles and recent advances in the Artificial Intelligent robotics and the utilization of robots in nowadays life and the various compass. The aim of the paper is to introduce the basic concepts of artificial intelligent techniques and present a survey about robots. In first section we have a survey on the concept of artificial intelligence and intelligence life; also we introduce two important factors in artificial intelligence. In the next section, we have overview on the basic elements of artificial intelligence. Then, another important section in this paper is intelligent robots and the behavior based robotics. The use of robots in nowadays life is in the various domains. We introduce one of them that are rehabilitation robots.

  15. Non-Newtonian Aspects of Artificial Intelligence

    Science.gov (United States)

    Zak, Michail

    2016-05-01

    The challenge of this work is to connect physics with the concept of intelligence. By intelligence we understand a capability to move from disorder to order without external resources, i.e., in violation of the second law of thermodynamics. The objective is to find such a mathematical object described by ODE that possesses such a capability. The proposed approach is based upon modification of the Madelung version of the Schrodinger equation by replacing the force following from quantum potential with non-conservative forces that link to the concept of information. A mathematical formalism suggests that a hypothetical intelligent particle, besides the capability to move against the second law of thermodynamics, acquires such properties like self-image, self-awareness, self-supervision, etc. that are typical for Livings. However since this particle being a quantum-classical hybrid acquires non-Newtonian and non-quantum properties, it does not belong to the physics matter as we know it: the modern physics should be complemented with the concept of the information force that represents a bridge to intelligent particle. As a follow-up of the proposed concept, the following question is addressed: can artificial intelligence (AI) system composed only of physical components compete with a human? The answer is proven to be negative if the AI system is based only on simulations, and positive if digital devices are included. It has been demonstrated that there exists such a quantum neural net that performs simulations combined with digital punctuations. The universality of this quantum-classical hybrid is in capability to violate the second law of thermodynamics by moving from disorder to order without external resources. This advanced capability is illustrated by examples. In conclusion, a mathematical machinery of the perception that is the fundamental part of a cognition process as well as intelligence is introduced and discussed.

  16. Artificial Intelligence – Making an Intelligent personal assistant

    OpenAIRE

    Mr. Ankush Bhatia

    2015-01-01

    A bot in computing is an autonomous program on a network (especially the Internet) which can interact with systems or users.[ Simpson, J., and Weiner, E. (1989)] This document gives the description of how memory of an Artificial-Intelligence bot can be stored in an optimized way with a faster searching algorithm and how it can learn new things; the user wants the bot to learn. This paper gives the details of how a bot uses a an ordered tree data structure, called TRIE or a prefix tree to dyna...

  17. Artificial intelligence as a diagnostic adjunct in cardiovascular nuclear imaging

    International Nuclear Information System (INIS)

    The radiologist and/or nuclear medicine physician is literally bombarded with information from today's diagnostic imaging technologies. As a consequence of this, whereas a decade ago the emphasis in medical image analysis was on improving the extraction of diagnostic information by developing and using more sophisticated imaging modalities, today those working on the development of medical imaging technology are struggling to find ways to handle all gathered information effectively. This chapter gives an introduction to the area of artificial intelligence, with an emphasis on the research ongoing in cardiovascular nuclear imaging. This chapter has reviewed the place of artificial intelligence in cardiovascular nuclear imaging. It is intended to provide a general sense of this new and emerging field, an insight into some of its specific methodologies and applications, and a closer look at the several AI approaches currently being applied in cardiovascular nuclear imaging

  18. The epistemology and information systems based on artificial intelligence

    Directory of Open Access Journals (Sweden)

    Miguel Rendueles Mata

    2011-02-01

    Full Text Available The Epistemology was been a Philosophy discipline, that takes its own autonomy from different XVII century currents. The epistemology action field considers the possibility of human intelligence representation. Because of the born of Information Systems based on Artificial Intelligence, the Epistemology is in front of a new challenge, its seems that a lot of things has to be clarify according with the advances on this area. This article reflects the problem and suggests the idea to conjugate the new advances of the epistemological tradition with the Artificial Intelligence.Key Words: Epistemology, Knowledge Theory, Ontology, Artificial Intelligence, Natural Intelligence.

  19. Artificial Intelligence-The Emerging Technology

    Directory of Open Access Journals (Sweden)

    R. P. Shenoy

    1985-04-01

    Full Text Available Artificial Intelligence (AI, once considered as an obscure branch of computer science, is now having a growing number of adherents in a wide variety of fields. AI is particularly useful for combat automation in defence. The combined works of computer scientists and technologists and cognitive scientists have brought out for intelligent information processing knowledge is the key factor. In the last few years, AI has been tried out with a high degree of success in certain areas such as the Expert Systems and the Computer Vision Systems. Both these have great potential in target classification and identification, information fusion, multiradar Air Defence Network, C2 (Command andControl operations etc. in defence.

  20. Artificial intelligence applications at the ICPP

    International Nuclear Information System (INIS)

    Westinghouse Idaho Nuclear Company (WINCO) initiated an aggressive program for artificial intelligence (AI) expert system implementations in 1985. The first expert system, Safety Analysis Methods Advisor (SAMA) was completed in 1986 to help operational safety analysts select analysis methodologies for safety analysis reports. The SAMA expert system was implemented as a rule-based system using a commercial expert system shell. The major benefit of the system is for training new safety analysts. The first successful implementation launched three other expert system projects: a process alarm filtering system, a process control advisor, and a mass spectrometer trouble-shooting advisor. This paper describes the current status of these projects

  1. Markov decision processes in artificial intelligence

    CERN Document Server

    Sigaud, Olivier

    2013-01-01

    Markov Decision Processes (MDPs) are a mathematical framework for modeling sequential decision problems under uncertainty as well as Reinforcement Learning problems. Written by experts in the field, this book provides a global view of current research using MDPs in Artificial Intelligence. It starts with an introductory presentation of the fundamental aspects of MDPs (planning in MDPs, Reinforcement Learning, Partially Observable MDPs, Markov games and the use of non-classical criteria). Then it presents more advanced research trends in the domain and gives some concrete examples using illustr

  2. Beyond Artificial Intelligence toward Engineered Psychology

    Science.gov (United States)

    Bozinovski, Stevo; Bozinovska, Liljana

    This paper addresses the field of Artificial Intelligence, road it went so far and possible road it should go. The paper was invited by the Conference of IT Revolutions 2008, and discusses some issues not emphasized in AI trajectory so far. The recommendations are that the main focus should be personalities rather than programs or agents, that genetic environment should be introduced in reasoning about personalities, and that limbic system should be studied and modeled. Engineered Psychology is proposed as a road to go. Need for basic principles in psychology are discussed and a mathematical equation is proposed as fundamental law of engineered and human psychology.

  3. Optimizing radiologic workup: An artificial intelligence approach

    International Nuclear Information System (INIS)

    The increasing complexity of diagnostic imaging is presenting an ever-expanding variety of radiologic test options to referring clinicians, making it more difficult for them to plan efficient workup. Diagnosis-oriented reimbursement systems are providing new incentives for hospitals and radiologists to use imaging modalities judiciously. This paper describes DxCON, a developmental artificial intelligence-based computer system, which gives advice to physicians about the optimum sequencing of radiologic tests. DxCON analyzes a physician's proposed workup plan and discusses its strengths and weaknesses. The domain chosen for this research is the imaging workup of obstructive jaundice

  4. Probabilistic machine learning and artificial intelligence

    Science.gov (United States)

    Ghahramani, Zoubin

    2015-05-01

    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

  5. Parallel processing for artificial intelligence 2

    CERN Document Server

    Kumar, V; Suttner, CB

    1994-01-01

    With the increasing availability of parallel machines and the raising of interest in large scale and real world applications, research on parallel processing for Artificial Intelligence (AI) is gaining greater importance in the computer science environment. Many applications have been implemented and delivered but the field is still considered to be in its infancy. This book assembles diverse aspects of research in the area, providing an overview of the current state of technology. It also aims to promote further growth across the discipline. Contributions have been grouped according to their

  6. A Progress Report on Artificial Intelligence: Hospital Applications and a Review of the Artificial Intelligence Marketplace

    OpenAIRE

    Brenkus, Lawrence M.

    1984-01-01

    Artificial intelligence applications are finally beginning to move from the university research laboratory into commercial use. Before the end of the century, this new computer technology will have profound effects on our work, economy, and lives. At present, relatively few products have appeared in the hospital, but we can anticipate significant product offerings in instrumentation and affecting hospital administration within 5 years.

  7. A Characterization of the Utility of Using Artificial Intelligence to Test Two Artificial Intelligence Systems

    Directory of Open Access Journals (Sweden)

    Jeremy Straub

    2013-05-01

    Full Text Available An artificial intelligence system, designed for operations in a real-world environment faces a nearly infinite set of possible performance scenarios. Designers and developers, thus, face the challenge of validating proper performance across both foreseen and unforeseen conditions, particularly when the artificial intelligence is controlling a robot that will be operating in close proximity, or may represent a danger, to humans. While the manual creation of test cases allows limited testing (perhaps ensuring that a set of foreseeable conditions trigger an appropriate response, this may be insufficient to fully characterize and validate safe system performance. An approach to validating the performance of an artificial intelligence system using a simple artificial intelligence test case producer (AITCP is presented. The AITCP allows the creation and simulation of prospective operating scenarios at a rate far exceeding that possible by human testers. Four scenarios for testing an autonomous navigation control system are presented: single actor in two-dimensional space, multiple actors in two-dimensional space, single actor in three-dimensional space, and multiple actors in three-dimensional space. The utility of using the AITCP is compared to that of human testers in each of these scenarios.

  8. Accelerating artificial intelligence with reconfigurable computing

    Science.gov (United States)

    Cieszewski, Radoslaw

    Reconfigurable computing is emerging as an important area of research in computer architectures and software systems. Many algorithms can be greatly accelerated by placing the computationally intense portions of an algorithm into reconfigurable hardware. Reconfigurable computing combines many benefits of both software and ASIC implementations. Like software, the mapped circuit is flexible, and can be changed over the lifetime of the system. Similar to an ASIC, reconfigurable systems provide a method to map circuits into hardware. Reconfigurable systems therefore have the potential to achieve far greater performance than software as a result of bypassing the fetch-decode-execute operations of traditional processors, and possibly exploiting a greater level of parallelism. Such a field, where there is many different algorithms which can be accelerated, is an artificial intelligence. This paper presents example hardware implementations of Artificial Neural Networks, Genetic Algorithms and Expert Systems.

  9. Artificial intelligence model for sustain ability measurement

    International Nuclear Information System (INIS)

    The article analyses the main dimensions of organizational sustain ability, their possible integrations into artificial neural network. In this article authors performing analyses of organizational internal and external environments, their possible correlations with 4 components of sustain ability, and the principal determination models for sustain ability of organizations. Based on the general principles of sustainable development organizations, a artificial intelligence model for the determination of organizational sustain ability has been developed. The use of self-organizing neural networks allows the identification of the organizational sustain ability and the endeavour to explore vital, social, antropogenical and economical efficiency. The determination of the forest enterprise sustain ability is expected to help better manage the sustain ability. (Authors)

  10. An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part A: The core ingredients

    Science.gov (United States)

    Gevarter, W. B.

    1983-01-01

    Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. The goal of Artificial Intelligence is focused on developing computational approaches to intelligent behavior. This goal is so broad - covering virtually all aspects of human cognitive activity - that substantial confusion has arisen as to the actual nature of AI, its current status and its future capability. This volume, the first in a series of NBS/NASA reports on the subject, attempts to address these concerns. Thus, this report endeavors to clarify what AI is, the foundations on which it rests, the techniques utilized, applications, the participants and, finally, AI's state-of-the-art and future trends. It is anticipated that this report will prove useful to government and private engineering and research managers, potential users, and others who will be affected by this field as it unfolds.

  11. Research in artificial intelligence for nuclear facilities

    International Nuclear Information System (INIS)

    The application of artificial intelligence, in the form of expert systems and neural networks, to the control room activities in a nuclear power plant has the potential to reduce operator error and increase plant safety, reliability, and efficiency. Furthermore, artificial intelligence can increase efficiency and effectiveness in a large number of nonoperating activities (testing, routine maintenance, outage planning, equipment diagnostics, and fuel management) and in research facility experiments. Recent work at the University of Tennessee has demonstrated the feasibility of using neural networks to identify six different transients introduced into the simulation of a steam generator of a nuclear power plant. This work is now being extended to utilize data from a nuclear power plant training simulator. In one configuration, the inputs to the neural network are a subset of the quantities that are typical of those available from the safety parameter display system. The outputs of the network represent the various states of the plant (e.g., normal operation, coolant leakage, inadequate core flow, excessive peak fuel temperature, etc.). Training of the neural network is performed by introducing various faults or conditions to be diagnosed into the simulator. The goal of this work is to demonstrate a neural network diagnostic system that could provide advice to the operators in accordance with the emergency operating procedures

  12. Artificial Intelligence Research Branch future plans

    Science.gov (United States)

    Stewart, Helen (Editor)

    1992-01-01

    This report contains information on the activities of the Artificial Intelligence Research Branch (FIA) at NASA Ames Research Center (ARC) in 1992, as well as planned work in 1993. These activities span a range from basic scientific research through engineering development to fielded NASA applications, particularly those applications that are enabled by basic research carried out in FIA. Work is conducted in-house and through collaborative partners in academia and industry. All of our work has research themes with a dual commitment to technical excellence and applicability to NASA short, medium, and long-term problems. FIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at the Jet Propulsion Laboratory (JPL) and AI applications groups throughout all NASA centers. This report is organized along three major research themes: (1) Planning and Scheduling: deciding on a sequence of actions to achieve a set of complex goals and determining when to execute those actions and how to allocate resources to carry them out; (2) Machine Learning: techniques for forming theories about natural and man-made phenomena; and for improving the problem-solving performance of computational systems over time; and (3) Research on the acquisition, representation, and utilization of knowledge in support of diagnosis design of engineered systems and analysis of actual systems.

  13. Artificial intelligence. Fears of an AI pioneer.

    Science.gov (United States)

    Russell, Stuart; Bohannon, John

    2015-07-17

    From the enraged robots in the 1920 play R.U.R. to the homicidal computer H.A.L. in 2001: A Space Odyssey, science fiction writers have embraced the dark side of artificial intelligence (AI) ever since the concept entered our collective imagination. Sluggish progress in AI research, especially during the “AI winter” of the 1970s and 1980s, made such worries seem far-fetched. But recent breakthroughs in machine learning and vast improvements in computational power have brought a flood of research funding— and fresh concerns about where AI may lead us. One researcher now speaking up is Stuart Russell, a computer scientist at the University of California, Berkeley, who with Peter Norvig, director of research at Google, wrote the premier AI textbook, Artificial Intelligence: A Modern Approach, now in its third edition. Last year, Russell joined the Centre for the Study of Existential Risk at Cambridge University in the United Kingdom as an AI expert focusing on “risks that could lead to human extinction.” Among his chief concerns, which he aired at an April meeting in Geneva, Switzerland, run by the United Nations, is the danger of putting military drones and weaponry under the full control of AI systems. This interview has been edited for clarity and brevity. PMID:26185241

  14. Artificial intelligence approaches to software engineering

    Science.gov (United States)

    Johannes, James D.; Macdonald, James R.

    1988-01-01

    Artificial intelligence approaches to software engineering are examined. The software development life cycle is a sequence of not so well-defined phases. Improved techniques for developing systems have been formulated over the past 15 years, but pressure continues to attempt to reduce current costs. Software development technology seems to be standing still. The primary objective of the knowledge-based approach to software development presented in this paper is to avoid problem areas that lead to schedule slippages, cost overruns, or software products that fall short of their desired goals. Identifying and resolving software problems early, often in the phase in which they first occur, has been shown to contribute significantly to reducing risks in software development. Software development is not a mechanical process but a basic human activity. It requires clear thinking, work, and rework to be successful. The artificial intelligence approaches to software engineering presented support the software development life cycle through the use of software development techniques and methodologies in terms of changing current practices and methods. These should be replaced by better techniques that that improve the process of of software development and the quality of the resulting products. The software development process can be structured into well-defined steps, of which the interfaces are standardized, supported and checked by automated procedures that provide error detection, production of the documentation and ultimately support the actual design of complex programs.

  15. Artificial intelligence and engineering curricula - are changes needed?

    International Nuclear Information System (INIS)

    The purpose of this paper is to identify the expected impact of artificial intelligence (AI) on curricula and training courses. From this examination, new elements are proposed for the academic preparation and training of engineers who will evaluate and use these systems and capabilities. Artificial intelligence, from an operational viewpoint, begins with a set of rules governing the operation of logic, implemented via computer software and userware. These systems apply logic and experience to handling problems in an intelligent approach, especially when the number of alternatives to problem solution is beyond the scope of the human user. Usually, AI applications take the form of expert systems. An expert system embodies in the computer the knowledge-based component of an expert, such as domain knowledge and reasoning techniques, in such a form that the system can offer intelligent advice and, on demand, justify its own line of reasoning. Two languages predominate, LISP and Prolog. The AI user may interface with the knowledge base via one of these languages or by means of menu displays, cursor selections, or other conventional user interface methods

  16. Application of Artificial Intelligence Techniques in Unmanned Aerial Vehicle Flight

    Science.gov (United States)

    Bauer, Frank H. (Technical Monitor); Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in Artificial Intelligence (AI) at Nova southeastern University and as an adjunct to a project at NASA Goddard Space Flight Center's Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an AI method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed. A low cost approach was taken using freeware, gnu, software, and demo programs. The focus of this research has been to outline some of the AI techniques used for UAV flight control and discuss some of the tools used to apply AI techniques. The intent is to succeed with the implementation of applying AI techniques to actually control different aspects of the flight of an UAV.

  17. The 1993 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Hostetter, Carl F. (Editor)

    1993-01-01

    This publication comprises the papers presented at the 1993 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, MD on May 10-13, 1993. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

  18. The 1994 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Hostetter, Carl F. (Editor)

    1994-01-01

    This publication comprises the papers presented at the 1994 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/GSFC, Greenbelt, Maryland, on 10-12 May 1994. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

  19. The Biological Relevance of Artificial Life: Lessons from Artificial Intelligence

    Science.gov (United States)

    Colombano, Silvano

    2000-01-01

    There is no fundamental reason why A-life couldn't simply be a branch of computer science that deals with algorithms that are inspired by, or emulate biological phenomena. However, if these are the limits we place on this field, we miss the opportunity to help advance Theoretical Biology and to contribute to a deeper understanding of the nature of life. The history of Artificial Intelligence provides a good example, in that early interest in the nature of cognition quickly was lost to the process of building tools, such as "expert systems" that, were certainly useful, but provided little insight in the nature of cognition. Based on this lesson, I will discuss criteria for increasing the biological relevance of A-life and the probability that this field may provide a theoretical foundation for Biology.

  20. The 1990 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Rash, James L. (Editor)

    1990-01-01

    The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

  1. Artificial Intelligence – Making an Intelligent personal assistant

    Directory of Open Access Journals (Sweden)

    Mr. Ankush Bhatia

    2015-12-01

    Full Text Available A bot in computing is an autonomous program on a network (especially the Internet which can interact with systems or users.[ Simpson, J., and Weiner, E. (1989] This document gives the description of how memory of an Artificial-Intelligence bot can be stored in an optimized way with a faster searching algorithm and how it can learn new things; the user wants the bot to learn. This paper gives the details of how a bot uses a an ordered tree data structure, called TRIE or a prefix tree to dynamically store the things it learns and what to reply when a person commands asks him something, with a little modification.

  2. A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms

    Directory of Open Access Journals (Sweden)

    Gys Albertus Marthinus Meiring

    2015-12-01

    Full Text Available In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced.

  3. The role of artificial intelligence and expert systems in increasing STS operations productivity

    Science.gov (United States)

    Culbert, C.

    1985-01-01

    Artificial Intelligence (AI) is discussed. A number of the computer technologies pioneered in the AI world can make significant contributions to increasing STS operations productivity. Application of expert systems, natural language, speech recognition, and other key technologies can reduce manpower while raising productivity. Many aspects of STS support lend themselves to this type of automation. The artificial intelligence section of the mission planning and analysis division has developed a number of functioning prototype systems which demonstrate the potential gains of applying AI technology.

  4. Enhancing nuclear power plant performance through the use of artificial intelligence

    International Nuclear Information System (INIS)

    The objective of this research was to advance the state-of-the-art of applying artificial intelligence technology (both expert systems and neural networks) to enhancing the performance (safety, efficiency, control and management) of nuclear power plants. A second, but equally important objective, was to build a broadly based critical mass of expertise in the artificial intelligence field that can be brought to bear on the technology of nuclear power plants

  5. Robustness in Nature as a Design Principle for Artificial Intelligence

    Science.gov (United States)

    Schuster, Alfons

    Robustness is a feature in many systems, natural and artificial alike. This chapter investigates robustness from a variety of perspectives including its appearances in nature and its application in modern environments. A particular focus investigates the relevance and importance of robustness in a discipline where many techniques are inspired by problem-solving strategies found in nature—artificial intelligence. The challenging field of artificial intelligence provides an opportunity to engage in a wider discussion on the subject of robustness.

  6. Artificial Intelligence Software Engineering (AISE) model

    Science.gov (United States)

    Kiss, Peter A.

    1990-01-01

    The American Institute of Aeronautics and Astronautics has initiated a committee on standards for Artificial Intelligence. Presented are the initial efforts of one of the working groups of that committee. A candidate model is presented for the development life cycle of knowledge based systems (KBSs). The intent is for the model to be used by the aerospace community and eventually be evolved into a standard. The model is rooted in the evolutionary model, borrows from the spiral model, and is embedded in the standard Waterfall model for software development. Its intent is to satisfy the development of both stand-alone and embedded KBSs. The phases of the life cycle are shown and detailed as are the review points that constitute the key milestones throughout the development process. The applicability and strengths of the model are discussed along with areas needing further development and refinement by the aerospace community.

  7. Artificial intelligence in the materials processing laboratory

    Science.gov (United States)

    Workman, Gary L.; Kaukler, William F.

    1990-01-01

    Materials science and engineering provides a vast arena for applications of artificial intelligence. Advanced materials research is an area in which challenging requirements confront the researcher, from the drawing board through production and into service. Advanced techniques results in the development of new materials for specialized applications. Hand-in-hand with these new materials are also requirements for state-of-the-art inspection methods to determine the integrity or fitness for service of structures fabricated from these materials. Two problems of current interest to the Materials Processing Laboratory at UAH are an expert system to assist in eddy current inspection of graphite epoxy components for aerospace and an expert system to assist in the design of superalloys for high temperature applications. Each project requires a different approach to reach the defined goals. Results to date are described for the eddy current analysis, but only the original concepts and approaches considered are given for the expert system to design superalloys.

  8. Artificial intelligence in process design and operation

    International Nuclear Information System (INIS)

    Artificial Intelligence (AI) has recently become prominent in the discussion of computer applications in the utility business. In order to assess this technology, a research project was performed to determine whether software development techniques based on AI could be used to facilitate management of information associated with the design of a generating station. The approach taken was the development of an expert system, using a relatively simple set of rules acting on a more complex knowledge base. A successful prototype for the application was developed and its potential extension to a production environment demonstrated. During the course of prototype development, other possible applications of AI in design engineering were discovered, and areas of particular interest selected for further investigation. A plan for AI R and D was formulated. That plan and other possible future work in AI are discussed

  9. An artificial intelligence approach towards disturbance analysis

    International Nuclear Information System (INIS)

    Scale and degree of sophistication of technological plants, e.g. nuclear power plants, have been essentially increased during the last decades. Conventional disturbance analysis systems have proved to work successfully in well-known situations. But in cases of emergencies, the operator needs more advanced assistance in realizing diagnosis and therapy control. The significance of introducing artificial intelligence (AI) methods in nuclear power technology is emphasized. Main features of the on-line disturbance analysis system SAAP-2 are reported about. It is being developed for application to nuclear power plants. Problems related to man-machine communication will be gone into more detail, because their solution will influence end-user acceptance considerably. (author)

  10. Issues and challenges in artificial intelligence

    CERN Document Server

    Kulikowski, Juliusz; Mroczek, Teresa; Wtorek, Jerzy

    2014-01-01

    The importance of human-computer system interaction problems is increasing due to the growing expectations of users on general computer systems capabilities in human work and life facilitation. Users expect system which is not only a passive tool in human hands but rather an active partner equipped with a sort of artificial intelligence, having access to large information resources, being able to adapt its behavior to the human requirements and to collaborate with the human users.   This book collects examples of recent human-computer system solutions. The content of the book is divided into three parts. Part I is devoted to detection, recognition and reasoning in different circumstances and applications. Problems associated with data modeling, acquisition and mining are presented by papers collected in part II and part III is devoted to Optimization.

  11. An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part B: Applications

    Science.gov (United States)

    Gevarter, W. B.

    1983-01-01

    Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. This report, Part B of a three part report on AI, presents overviews of the key application areas: Expert Systems, Computer Vision, Natural Language Processing, Speech Interfaces, and Problem Solving and Planning. The basic approaches to such systems, the state-of-the-art, existing systems and future trends and expectations are covered.

  12. Amplify scientific discovery with artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Gil, Yolanda; Greaves, Mark T.; Hendler, James; Hirsch, Hyam

    2014-10-10

    Computing innovations have fundamentally changed many aspects of scientific inquiry. For example, advances in robotics, high-end computing, networking, and databases now underlie much of what we do in science such as gene sequencing, general number crunching, sharing information between scientists, and analyzing large amounts of data. As computing has evolved at a rapid pace, so too has its impact in science, with the most recent computing innovations repeatedly being brought to bear to facilitate new forms of inquiry. Recently, advances in Artificial Intelligence (AI) have deeply penetrated many consumer sectors, including for example Apple’s Siri™ speech recognition system, real-time automated language translation services, and a new generation of self-driving cars and self-navigating drones. However, AI has yet to achieve comparable levels of penetration in scientific inquiry, despite its tremendous potential in aiding computers to help scientists tackle tasks that require scientific reasoning. We contend that advances in AI will transform the practice of science as we are increasingly able to effectively and jointly harness human and machine intelligence in the pursuit of major scientific challenges.

  13. Westinghouse use of artificial intelligence in signal interpretation

    International Nuclear Information System (INIS)

    This paper discusses Westinghouse's use of artificial intelligence to assist inspectors who routinely monitor the thousands of tubes in nuclear steam generators. Using the AI technology has made the inspection process easier to learn and to apply. The system uses pattern recognition to identify off-normal conditions. As part of the in-service inspection program for nuclear power reactors, utilities make a practice of inspecting the condition of the large heat exchangers that produce the steam that turns the electric turbine generator. The same data are presented for inspection using form, motion, and color to call attention to off-normal signal patterns

  14. Advances in artificial intelligence for privacy protection and security

    CERN Document Server

    Solanas, Agusti

    2009-01-01

    In this book, we aim to collect the most recent advances in artificial intelligence techniques (i.e. neural networks, fuzzy systems, multi-agent systems, genetic algorithms, image analysis, clustering, etc), which are applied to the protection of privacy and security. The symbiosis between these fields leads to a pool of invigorating ideas, which are explored in this book. On the one hand, individual privacy protection is a hot topic and must be addressed in order to guarantee the proper evolution of a modern society. On the other, security can invade individual privacy, especially after the a

  15. An Artificial Intelligence Approach for Gears Diagnostics in AUVs

    Directory of Open Access Journals (Sweden)

    Graciliano Nicolás Marichal

    2016-04-01

    Full Text Available In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles, where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved.

  16. An Artificial Intelligence Approach for Gears Diagnostics in AUVs

    Science.gov (United States)

    Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano

    2016-01-01

    In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved. PMID:27077868

  17. An Artificial Intelligence Approach for Gears Diagnostics in AUVs.

    Science.gov (United States)

    Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano

    2016-01-01

    In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved. PMID:27077868

  18. Beyond AI: Interdisciplinary Aspects of Artificial Intelligence

    CERN Document Server

    Romportl, Jan; Zackova, Eva; Beyond Artificial Intelligence : Contemplations, Expectations, Applications

    2013-01-01

    Products of modern artificial intelligence (AI) have mostly been formed by the views, opinions and goals of the “insiders”, i.e. people usually with engineering background who are driven by the force that can be metaphorically described as the pursuit of the craft of Hephaestus. However, since the present-day technology allows for tighter and tighter mergence of the “natural” everyday human life with machines of immense complexity, the responsible reaction of the scientific community should be based on cautious reflection of what really lies beyond AI, i.e. on the frontiers where the tumultuous ever-growing and ever-changing cloud of AI touches the rest of the world.   The chapters of this boo are based on the selected subset of the presentations that were delivered by their respective authors at the conference “Beyond AI: Interdisciplinary Aspects of Artificial Intelligence” held in Pilsen in December 2011.   From its very definition, the reflection of the phenomena that lie beyond AI must be i...

  19. WEEDS IDENTIFICATION USING EVOLUTIONARY ARTIFICIAL INTELLIGENCE ALGORITHM

    Directory of Open Access Journals (Sweden)

    Ahmed M. Tobal

    2014-01-01

    Full Text Available In a world reached a population of six billion humans increasingly demand it for food, feed with a water shortage and the decline of agricultural land and the deterioration of the climate needs 1.5 billion hectares of agricultural land and in case of failure to combat pests needs about 4 billion hectares. Weeds represent 34% of the whole pests while insects, diseases and the deterioration of agricultural land present the remaining percentage. Weeds Identification has been one of the most interesting classification problems for Artificial Intelligence (AI and image processing. The most common case is to identify weeds within the field as they reduce the productivity and harm the existing crops. Success in this area results in an increased productivity, profitability and at the same time decreases the cost of operation. On the other hand, when AI algorithms combined with appropriate imagery tools may present the right solution to the weed identification problem. In this study, we introduce an evolutionary artificial neural network to minimize the time of classification training and minimize the error through the optimization of the neuron parameters by means of a genetic algorithm. The genetic algorithm, with its global search capability, finds the optimum histogram vectors used for network training and target testing through a fitness measure that reflects the result accuracy and avoids the trial-and-error process of estimating the network inputs according to the histogram data.

  20. XII International Conference of the Italian Association on Artificial Intelligence

    CERN Document Server

    Semeraro, Giovanni; Vargiu, Eloisa; New Challenges in Distributed Information Filtering and Retrieval : DART 2011: Revised and Invited Papers

    2013-01-01

    This volume focuses on new challenges in distributed Information Filtering and Retrieval. It collects invited chapters and extended research contributions from the DART 2011 Workshop, held in Palermo (Italy), on September 2011, and co-located with the XII International Conference of the Italian Association on Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world applications. The chapters of this book present a comprehensive review of related works and state of the art. Authors, both practitioners and researchers, shared their results in several topics such as "Multi-Agent Systems", "Natural Language Processing", "Automatic Advertisement", "Customer Interaction Analytics", "Opinion Mining".

  1. The First Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI '06)

    OpenAIRE

    Augusto, Juan Carlos; Shapiro, Daniel

    2007-01-01

    The first annual workshop on the role of AI in ambient intelligence was held in Riva de Garda, Italy, on August 29, 2006. The workshop was colocated with the European Conference on Artificial Intelligence (ECAI 2006). It provided an opportunity for researchers in a variety of AI subfields together with representatives of commercial interests to explore ambient intelligence technology and applications.

  2. Artificial Intelligence Research in Engineering at North Carolina State University

    OpenAIRE

    Rasdorf, William J.; Fisher, Edward L.

    1985-01-01

    This article presents a summary of ongoing, funded artificial intelligence research at North Carolina State University. The primary focus of the research is engineering aspects of artificial intelligence. These research efforts can be categorized into four main areas: engineering expert systems, generative database management systems, human-machine communication, and robotics and vision. Involved in the research are investigators from both the School of Engineering and the Department of Compu...

  3. The Role of Artificial Intelligence Technologies in Crisis Response

    CERN Document Server

    Khalil, Khaled M; Nazmy, Taymour T; Salem, Abdel-Badeeh M

    2008-01-01

    Crisis response poses many of the most difficult information technology in crisis management. It requires information and communication-intensive efforts, utilized for reducing uncertainty, calculating and comparing costs and benefits, and managing resources in a fashion beyond those regularly available to handle routine problems. In this paper, we explore the benefits of artificial intelligence technologies in crisis response. This paper discusses the role of artificial intelligence technologies; namely, robotics, ontology and semantic web, and multi-agent systems in crisis response.

  4. ARTIFICIAL INTELLIGENCE PLANNING TECHNIQUES FOR ADAPTIVE VIRTUAL COURSE CONSTRUCTION

    OpenAIRE

    NÉSTOR DARÍO DUQUE; DEMETRIO ARTURO OVALLE

    2011-01-01

    This paper aims at presenting a planning model for adapting the behavior of virtual courses based on artificial intelligence techniques, in particular using not only a multi-agent system approach, but also artificial intelligence planning methods. The design and implementation of the system by means of a pedagogical multi-agent approach and the definition of a framework to specify the adaptation strategy allow us to incorporate several pedagogical and technological approaches that are in acco...

  5. Artificial intelligence applications in information and communication technologies

    CERN Document Server

    Bouguila, Nizar

    2015-01-01

    This book presents various recent applications of Artificial Intelligence in Information and Communication Technologies such as Search and Optimization methods, Machine Learning, Data Representation and Ontologies, and Multi-agent Systems. The main aim of this book is to help Information and Communication Technologies (ICT) practitioners in managing efficiently their platforms using AI tools and methods and to provide them with sufficient Artificial Intelligence background to deal with real-life problems.  .

  6. Computational neuroscience for advancing artificial intelligence

    Directory of Open Access Journals (Sweden)

    Fernando P. Ponce

    2011-07-01

    Full Text Available resumen del libro de Alonso, E. y Mondragón, E. (2011. Hershey, NY: Medical Information Science Reference. La neurociencia como disciplinapersigue el entendimiento del cerebro y su relación con el funcionamiento de la mente a través del análisis de la comprensión de la interacción de diversos procesos físicos, químicos y biológicos (Bassett & Gazzaniga, 2011. Por otra parte, numerosas disciplinasprogresivamente han realizado significativas contribuciones en esta empresa tales como la matemática, la psicología o la filosofía, entre otras. Producto de este esfuerzo, es que junto con la neurociencia tradicional han aparecido disciplinas complementarias como la neurociencia cognitiva, la neuropsicología o la neurocienciacomputacional (Bengio, 2007; Dayan & Abbott, 2005. En el contexto de la neurociencia computacional como disciplina complementaria a laneurociencia tradicional. Alonso y Mondragón (2011 editan el libroComputacional Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications.

  7. [Artificial intelligence] AI for protection systems

    Energy Technology Data Exchange (ETDEWEB)

    Aggarwal, R.; Johns, A.

    1997-12-31

    The reliable operation of large power systems with small stability margins is highly dependent on control systems and protection devices. Progress in the field of microprocessor systems and demanding requirements in respect of the performance of protective relays are the reasons for digital device applications to power system protection. The superiority of numeric protection over its analogue alternatives is attributed to such factors as accurate extraction of the fundamental voltage and current components through filtering, functional benefits resulting from multi-processor design and extensive self-monitoring, etc. However, all these reasons have not led to a major impact on speed, sensitivity and selectivity of primary protective relays, and the gains are only marginal; this is so because conventional digital relays still rely on deterministic signal models and a heuristic approach for decision making, so that only a fraction of the information contained within voltage and current signals as well as knowledge about the plant to be protected is used. The performance of digital relays may be substantially improved if the decision making is based on elements of artificial intelligence (AI). (Author)

  8. Artificial intelligence aid to efficient plant operations

    International Nuclear Information System (INIS)

    As the nuclear power industry matures, it is becoming more and more important that plants be operated in an efficient, cost-effective manner, without, of course, any decrease in the essential margins of safety. Indeed, most opportunities for improved efficiency have little or no relation to nuclear safety, but are based on trade-offs among operator controllable parameters both within and external to the reactor itself. While these trade-offs are describable in terms of basic physical theory, thermodynamics, and the mathematics of control systems, their actual application is highly plant specific and influenced even by the day-to-day condition of the various plant components. This paper proposes the use of artificial intelligence techniques to construct a computer-based expert assistant to the plant operator for the purpose of aiding him in improving the efficiency of plant operation on a routine basis. The proposed system, which only advises the human operator, seems more amenable to the current regulatory approach than a truly automated control system even if the latter provides for manual override

  9. Vibration energy harvester optimization using artificial intelligence

    Science.gov (United States)

    Hadas, Z.; Ondrusek, C.; Kurfurst, J.; Singule, V.

    2011-06-01

    This paper deals with an optimization study of a vibration energy harvester. This harvester can be used as autonomous source of electrical energy for remote or wireless applications, which are placed in environment excited by ambient mechanical vibrations. The ambient energy of vibrations is usually on very low level but the harvester can be used as alternative source of energy for electronic devices with an expected low level of power consumption of several mW. The optimized design of the vibration energy harvester was based on previous development and the sensitivity of harvester design was improved for effective harvesting from mechanical vibrations in aeronautic applications. The vibration energy harvester is a mechatronic system which generates electrical energy from ambient vibrations due to precision tuning up generator parameters. The optimization study for maximization of harvested power or minimization of volume and weight are the main goals of our development. The optimization study of such complex device is complicated therefore artificial intelligence methods can be used for tuning up optimal harvester parameters.

  10. Applications of artificial intelligence to mission planning

    Science.gov (United States)

    Ford, Donnie R.; Rogers, John S.; Floyd, Stephen A.

    1990-01-01

    The scheduling problem facing NASA-Marshall mission planning is extremely difficult for several reasons. The most critical factor is the computational complexity involved in developing a schedule. The size of the search space is large along some dimensions and infinite along others. It is because of this and other difficulties that many of the conventional operation research techniques are not feasible or inadequate to solve the problems by themselves. Therefore, the purpose is to examine various artificial intelligence (AI) techniques to assist conventional techniques or to replace them. The specific tasks performed were as follows: (1) to identify mission planning applications for object oriented and rule based programming; (2) to investigate interfacing AI dedicated hardware (Lisp machines) to VAX hardware; (3) to demonstrate how Lisp may be called from within FORTRAN programs; (4) to investigate and report on programming techniques used in some commercial AI shells, such as Knowledge Engineering Environment (KEE); and (5) to study and report on algorithmic methods to reduce complexity as related to AI techniques.

  11. Optimizing Water Treatment Systems Using Artificial Intelligence Based Tools

    OpenAIRE

    Pinto, Ana Mafalda; Fernandes, Ana; Vicente, Henrique; Neves, José

    2009-01-01

    Predictive modelling is a process used in predictive analytics to create a statistical model of future behaviour. Predictive analytics is the area of data mining concerned with forecasting probabilities and trends. On the other hand, Artificial Intelligence (AI) concerns itself with intelligent behaviour, i.e. the things that make us seem intelligent. Following this process of thinking, in this work the main goal is the assessment of the impact of using AI based tools for th...

  12. Worldwide Intelligent Systems: Approaches to Telecommunications and Network Management. Frontiers in Artificial Intelligence and Applications, Volume 24.

    Science.gov (United States)

    Liebowitz, Jay, Ed.; Prerau, David S., Ed.

    This is an international collection of 12 papers addressing artificial intelligence (AI) and knowledge technology applications in telecommunications and network management. It covers the latest and emerging AI technologies as applied to the telecommunications field. The papers are: "The Potential for Knowledge Technology in Telecommunications: A…

  13. Computational Narrative Intelligence: A Human-Centered Goal for Artificial Intelligence

    OpenAIRE

    Riedl, Mark O.

    2016-01-01

    Narrative intelligence is the ability to craft, tell, understand, and respond affectively to stories. We argue that instilling artificial intelligences with computational narrative intelligence affords a number of applications beneficial to humans. We lay out some of the machine learning challenges necessary to solve to achieve computational narrative intelligence. Finally, we argue that computational narrative is a practical step towards machine enculturation, the teaching of sociocultural v...

  14. Artificial intelligence applications in offshore oil and gas production

    International Nuclear Information System (INIS)

    The field of Artificial Intelligence (AI) has gained considerable acceptance in virtually all fields, of engineering applications. Artificial intelligence is now being applied in several areas of offshore oil and gas operations, such as drilling, well testing, well logging and interpretation, reservoir engineering, planning and economic evaluation, process control, and risk analysis. Current AI techniques offer a new and exciting technology for solving problems in the oil and gas industry. Expert systems, fuzzy logic systems, neural networks and genetic algorithms are major AI technologies which have made an impact on the petroleum industry. Presently, these technologies are at different stages of maturity with expert systems being the most mature and genetic algorithms the least. However, all four technologies have evolved such that practical applications were produced. This paper describes the four major Al techniques and their many applications in offshore oil and gas production operations. A summary description of future developments in Al technology that will affect the execution and productivity of offshore operations will be also provided

  15. Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

    Science.gov (United States)

    Abbasi, Maryam; El Hanandeh, Ali

    2016-10-01

    Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of future waste generation quantities. The main objective of this study was to develop a model for accurate forecasting of MSW generation that helps waste related organizations to better design and operate effective MSW management systems. Four intelligent system algorithms including support vector machine (SVM), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and k-nearest neighbours (kNN) were tested for their ability to predict monthly waste generation in the Logan City Council region in Queensland, Australia. Results showed artificial intelligence models have good prediction performance and could be successfully applied to establish municipal solid waste forecasting models. Using machine learning algorithms can reliably predict monthly MSW generation by training with waste generation time series. In addition, results suggest that ANFIS system produced the most accurate forecasts of the peaks while kNN was successful in predicting the monthly averages of waste quantities. Based on the results, the total annual MSW generated in Logan City will reach 9.4×10(7)kg by 2020 while the peak monthly waste will reach 9.37×10(6)kg. PMID:27297046

  16. The implementation of artificial intelligence in control systems

    International Nuclear Information System (INIS)

    Some concepts of artificial intelligence are reviewed, particularly as they apply to control systems of accelerators. Logical representation and formal reasoning are discussed briefly, as well as production systems, which describe various systems based on the idea of condition-action pairs (productions). Procedural knowledge, which deals with routine activities that rarely require change, is described. Frames are defined, which provide a convenient structure for representing knowledge. Frames consist of information about objects. For a given frame there are various slots, and for each slot there are various facets, each containing various data. Direct analogical representation is defined as a class of representation which represents knowledge in a natural analog manner, allowing observation of facts in many cases to be achieved quickly and easily compared to deduction. Architecture of systems applied to accelerator control is then described

  17. Medical image diagnosis of liver cancer using artificial intelligence

    International Nuclear Information System (INIS)

    A revised Group Method of Data Handling (GMDH)-type neural network algorithm using artificial intelligence technology for medical image diagnosis is proposed and is applied to medical image diagnosis of liver cancer. In this algorithm, the knowledge base for medical image diagnosis are used for organizing the neural network architecture for medical image diagnosis. Furthermore, the revised GMDH-type neural network algorithm has a feedback loop and can identify the characteristics of the medical images accurately using feedback loop calculations. The optimum neural network architecture fitting the complexity of the medical images is automatically organized so as to minimize the prediction error criterion defined as Prediction Sum of Squares (PSS). It is shown that the revised GMDH-type neural network can be easily applied to the medical image diagnosis. (author)

  18. Dynamic Analysis of Emotions through Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Susana Mejía M.

    2016-04-01

    Full Text Available Emotions have been demonstrated to be an important aspect of human intelligence and to play a significant role in human decision-making processes. Emotions are not only feelings but also processes of establishing, maintaining or disrupting the relation between the organism and the environment. In the present paper, several features of social and developmental Psychology are introduced, especially concepts that are related to Theories of Emotions and the Mathematical Tools applied in psychology (i.e., Dynamic Systems and Fuzzy Logic. Later, five models that infer emotions from a single event, in AV-Space, are presented and discussed along with the finding that fuzzy logic can measure human emotional states

  19. Artificial Life of Soybean Plant Growth Modeling Using Intelligence Approaches

    Directory of Open Access Journals (Sweden)

    Atris Suyantohadi

    2010-03-01

    Full Text Available The natural process on plant growth system has a complex system and it has could be developed on characteristic studied using intelligent approaches conducting with artificial life system. The approaches on examining the natural process on soybean (Glycine Max L.Merr plant growth have been analyzed and synthesized in these research through modeling using Artificial Neural Network (ANN and Lindenmayer System (L-System methods. Research aimed to design and to visualize plant growth modeling on the soybean varieties which these could help for studying botany of plant based on fertilizer compositions on plant growth with Nitrogen (N, Phosphor (P and Potassium (K. The soybean plant growth has been analyzed based on the treatments of plant fertilizer compositions in the experimental research to develop plant growth modeling. By using N, P, K fertilizer compositions, its capable result on the highest production 2.074 tons/hectares. Using these models, the simulation on artificial life for describing identification and visualization on the characteristic of soybean plant growth could be demonstrated and applied.

  20. Where Artificial Intelligence and Neuroscience Meet: The Search for Grounded Architectures of Cognition

    OpenAIRE

    Frank van der Velde

    2010-01-01

    The collaboration between artificial intelligence and neuroscience can produce an understanding of the mechanisms in the brain that generate human cognition. This article reviews multidisciplinary research lines that could achieve this understanding. Artificial intelligence has an important role to play in research, because artificial intelligence focuses on the mechanisms that generate intelligence and cognition. Artificial intelligence can also benefit from studying the neural mechanisms of...

  1. Taxonomic Evidence Applying Intelligent Information Taxonomic Evidence Applying Intelligent Information

    Directory of Open Access Journals (Sweden)

    Félix Anibal Vallejos

    2005-12-01

    Full Text Available The Numeric Taxonomy aims to group operational taxonomic units in clusters (OTUs or taxons or taxa, using the denominated structure analysis by means of numeric methods. These clusters that constitute families are the purpose of this series of projects and they emerge of the structural analysis, of their phenotypical characteristic, exhibiting the relationships in terms of grades of similarity of the OTUs, employing tools such as i the Euclidean distance and ii nearest neighbor techniques. Thus taxonomic evidence is gathered so as to quantify the similarity for each pair of OTUs (pair-group method obtained from the basic data matrix and in this way the significant concept of spectrum of the OTUs is introduced, being based the same one on the state of their characters. A new taxonomic criterion is thereby formulated and a new approach to Computational Taxonomy is presented, that has been already employed with reference to Data Mining, when apply of Machine Learning techniques, in particular to the C4.5 algorithms, created by Quinlan, the degree of efficiency achieved by the TDIDT family's algorithms when are generating valid models of the data in classification problems with the Gain of Entropy through Maximum Entropy Principle. The Numeric Taxonomy aims to group operational taxonomic units in clusters (OTUs or taxons or taxa, using the denominated structure analysis by means of numeric methods. These clusters that constitute families are the purpose of this series of projects and they emerge of the structural analysis, of their phenotypical characteristic, exhibiting the relationships in terms of grades of similarity of the OTUs, employing tools such as i the Euclidean distance and ii nearest neighbor techniques. Thus taxonomic evidence is gathered so as to quantify the similarity for each pair of OTUs (pair-group method obtained from the basic data matrix and in this way the significant concept of spectrum of the OTUs is introduced, being based

  2. Artificial intelligence in nuclear power plants. Vol. 2

    International Nuclear Information System (INIS)

    The IAEA Specialists' Meeting on Artificial Intelligence in Nuclear Power Plants was arranged in Helsinki/Vantaa, Finland, on October 10-12, 1989, under auspices of the International Working Group of Nuclear Power Plant Control and Instrumentation of the International Atomic Energy Agency (IAEA/IWG NPPCI). Technical Research Centre of Finland together with Imatran Voima Oy and Teollisuuden Voima Oy answered for the practical arrangements of the meeting. 105 participants from 17 countries and 2 international organizations took part in the meeting and 58 papers were submitted for presentation. These papers gave a comprehensive picture of the recent status and further trends in applying the rapidly developing techniques of and safety in designing and using of nuclear power worldwide

  3. 13th International Conference on Distributed Computing and Artificial Intelligence

    CERN Document Server

    Silvestri, Marcello; González, Sara

    2016-01-01

    The special session Decision Economics (DECON) 2016 is a scientific forum by which to share ideas, projects, researches results, models and experiences associated with the complexity of behavioral decision processes aiming at explaining socio-economic phenomena. DECON 2016 held in the University of Seville, Spain, as part of the 13th International Conference on Distributed Computing and Artificial Intelligence (DCAI) 2016. In the tradition of Herbert A. Simon’s interdisciplinary legacy, this book dedicates itself to the interdisciplinary study of decision-making in the recognition that relevant decision-making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, small and international business, management, operations, and production. Decision-making issues are of crucial importance in economics. Not surprisingly, the study of decision-making has received a growing empirical research efforts in the applied economic literature over the last ...

  4. Applications of artificial intelligence to reactor and plant control

    International Nuclear Information System (INIS)

    Potential improvements in plant efficiency and reliability are often cited as reasons for developing and applying artificial intelligence (AI) techniques, principally expert systems, to the control and operation of nuclear reactors. Nevertheless, there have been few such applications and then mostly at the prototype level. Therefore, if AI techniques are to contribute to process control, methods must be identified by which rule-based and analytic approaches can be merged. This hypothesis is the basic premise of this article. Presented below are 1. a brief review of the human approach towards process control, 2. a discussion of the suitability of AI methodologies for the performance of control tasks, 3. examples of AI applications to both open- and closed-loop control, 4. an enumeration of unresolved issues associated with the use of AI for control, and 5. a discussion of the possible role of expert system techniques in process control. (orig./GL)

  5. Artificial intelligence for the CTA Observatory scheduler

    Science.gov (United States)

    Colomé, Josep; Colomer, Pau; Campreciós, Jordi; Coiffard, Thierry; de Oña, Emma; Pedaletti, Giovanna; Torres, Diego F.; Garcia-Piquer, Alvaro

    2014-08-01

    The Cherenkov Telescope Array (CTA) project will be the next generation ground-based very high energy gamma-ray instrument. The success of the precursor projects (i.e., HESS, MAGIC, VERITAS) motivated the construction of this large infrastructure that is included in the roadmap of the ESFRI projects since 2008. CTA is planned to start the construction phase in 2015 and will consist of two arrays of Cherenkov telescopes operated as a proposal-driven open observatory. Two sites are foreseen at the southern and northern hemispheres. The CTA observatory will handle several observation modes and will have to operate tens of telescopes with a highly efficient and reliable control. Thus, the CTA planning tool is a key element in the control layer for the optimization of the observatory time. The main purpose of the scheduler for CTA is the allocation of multiple tasks to one single array or to multiple sub-arrays of telescopes, while maximizing the scientific return of the facility and minimizing the operational costs. The scheduler considers long- and short-term varying conditions to optimize the prioritization of tasks. A short-term scheduler provides the system with the capability to adapt, in almost real-time, the selected task to the varying execution constraints (i.e., Targets of Opportunity, health or status of the system components, environment conditions). The scheduling procedure ensures that long-term planning decisions are correctly transferred to the short-term prioritization process for a suitable selection of the next task to execute on the array. In this contribution we present the constraints to CTA task scheduling that helped classifying it as a Flexible Job-Shop Problem case and finding its optimal solution based on Artificial Intelligence techniques. We describe the scheduler prototype that uses a Guarded Discrete Stochastic Neural Network (GDSN), for an easy representation of the possible long- and short-term planning solutions, and Constraint

  6. 26th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE)

    CERN Document Server

    Bosse, Tibor; Hindriks, Koen; Hoogendoorn, Mark; Jonker, Catholijn; Treur, Jan; Contemporary Challenges and Solutions in Applied Artificial Intelligence

    2013-01-01

      Since its origination in the mid-twentieth century, the area of Artificial Intelligence (AI) has undergone a number of developments. While the early interest in AI was mainly triggered by the desire to develop artifacts that show the same intelligent behavior as humans, nowadays scientists have realized that research in AI involves a multitude of separate challenges, besides the traditional goal to replicate human intelligence. In particular, recent history has pointed out that a variety of ‘intelligent’ computational techniques, part of which are inspired by human intelligence, may be successfully applied to solve all kinds of practical problems. This sub-area of AI, which has its main emphasis on applications of intelligent systems to solve real-life problems, is currently known under the term Applied Intelligence.   The objective of the International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE) is to promote and disseminate recent research ...

  7. A PHILOSOPHICAL APPROACH TO ARTIFICIAL INTELLIGENCE AND ISLAMIC VALUES

    Directory of Open Access Journals (Sweden)

    Ali Akbar Ziaee

    2012-02-01

    Full Text Available Artificial Intelligence has the potential to empower humans through enhanced learning and performance. But if this potential is to be realized and accepted, the ethical aspects as well as the technical must be addressed. Many engineers claim that AI will be smarter than human brains, including scientific creativity, general wisdom and social skills, so we must consider it an important factor for making decisions in our social life and especially in our Islamic societies. The most important challenges will be the quality of representing the Islamic values like piety, obedience, Halal and Haram, and etc in the form of semantics. In this paper, I want to emphasize on the role of Divine Islamic values in the application of AI and discuss it according to philosophy of AI and Islamic perspective.Keywords- Value, expert, Community Development, Artificial Intelligence, Superintelligence, Friendly Artificial Intelligence

  8. Artificial intelligence tool development and applications to nuclear power

    International Nuclear Information System (INIS)

    Two parallel efforts are being performed at the Electric Power Research Institute (EPRI) to help the electric utility industry take advantage of the expert system technology. The first effort is the development of expert system building tools, which are tailored to electric utility industry applications. The second effort is the development of expert system applications. These two efforts complement each other. The application development tests the tools and identifies additional tool capabilities that are required. The tool development helps define the applications that can be successfully developed. Artificial intelligence, as demonstrated by the developments described is being established as a credible technological tool for the electric utility industry. The challenge to transferring artificial intelligence technology and an understanding of its potential to the electric utility industry is to gain an understanding of the problems that reduce power plant performance and identify which can be successfully addressed using artificial intelligence

  9. Artificial intelligence and robot responsibilities: innovating beyond rights.

    Science.gov (United States)

    Ashrafian, Hutan

    2015-04-01

    The enduring innovations in artificial intelligence and robotics offer the promised capacity of computer consciousness, sentience and rationality. The development of these advanced technologies have been considered to merit rights, however these can only be ascribed in the context of commensurate responsibilities and duties. This represents the discernable next-step for evolution in this field. Addressing these needs requires attention to the philosophical perspectives of moral responsibility for artificial intelligence and robotics. A contrast to the moral status of animals may be considered. At a practical level, the attainment of responsibilities by artificial intelligence and robots can benefit from the established responsibilities and duties of human society, as their subsistence exists within this domain. These responsibilities can be further interpreted and crystalized through legal principles, many of which have been conserved from ancient Roman law. The ultimate and unified goal of stipulating these responsibilities resides through the advancement of mankind and the enduring preservation of the core tenets of humanity. PMID:24737482

  10. Distributed computing and artificial intelligence : 10th International Conference

    CERN Document Server

    Neves, José; Rodriguez, Juan; Santana, Juan; Gonzalez, Sara

    2013-01-01

    The International Symposium on Distributed Computing and Artificial Intelligence 2013 (DCAI 2013) is a forum in which applications of innovative techniques for solving complex problems are presented. Artificial intelligence is changing our society. Its application in distributed environments, such as the internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to mention only a few, is continuously increasing, becoming an element of high added value with social and economic potential, in industry, quality of life, and research. This conference is a stimulating and productive forum where the scientific community can work towards future cooperation in Distributed Computing and Artificial Intelligence areas. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. The exchange of ideas between scientists and technicians from both the academic and industry se...

  11. A review of European applications of artificial intelligence to space

    Science.gov (United States)

    Drummond, Mark (Editor); Stewart, Helen (Editor)

    1993-01-01

    The purpose is to describe the applications of Artificial Intelligence (AI) to the European Space program that are being developed or have been developed. The results of a study sponsored by the Artificial Intelligence Research and Development program of NASA's Office of Advanced Concepts and Technology (OACT) are described. The report is divided into two sections. The first consists of site reports, which are descriptions of the AI applications seen at each place visited. The second section consists of two summaries which synthesize the information in the site reports by organizing this information in two different ways. The first organizes the material in terms of the type of application, e.g., data analysis, planning and scheduling, and procedure management. The second organizes the material in terms of the component technologies of Artificial Intelligence which the applications used, e.g., knowledge based systems, model based reasoning, procedural reasoning, etc.

  12. 9th International conference on distributed computing and artificial intelligence

    CERN Document Server

    Santana, Juan; González, Sara; Molina, Jose; Bernardos, Ana; Rodríguez, Juan; DCAI 2012; International Symposium on Distributed Computing and Artificial Intelligence 2012

    2012-01-01

    The International Symposium on Distributed Computing and Artificial Intelligence 2012 (DCAI 2012) is a stimulating and productive forum where the scientific community can work towards future cooperation in Distributed Computing and Artificial Intelligence areas. This conference is a forum in which  applications of innovative techniques for solving complex problems will be presented. Artificial intelligence is changing our society. Its application in distributed environments, such as the internet, electronic commerce, environment monitoring, mobile communications, wireless devices, distributed computing, to mention only a few, is continuously increasing, becoming an element of high added value with social and economic potential, in industry, quality of life, and research. These technologies are changing constantly as a result of the large research and technical effort being undertaken in both universities and businesses. The exchange of ideas between scientists and technicians from both the academic and indus...

  13. Survey of artificial intelligence methods for detection and identification of component faults in nuclear power plants

    International Nuclear Information System (INIS)

    A comprehensive survey of computer-based systems that apply artificial intelligence methods to detect and identify component faults in nuclear power plants is presented. Classification criteria are established that categorize artificial intelligence diagnostic systems according to the types of computing approaches used (e.g., computing tools, computer languages, and shell and simulation programs), the types of methodologies employed (e.g., types of knowledge, reasoning and inference mechanisms, and diagnostic approach), and the scope of the system. The major issues of process diagnostics and computer-based diagnostic systems are identified and cross-correlated with the various categories used for classification. Ninety-five publications are reviewed

  14. Bionics: A Step toward Artificial Intelligence Systems

    Science.gov (United States)

    Dutton, Robert E.

    1970-01-01

    Recent developments and future prospects in the borrowing of biological principles to build problem solving relationships between human intelligence and the information storage and manipulation capacities of computers. Twenty-one references. (LY)

  15. The Emergence of Artificial Intelligence: Learning to Learn

    OpenAIRE

    de Bock, Peter

    1985-01-01

    The classical approach to the acquisition of knowledge and reason in artificial intelligence is to program the facts and rules into the machine. Unfortunately, the amount of time required to program the equivalent of human intelligence is prohibitively large. An alternative approach allows an automaton to learn to solve problems through iterative trial-and-error interaction with its environment, much as humans do. To solve a problem posed by the environment, the automaton generates a sequence...

  16. Distinct Neurocognitive Strategies for Comprehensions of Human and Artificial Intelligence

    OpenAIRE

    Ge, Jianqiao; Han, Shihui

    2008-01-01

    Although humans have inevitably interacted with both human and artificial intelligence in real life situations, it is unknown whether the human brain engages homologous neurocognitive strategies to cope with both forms of intelligence. To investigate this, we scanned subjects, using functional MRI, while they inferred the reasoning processes conducted by human agents or by computers. We found that the inference of reasoning processes conducted by human agents but not by computers induced incr...

  17. Fifth Conference on Artificial Intelligence for Space Applications

    Science.gov (United States)

    Odell, Steve L. (Compiler)

    1990-01-01

    The Fifth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: automation for Space Station; intelligent control, testing, and fault diagnosis; robotics and vision; planning and scheduling; simulation, modeling, and tutoring; development tools and automatic programming; knowledge representation and acquisition; and knowledge base/data base integration.

  18. Cryptic Mining in Light of Artificial Intelligence

    OpenAIRE

    Shaligram Prajapat; Aditi Thakur; Kajol Maheshwari; Ramjeevan Singh Thakur

    2015-01-01

    “The analysis of cryptic text is hard problem”, and there is no fixed algorithm for generating plain-text from cipher text. Human brains do this intelligently. The intelligent cryptic analysis process needs learning algorithms, co-operative effort of cryptanalyst and mechanism of knowledge based inference engine. This information of knowledge base will be useful for mining data(plain-text, key or cipher text plain-text relationships), classification of cipher text based on enciphering algorit...

  19. Distributed Computing and Artificial Intelligence, 12th International Conference

    CERN Document Server

    Malluhi, Qutaibah; Gonzalez, Sara; Bocewicz, Grzegorz; Bucciarelli, Edgardo; Giulioni, Gianfranco; Iqba, Farkhund

    2015-01-01

    The 12th International Symposium on Distributed Computing and Artificial Intelligence 2015 (DCAI 2015) is a forum to present applications of innovative techniques for studying and solving complex problems. The exchange of ideas between scientists and technicians from both the academic and industrial sector is essential to facilitate the development of systems that can meet the ever-increasing demands of today’s society. The present edition brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This symposium is organized by the Osaka Institute of Technology, Qatar University and the University of Salamanca.

  20. Systems with artificial intelligence in nuclear power plant operation

    International Nuclear Information System (INIS)

    The authors first summarize some developments made by GRS teams which can be regarded as the precursors of systems with artificial intelligence, and explain the basic characteristics of artificial intelligence, referring in particular to possible applications in nuclear engineering. The systems described are arranged in four groups according to applicability as follows: plant diagnosis and failure analysis, information systems and operating systems, control systems, assessment and decision aids. The working principle of the systems is explained by some examples giving details of the database and the interference processes. (orig./DG)

  1. Training Software in Artificial-Intelligence Computing Techniques

    Science.gov (United States)

    Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

    2005-01-01

    The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

  2. Artificial Intelligence Needs More Emphasis on Basic Research: President's Quarterly Message

    OpenAIRE

    McCarthy, John

    1983-01-01

    Too few people are doing basic research in AI relative to the number working on applications. The ratio of basic/applied is less in AI than in the older sciences and than in computer science generally. This is unfortunate, because reaching human level artificial intelligence will require fundamental conceptual advances.

  3. Prediction of shipboard electromagnetic interference (EMI) problems using artificial intelligence (AI) technology

    Science.gov (United States)

    Swanson, David J.

    1990-01-01

    The electromagnetic interference prediction problem is characteristically ill-defined and complicated. Severe EMI problems are prevalent throughout the U.S. Navy, causing both expected and unexpected impacts on the operational performance of electronic combat systems onboard ships. This paper focuses on applying artificial intelligence (AI) technology to the prediction of ship related electromagnetic interference (EMI) problems.

  4. The present status of artificial intelligence for nuclear power plants

    International Nuclear Information System (INIS)

    JNC researches the development of distributed intelligence systems at autonomous plants and intelligent support system at nuclear power plant. This report describes the present status of artificial intelligence (AI) technologies for this research. The following are represented in this report: present research study for AI, Implementation of AI system and application of AI technologies in the field of industries, requirement for AI by industries, problems of social acceptance for AI. A development of AI systems has to be motivated both by current status of AI and requirement for AI. Furthermore a problem of social acceptance for AI technologies has to be solved for using AI systems in society. (author)

  5. SOME PARADIGMS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL COMPUTER SYSTEMS

    Directory of Open Access Journals (Sweden)

    Jerzy Balicki

    2015-12-01

    Full Text Available The article discusses some paradigms of artificial intelligence in the context of their applications in computer financial systems. The proposed approach has a significant po-tential to increase the competitiveness of enterprises, including financial institutions. However, it requires the effective use of supercomputers, grids and cloud computing. A reference is made to the computing environment for Bitcoin. In addition, we characterized genetic programming and artificial neural networks to prepare investment strategies on the stock exchange market.

  6. A Multidisciplinary Artificial Intelligence Model of an Affective Robot

    OpenAIRE

    Hooman Aghaebrahimi Samani; Elham Saadatian

    2012-01-01

    A multidisciplinary approach to a novel artificial intelligence system for an affective robot is presented in this paper. The general objective of the system is to develop a robotic system which strives to achieve a high level of emotional bond between humans and robot by exploring human love. Such a relationship is a contingent process of attraction, affection and attachment from humans towards robots, and the belief of the vice versa from robots to humans. The advanced artificial intelli...

  7. Neuro-Based Artificial Intelligence Model for Loan Decisions

    OpenAIRE

    Shorouq F. Eletter; Saad G. Yaseen; Ghaleb A. Elrefae

    2010-01-01

    Problem statement: Despite the increase in consumer loans defaults and competition in the banking market, most of the Jordanian commercial banks are reluctant to use artificial intelligence software systems for supporting loan decisions. Approach: This study developed a proposed model that identifies artificial neural network as an enabling tool for evaluating credit applications to support loan decisions in the Jordanian Commercial banks. A multi-layer feed-forward neural network with backpr...

  8. Artificial Life of Soybean Plant Growth Modeling Using Intelligence Approaches

    OpenAIRE

    Atris Suyantohadi; Mochamad Hariadi; Mauridhi Hery Purnomo

    2010-01-01

    The natural process on plant growth system has a complex system and it has could be developed on characteristic studied using intelligent approaches conducting with artificial life system. The approaches on examining the natural process on soybean (Glycine Max L.Merr) plant growth have been analyzed and synthesized in these research through modeling using Artificial Neural Network (ANN) and Lindenmayer System (L-System) methods. Research aimed to design and to visualize plant growth modeling...

  9. Inteligência artificial aplicada à Zootecnia Artificial intelligence in Animal Science

    Directory of Open Access Journals (Sweden)

    Ernane José Xavier Costa

    2009-07-01

    Full Text Available Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11 neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja concretizado. No entanto, algumas técnicas como Redes neurais artificiais e lógica fuzzy tem mostrado efetivas para resolver problemas complexos usando a heurística dos sistemas biológicos. Recentemente o numero de aplicação dos métodos da IA em sistemas zootécnicos tem aumentado significativamente. O objetivo deste artigo é explicar os princípios básicos da resolução de problemas usando heurística e demonstrar como a IA pode ser aplicada para construir um sistema especialista para resolver problemas na área de zootecnia.Biological systems are surprising flexible in processing information in the real world. Some biological organisms have a central unit processing named brain. The human's brain, consisting of 10(11 neurons, realizes intelligent information processing based on exact and commonsense reasoning. Artificial intelligence (AI has been trying to implement biological intelligence in computers in various ways, but is still far from real one. Therefore, there are approaches like Symbolic AI, Artificial Neural Network and Fuzzy system that partially successful in implementing heuristic from biological intelligence. Many recent applications of these approaches show an increased interest in animal science research. The main goal of this article is to explain the principles of heuristic problem-solving approach and to demonstrate how they can be applied to building knowledge-based systems for animal science problem solving.

  10. Space Communications Artificial Intelligence for Link Evaluation Terminal (SCAILET)

    Science.gov (United States)

    Shahidi, Anoosh

    1991-01-01

    A software application to assis end-users of the Link Evaluation Terminal (LET) for satellite communication is being developed. This software application incorporates artificial intelligence (AI) techniques and will be deployed as an interface to LET. The high burst rate (HBR) LET provides 30 GHz transmitting/20 GHz receiving, 220/110 Mbps capability for wideband communications technology experiments with the Advanced Communications Technology Satellite (ACTS). The HBR LET and ACTS are being developed at the NASA Lewis Research Center. The HBR LET can monitor and evaluate the integrity of the HBR communications uplink and downlink to the ACTS satellite. The uplink HBR transmission is performed by bursting the bit-pattern as a modulated signal to the satellite. By comparing the transmitted bit pattern with the received bit pattern, HBR LET can determine the bit error rate BER) under various atmospheric conditions. An algorithm for power augmentation is applied to enhance the system's BER performance at reduced signal strength caused by adverse conditions. Programming scripts, defined by the design engineer, set up the HBR LET terminal by programming subsystem devices through IEEE488 interfaces. However, the scripts are difficult to use, require a steep learning curve, are cryptic, and are hard to maintain. The combination of the learning curve and the complexities involved with editing the script files may discourage end-users from utilizing the full capabilities of the HBR LET system. An intelligent assistant component of SCAILET that addresses critical end-user needs in the programming of the HBR LET system as anticipated by its developers is described. A close look is taken at the various steps involved in writing ECM software for a C&P, computer and at how the intelligent assistant improves the HBR LET system and enhances the end-user's ability to perform the experiments.

  11. 25th International Conference on Industrial, Engineering & Other Applica- tions of Applied Intelligent Systems (IEA/AIE 2012)

    CERN Document Server

    Jiang, He; Ali, Moonis; Li, Mingchu; Modern Advances in Intelligent Systems and Tools

    2012-01-01

    Intelligent systems provide a platform to connect the research in artificial intelligence to real-world problem solving applications. Various intelligent systems have been developed to face real-world applications. This book discusses the modern advances in intelligent systems and the tools in applied artificial intelligence. It consists of twenty-three chapters authored by participants of the 25th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2012) which was held in Dalian, China. This book is divided into six parts, including Applied Intelligence, Cognitive Computing and Affective Computing, Data Mining and Intelligent Systems, Decision Support Systems, Machine Learning, and Natural Language Processing. Each part includes three to five chapters. In these chapters, many approaches, applications, restrictions, and discussions are presented. The material of each chapter is self-contained and was reviewed by at least two anonymous referees t...

  12. A Multidisciplinary Artificial Intelligence Model of an Affective Robot

    Directory of Open Access Journals (Sweden)

    Hooman Aghaebrahimi Samani

    2012-03-01

    The advanced artificial intelligence of the system includes three modules, namely Probabilistic Love Assembly (PLA, based on the psychology of love, Artificial Endocrine System (AES, based on the physiology of love, and Affective State Transition (AST, based on emotions. The PLA module employs a Bayesian network to incorporate psychological parameters of affection in the robot. The AES module employs artificial emotional and biological hormones via a Dynamic Bayesian Network (DBN. The AST module uses a novel transition method for handling affective states of the robot. These three modules work together to manage emotional behaviours of the robot.

  13. 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.

  14. 50 years of artificial intelligence: a neuronal approach

    OpenAIRE

    Fernández Caballero, Antonio; Deco, Gustavo; Mira Mira, José

    2008-01-01

    Recently, the 50th anniversary of the birth of Artificial Intelligence (AI) has been celebrated worldwide, and about 65 years ago (1943) its foundational works on Biocybernetics and Bionics were published due to movements led by McCulloch and Pitts and Wiener.

  15. Traditional and Modern Artificial Intelligence Explores Ecological Data

    Czech Academy of Sciences Publication Activity Database

    Holeňa, Martin

    Helsinki : Finnish Artificial Intelligence Society, 2000 - (Hyötyniemi, H.), s. 53-60 ISBN 951-22-5129-9. [STeP 2000. Helsinki (FI), 00.08.2000-00.08.2000] R&D Projects: GA AV ČR IAB2030007 Institutional research plan: AV0Z1030915 Subject RIV: BA - General Mathematics

  16. An Artificial Intelligence Approach to Transient Stability Assessment

    OpenAIRE

    Akella, Vijay Ahaskar; Khincha, HP; Kumar, Sreerama R

    1991-01-01

    An artificial intelligence approach to online transient stability assessment is briefly discussed, and some crucial requirements for this algorithm are identified. Solutions to these are proposed. Some new attributes are suggested so as to reflect machine dynamics and changes in the network. Also a new representative learning set algorithm has been developed.

  17. Evolution and Revolution in Artificial Intelligence in Education

    Science.gov (United States)

    Roll, Ido; Wylie, Ruth

    2016-01-01

    The field of Artificial Intelligence in Education (AIED) has undergone significant developments over the last twenty-five years. As we reflect on our past and shape our future, we ask two main questions: What are our major strengths? And, what new opportunities lay on the horizon? We analyse 47 papers from three years in the history of the…

  18. Artificial Intelligence: Is the Future Now for A.I.?

    Science.gov (United States)

    Ramaswami, Rama

    2009-01-01

    In education, artificial intelligence (AI) has not made much headway. In the one area where it would seem poised to lend the most benefit--assessment--the reliance on standardized tests, intensified by the demands of the No Child Left Behind Act of 2001, which holds schools accountable for whether students pass statewide exams, precludes its use.…

  19. Systems in Science: Modeling Using Three Artificial Intelligence Concepts.

    Science.gov (United States)

    Sunal, Cynthia Szymanski; Karr, Charles L.; Smith, Coralee; Sunal, Dennis W.

    2003-01-01

    Describes an interdisciplinary course focusing on modeling scientific systems. Investigates elementary education majors' applications of three artificial intelligence concepts used in modeling scientific systems before and after the course. Reveals a great increase in understanding of concepts presented but inconsistent application. (Author/KHR)

  20. The 1992 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Rash, James L. (Editor)

    1992-01-01

    The purpose of this conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers fall into the following areas: planning and scheduling, control, fault monitoring/diagnosis and recovery, information management, tools, neural networks, and miscellaneous applications.

  1. An Artificial Intelligence-Based Distance Education System: Artimat

    Science.gov (United States)

    Nabiyev, Vasif; Karal, Hasan; Arslan, Selahattin; Erumit, Ali Kursat; Cebi, Ayca

    2013-01-01

    The purpose of this study is to evaluate the artificial intelligence-based distance education system called ARTIMAT, which has been prepared in order to improve mathematical problem solving skills of the students, in terms of conceptual proficiency and ease of use with the opinions of teachers and students. The implementation has been performed…

  2. Research Priorities for Robust and Beneficial Artificial Intelligence

    OpenAIRE

    Russell, Stuart; University of California, Berkeley; Dewey, Daniel; Oxford University; Tegmark, Max; Massachusetts Institute of Technology

    2016-01-01

    Success in the quest for artificial intelligence has the potential to bring unprecedented benefits to humanity, and it is therefore worthwhile to investigate how to maximize these benefits while avoiding potential pitfalls. This article gives numerous examples (which should by no means be construed as an exhaustive list) of such worthwhile research aimed at ensuring that AI remains robust and beneficial.

  3. Artificial Intelligence: Realizing the Ultimate Promises of Computing

    OpenAIRE

    Waltz, David L.

    1997-01-01

    Artificial intelligence (AI) is the key technology in many of today's novel applications, ranging from banking systems that detect attempted credit card fraud, to telephone systems that understand speech, to software systems that notice when you're having problems and offer appropriate advice. These technologies would not exist today without the sustained federal support of fundamental AI research over the past three decades.

  4. Artificial Intelligence and the High School Computer Curriculum.

    Science.gov (United States)

    Dillon, Richard W.

    1993-01-01

    Describes a four-part curriculum that can serve as a model for incorporating artificial intelligence (AI) into the high school computer curriculum. The model includes examining questions fundamental to AI, creating and designing an expert system, language processing, and creating programs that integrate machine vision with robotics and…

  5. Artificial intelligence system for technical diagnostics of photomasks

    Directory of Open Access Journals (Sweden)

    Kozin A. A.

    2012-02-01

    Full Text Available The developed artificial intelligence system has a high level of noise immunity, so its inclusion in the hardware and software for technical diagnostics of photomasks will reduce the hardware requirements for its execution, and thereby reduce the cost of the complex. As a result it will allow to make a small-scale production profitable.

  6. The future of artificial intelligence in nuclear plant maintenance

    International Nuclear Information System (INIS)

    Robots with vision and force sensing capability, performing tasks under computer control, will offer new opportunities to reduce human exposure to radiation. Such machines do not yet exist and even simple maintenance tasks challenge current robot technology. Recently increased priority for research on artificial intelligence and fifth generation computer technology is likely to bring useful maintenance robots closer to reality

  7. Social Studies and Emerging Paradigms: Artificial Intelligence and Consciousness Education.

    Science.gov (United States)

    Braun, Joseph A., Jr.

    1987-01-01

    Asks three questions: (1) Are machines capable of thinking as people do? (2) How is the thinking of computers similar and different from human thinking? and (3) What exactly is thinking? Examines research in artificial intelligence. Describes the theory and research of consciousness education and discusses an emerging paradigm for human thinking…

  8. Artificial intelligence system for technical diagnostics of photomasks

    OpenAIRE

    Kozin A. A.; Kozina Yu. Yu.

    2012-01-01

    The developed artificial intelligence system has a high level of noise immunity, so its inclusion in the hardware and software for technical diagnostics of photomasks will reduce the hardware requirements for its execution, and thereby reduce the cost of the complex. As a result it will allow to make a small-scale production profitable.

  9. Artificial Intelligence in Business: Technocrat Jargon or Quantum Leap?

    Science.gov (United States)

    Burford, Anna M.; Wilson, Harold O.

    This paper addresses the characteristics and applications of artificial intelligence (AI) as a subsection of computer science, and briefly describes the most common types of AI programs: expert systems, natural language, and neural networks. Following a brief presentation of the historical background, the discussion turns to an explanation of how…

  10. Artificial intelligence - New tools for aerospace project managers

    Science.gov (United States)

    Moja, D. C.

    1985-01-01

    Artificial Intelligence (AI) is currently being used for business-oriented, money-making applications, such as medical diagnosis, computer system configuration, and geological exploration. The present paper has the objective to assess new AI tools and techniques which will be available to assist aerospace managers in the accomplishment of their tasks. A study conducted by Brown and Cheeseman (1983) indicates that AI will be employed in all traditional management areas, taking into account goal setting, decision making, policy formulation, evaluation, planning, budgeting, auditing, personnel management, training, legal affairs, and procurement. Artificial intelligence/expert systems are discussed, giving attention to the three primary areas concerned with intelligent robots, natural language interfaces, and expert systems. Aspects of information retrieval are also considered along with the decision support system, and expert systems for project planning and scheduling.

  11. Intelligent instrumentation applied in environment management

    Science.gov (United States)

    Magheti, Mihnea I.; Walsh, Patrick; Delassus, Patrick

    2005-06-01

    The use of information and communications technology in environment management and research has witnessed a renaissance in recent years. From optical sensor technology, expert systems, GIS and communications technologies to computer aided harvesting and yield prediction, these systems are increasable used for applications developing in the management sector of natural resources and biodiversity. This paper presents an environmental decision support system, used to monitor biodiversity and present a risk rating for the invasion of pests into the particular systems being examined. This system will utilise expert mobile technology coupled with artificial intelligence and predictive modelling, and will emphasize the potential for expansion into many areas of intelligent remote sensing and computer aided decision-making for environment management or certification. Monitoring and prediction in natural systems, harnessing the potential of computing and communication technologies is an emerging technology within the area of environmental management. This research will lead to the initiation of a hardware and software multi tier decision support system for environment management allowing an evaluation of areas for biodiversity or areas at risk from invasive species, based upon environmental factors/systems.

  12. Computer-aided diagnosis and artificial intelligence in clinical imaging.

    Science.gov (United States)

    Shiraishi, Junji; Li, Qiang; Appelbaum, Daniel; Doi, Kunio

    2011-11-01

    Computer-aided diagnosis (CAD) is rapidly entering the radiology mainstream. It has already become a part of the routine clinical work for the detection of breast cancer with mammograms. The computer output is used as a "second opinion" in assisting radiologists' image interpretations. The computer algorithm generally consists of several steps that may include image processing, image feature analysis, and data classification via the use of tools such as artificial neural networks (ANN). In this article, we will explore these and other current processes that have come to be referred to as "artificial intelligence." One element of CAD, temporal subtraction, has been applied for enhancing interval changes and for suppressing unchanged structures (eg, normal structures) between 2 successive radiologic images. To reduce misregistration artifacts on the temporal subtraction images, a nonlinear image warping technique for matching the previous image to the current one has been developed. Development of the temporal subtraction method originated with chest radiographs, with the method subsequently being applied to chest computed tomography (CT) and nuclear medicine bone scans. The usefulness of the temporal subtraction method for bone scans was demonstrated by an observer study in which reading times and diagnostic accuracy improved significantly. An additional prospective clinical study verified that the temporal subtraction image could be used as a "second opinion" by radiologists with negligible detrimental effects. ANN was first used in 1990 for computerized differential diagnosis of interstitial lung diseases in CAD. Since then, ANN has been widely used in CAD schemes for the detection and diagnosis of various diseases in different imaging modalities, including the differential diagnosis of lung nodules and interstitial lung diseases in chest radiography, CT, and position emission tomography/CT. It is likely that CAD will be integrated into picture archiving and

  13. Intelligent process control operator aid -- An artificial intelligence approach

    International Nuclear Information System (INIS)

    This paper describes an approach for designing intelligent process and power plant control operator aids. It is argued that one of the key aspects of an intelligent operator aid is the capability for dynamic procedure synthesis with incomplete definition of initial state, unknown goal states, and the dynamic world situation. The dynamic world state is used to determine the goal, select appropriate plan steps from prespecified procedures to achieve the goal, control the execution of the synthesized plan, and provide for dynamic recovery from failure often using a goal hierarchy. The dynamic synthesis of a plan requires integration of various problems solving capabilities such as plan generation, plan synthesis, plan modification, and failure recovery from a plan. The programming language for implementing the DPS framework provides a convenient tool for developing applications. An application of the DPS approach to a Nuclear Power Plant emergency procedure synthesis is also described. Initial test results indicate that the approach is successful in dynamically synthesizing the procedures. The authors realize that the DPS framework is not a solution for all control tasks. However, many existing process and plant control problems satisfy the requirements discussed in the paper and should be able to benefit from the framework described

  14. Autonomous operations through onboard artificial intelligence

    Science.gov (United States)

    Sherwood, R. L.; Chien, S.; Castano, R.; Rabideau, G.

    2002-01-01

    The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.

  15. Artificial intelligence in nuclear reactor operation

    International Nuclear Information System (INIS)

    Assessment of four real fuzzy control applications at the MIT research reactor in the US, the FUGEN heavy water reactor in Japan, the BR1 research reactor in Belgium, and a TRIGA Mark III reactor in Mexico will be examined through a SWOT analysis (strengths, weakness, opportunities, and threats). Special attention will be paid to the current cooperation between the Belgian Nuclear Research Centre (SCK·CEN) and the Mexican Nuclear Centre (ININ) on AI-based intelligent control for nuclear reactor operation under the partial support of the National Council for Science and Technology of Mexico (CONACYT). (authors)

  16. Artificial organic networks artificial intelligence based on carbon networks

    CERN Document Server

    Ponce-Espinosa, Hiram; Molina, Arturo

    2014-01-01

    This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: ·        approximation; ·        inference; ·        clustering; ·        control; ·        class...

  17. Air Quality Forecasting through Different Statistical and Artificial Intelligence Techniques

    Science.gov (United States)

    Mishra, D.; Goyal, P.

    2014-12-01

    Urban air pollution forecasting has emerged as an acute problem in recent years because there are sever environmental degradation due to increase in harmful air pollutants in the ambient atmosphere. In this study, there are different types of statistical as well as artificial intelligence techniques are used for forecasting and analysis of air pollution over Delhi urban area. These techniques are principle component analysis (PCA), multiple linear regression (MLR) and artificial neural network (ANN) and the forecasting are observed in good agreement with the observed concentrations through Central Pollution Control Board (CPCB) at different locations in Delhi. But such methods suffers from disadvantages like they provide limited accuracy as they are unable to predict the extreme points i.e. the pollution maximum and minimum cut-offs cannot be determined using such approach. Also, such methods are inefficient approach for better output forecasting. But with the advancement in technology and research, an alternative to the above traditional methods has been proposed i.e. the coupling of statistical techniques with artificial Intelligence (AI) can be used for forecasting purposes. The coupling of PCA, ANN and fuzzy logic is used for forecasting of air pollutant over Delhi urban area. The statistical measures e.g., correlation coefficient (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA) of the proposed model are observed in better agreement with the all other models. Hence, the coupling of statistical and artificial intelligence can be use for the forecasting of air pollutant over urban area.

  18. Philosophy and Theory of Artificial Intelligence

    CERN Document Server

    2013-01-01

    Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we s...

  19. Learning comunication strategies for distributed artificial intelligence

    Science.gov (United States)

    Kinney, Michael; Tsatsoulis, Costas

    1992-08-01

    We present a methodology that allows collections of intelligent system to automatically learn communication strategies, so that they can exchange information and coordinate their problem solving activity. In our methodology communication between agents is determined by the agents themselves, which consider the progress of their individual problem solving activities compared to the communication needs of their surrounding agents. Through learning, communication lines between agents might be established or disconnected, communication frequencies modified, and the system can also react to dynamic changes in the environment that might force agents to cease to exist or to be added. We have established dynamic, quantitative measures of the usefulness of a fact, the cost of a fact, the work load of an agent, and the selfishness of an agent (a measure indicating an agent's preference between transmitting information versus performing individual problem solving), and use these values to adapt the communication between intelligent agents. In this paper we present the theoretical foundations of our work together with experimental results and performance statistics of networks of agents involved in cooperative problem solving activities.

  20. Cryptic Mining in Light of Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Shaligram Prajapat

    2015-08-01

    Full Text Available “The analysis of cryptic text is hard problem”, and there is no fixed algorithm for generating plain-text from cipher text. Human brains do this intelligently. The intelligent cryptic analysis process needs learning algorithms, co-operative effort of cryptanalyst and mechanism of knowledge based inference engine. This information of knowledge base will be useful for mining data(plain-text, key or cipher text plain-text relationships, classification of cipher text based on enciphering algorithms, key length or any other desirable parameters, clustering of cipher text based on similarity and extracting association rules for identifying weaknesses of cryptic algorithms. This categorization will be useful for placing given cipher text into a specific category or solving difficult level of cipher text-plain text conversion process. This paper elucidates cipher text-plain text process first than utilizes it to create a framework for AI-enabled-Cryptanalysis system. The process demonstrated in this paper attempts to analyze captured cipher from scratch. The system design elements presented in the paper gives all hints and guidelines for development of AI enabled Cryptic analysis tool.

  1. An application of artificial intelligence theory to reconfigurable flight control

    Science.gov (United States)

    Handelman, David A.

    1987-01-01

    Artificial intelligence techniques were used along with statistical hpyothesis testing and modern control theory, to help the pilot cope with the issues of information, knowledge, and capability in the event of a failure. An intelligent flight control system is being developed which utilizes knowledge of cause and effect relationships between all aircraft components. It will screen the information available to the pilots, supplement his knowledge, and most importantly, utilize the remaining flight capability of the aircraft following a failure. The list of failure types the control system will accommodate includes sensor failures, actuator failures, and structural failures.

  2. Artificial intelligence: the future in nuclear plant maintenance

    International Nuclear Information System (INIS)

    The role of robotics and remote handling equipment in future nuclear power plant maintenance activities is discussed in the context of artificial intelligence applications. Special requirements manipulators, control systems, and man-machine interfaces for nuclear applications are noted. Tasks might include inspection with cameras, eddy current probes, and leak detectors; the collection of material samples; radiation monitoring; and the disassembly, repair and reassembly of a variety of system components. A robot with vision and force sensing and an intelligent control system that can access a knowledge base is schematically described. Recent advances in image interpretation systems are also discussed

  3. Information Processing in Cognition Process and New Artificial Intelligent Systems

    Science.gov (United States)

    Zheng, Nanning; Xue, Jianru

    In this chapter, we discuss, in depth, visual information processing and a new artificial intelligent (AI) system that is based upon cognitive mechanisms. The relationship between a general model of intelligent systems and cognitive mechanisms is described, and in particular we explore visual information processing with selective attention. We also discuss a methodology for studying the new AI system and propose some important basic research issues that have emerged in the intersecting fields of cognitive science and information science. To this end, a new scheme for associative memory and a new architecture for an AI system with attractors of chaos are addressed.

  4. Application of artificial intelligence methods for prediction of steel mechanical properties

    Directory of Open Access Journals (Sweden)

    Z. Jančíková

    2008-10-01

    Full Text Available The target of the contribution is to outline possibilities of applying artificial neural networks for the prediction of mechanical steel properties after heat treatment and to judge their perspective use in this field. The achieved models enable the prediction of final mechanical material properties on the basis of decisive parameters influencing these properties. By applying artificial intelligence methods in combination with mathematic-physical analysis methods it will be possible to create facilities for designing a system of the continuous rationalization of existing and also newly developing industrial technologies.

  5. Providing Language Instructor with Artificial Intelligence Assistant

    Directory of Open Access Journals (Sweden)

    K. Pietroszek

    2007-12-01

    Full Text Available Abstract—This paper presents the preliminary results ofdeveloping HAL for CALL, an artificial intelligenceassistant for language instructor. The assistant consists of achatbot, an avatar (a three-dimensional visualization of thechatbot, a voice (text-to-speech engine interface andinterfaces to external sources of language knowledge. Sometechniques used in adapting freely available chatbot for theneed of a language learning system are presented.Integration of HAL with Second Life virtual world isproposed. We will discuss technical challenges and possiblefuture work directions.

  6. Nuclear fuel pellet quality control using artificial intelligence techniques

    Science.gov (United States)

    Song, Xiaolong

    Inspection of nuclear fuel pellets is a complex and time-consuming process. At present, quality control in the fuel fabrication field mainly relies on human manual inspection, which is essentially a judgement call. Considering the high quality requirement of fuel pellets in the nuclear industry, pellet inspection systems must have a high accuracy rate in addition to a high inspection speed. Furthermore, any inspection process should have a low rejection rate of good pellets from the manufacturer point of view. It is very difficult to use traditional techniques, such as simple image comparison, to adequately perform the inspection process of the nuclear fuel pellet. Knowledge-based inspection and a defect-recognition algorithm, which maps the human inspection knowledge, is more robust and effective. A novel method is introduced here for pellet image processing. Three artificial intelligence techniques are studied and applied for fuel pellet inspection in this research. They are an artificial neural network, fuzzy logic, and the decision tree method. A dynamic reference model is located on each input fuel pellet image. Then, those pixels that belong to the abnormal defect are enhanced with high speed and high accuracy. Next, the content-based features for the defect are extracted from those abno1mal pixels and used in the inspection algorithm. Finally, an automated inspection prototype system---Visual Inspection Studio---which combines machine vision and these three AI techniques, is developed and tested. The experimental results indicate a very successful system with a high potential for on-line automatic inspection process.

  7. A Survey on Using Artificial Intelligence Techniques in the Software Development Process

    OpenAIRE

    K. Hema Shankari; Dr. R.Thirumalaiselvi

    2014-01-01

    Software engineering and artificial intelligence are the two important fields of the computer science. Artificial Intelligence is about making machines intelligent, while Software engineering is knowledge –intensive activity, requiring extensive knowledge of the application domain and of the target software itself. This study intends to review the techniques developed in artificial intelligence from the standpoint of their application in software engineering. The goal of this rese...

  8. Application of Artificial Intelligence and Data Mining Techniques to Financial Markets

    OpenAIRE

    Katarína Hilovska; Peter Koncz

    2012-01-01

    The aim of artificial intelligence is to discover mechanisms of adaptation in a changing environment with utilisation of intelligence, for instance in the ability to exclude unlikely solutions. Artificial intelligence methods have extensive application in different fields such as medicine, games, transportation, or heavy industry. This paper deals with interdisciplinary issues – interconnection of artificial intelligence and finance. The paper briefly describes techniques of data mining, expe...

  9. Artificial Intelligent Controller for a DC Motor

    Science.gov (United States)

    Delavari, Hadi; Ranjbar Noiey, Abolzafl; Minagar, Sara

    The Speed and position control of DC motors is addressed in this paper. An optimal intelligent control scheme is proposed for the system. Preliminary a PID controller is designed using Genetic Algorithms (GA). The proposed controller is implemented by using optimal integral state feedback control with GA and Kalman filter. In the proposed scheme, performance depends on choosing weighting matrices Q and R in the cost function, and accordingly GA is used to find these proper weighting matrices. In order to reduce the control performance degradation due to system parameters variation, a Kalman filter is gained. The performance of the proposed technique (ISF) is compared with PID controller. Computer simulation validates the effectiveness of the proposed scheme even in presence of uncertainties.

  10. Artificial Intelligence based technique for BTS placement

    International Nuclear Information System (INIS)

    The increase of the base transceiver station (BTS) in most urban areas can be traced to the drive by network providers to meet demand for coverage and capacity. In traditional network planning, the final decision of BTS placement is taken by a team of radio planners, this decision is not fool proof against regulatory requirements. In this paper, an intelligent based algorithm for optimal BTS site placement has been proposed. The proposed technique takes into consideration neighbour and regulation considerations objectively while determining cell site. The application will lead to a quantitatively unbiased evaluated decision making process in BTS placement. An experimental data of a 2km by 3km territory was simulated for testing the new algorithm, results obtained show a 100% performance of the neighbour constrained algorithm in BTS placement optimization. Results on the application of GA with neighbourhood constraint indicate that the choices of location can be unbiased and optimization of facility placement for network design can be carried out

  11. ARTIFICIAL INTELLIGENCE EFFECTIVENESS IN JOB SHOP ENVIRONMENTS

    Directory of Open Access Journals (Sweden)

    OMAR CASTRILLON

    2011-01-01

    Full Text Available El objetivo del presente trabajo, es definir una nueva metodología la cual permita comparar la efectividad de algunas de las principales técnicas de inteligencia artificial (aleatorias, búsqueda tabú, minería de datos, algoritmos evolutivos. Esta metodología es aplicada en los procesos de secuenciación de la producción en ambientes job shop, en un problema con N pedidos y M máquinas, donde cada uno de los pedidos debe pasar por todas las máquinas sin importar el orden. Estas técnicas son medidas en las variables tiempo total de proceso, tiempo total muerto y porcentaje de utilización de las máquinas. Inicialmente, una revisión teórica fue realizada, esta muestra la utilidad y efectividad de la inteligencia artificial en los procesos de secuenciación de la producción. Posteriormente y con base en la experimentación planteada, los resultados obtenidos, muestran que estas técnicas presentan una efectividad superior al 95%, con un intervalo de confiabilidad del 99.5% medido en las variables objeto de estudio.

  12. A psychoanalyst artificial intelligence model in a computer game

    OpenAIRE

    Muñoz Fernández, Enrique

    2012-01-01

    Projecte realitzat en el marc d'un programa de mobilitat amb la Vienna University of Technology. [ANGLÈS] Implementation of an artificial intelligence model based on the psychoanalytic theory of the ID-Ego-SuperEgo of Sigmund Freud into the computer game Unreal Tournament 2004. [CASTELLÀ] Implementación de un modelo de inteligencia artificial basado en la teoría psicoanalítica del ID-Ego-SuperEgo de Sigmund Freud en el videojuego Unreal Tournament 2004. [CATALÀ] Implementació d'un mo...

  13. Use of Artificial Intelligence in Real Property Valuation

    Directory of Open Access Journals (Sweden)

    Dr. N. B. Chaphalkar

    2013-06-01

    Full Text Available Real properties possess value which is dependent on numerous factors. Investors and owners of the property are interested in the maximum returns, it would fetch. Considering the amount of money involved in real estate, there is a need of accurate prediction of returns and associated risks. This necessitates use of Artificial Intelligence (AI prediction models. This study attempts to analyze and summarize AI techniques, which gives insight to application of various techniques for prediction related to property valuation. Comparison of various techniques shows that Artificial Neural Network (ANNand fuzzy logic are better suited if attributes and model parameters are appropriately selected.

  14. Artificial Intelligent Control for a Novel Advanced Microwave Biodiesel Reactor

    International Nuclear Information System (INIS)

    Biodiesel, an alternative diesel fuel made from a renewable source, is produced by the transesterification of vegetable oil or fat with methanol or ethanol. In order to control and monitor the progress of this chemical reaction with complex and highly nonlinear dynamics, the controller must be able to overcome the challenges due to the difficulty in obtaining a mathematical model, as there are many uncertain factors and disturbances during the actual operation of biodiesel reactors. Classical controllers show significant difficulties when trying to control the system automatically. In this paper we propose a comparison of artificial intelligent controllers, Fuzzy logic and Adaptive Neuro-Fuzzy Inference System(ANFIS) for real time control of a novel advanced biodiesel microwave reactor for biodiesel production from waste cooking oil. Fuzzy logic can incorporate expert human judgment to define the system variables and their relationships which cannot be defined by mathematical relationships. The Neuro-fuzzy system consists of components of a fuzzy system except that computations at each stage are performed by a layer of hidden neurons and the neural network's learning capability is provided to enhance the system knowledge. The controllers are used to automatically and continuously adjust the applied power supplied to the microwave reactor under different perturbations. A Labview based software tool will be presented that is used for measurement and control of the full system, with real time monitoring.

  15. Artificial Intelligent Control for a Novel Advanced Microwave Biodiesel Reactor

    Science.gov (United States)

    Wali, W. A.; Hassan, K. H.; Cullen, J. D.; Al-Shamma'a, A. I.; Shaw, A.; Wylie, S. R.

    2011-08-01

    Biodiesel, an alternative diesel fuel made from a renewable source, is produced by the transesterification of vegetable oil or fat with methanol or ethanol. In order to control and monitor the progress of this chemical reaction with complex and highly nonlinear dynamics, the controller must be able to overcome the challenges due to the difficulty in obtaining a mathematical model, as there are many uncertain factors and disturbances during the actual operation of biodiesel reactors. Classical controllers show significant difficulties when trying to control the system automatically. In this paper we propose a comparison of artificial intelligent controllers, Fuzzy logic and Adaptive Neuro-Fuzzy Inference System(ANFIS) for real time control of a novel advanced biodiesel microwave reactor for biodiesel production from waste cooking oil. Fuzzy logic can incorporate expert human judgment to define the system variables and their relationships which cannot be defined by mathematical relationships. The Neuro-fuzzy system consists of components of a fuzzy system except that computations at each stage are performed by a layer of hidden neurons and the neural network's learning capability is provided to enhance the system knowledge. The controllers are used to automatically and continuously adjust the applied power supplied to the microwave reactor under different perturbations. A Labview based software tool will be presented that is used for measurement and control of the full system, with real time monitoring.

  16. An artificial intelligence system for computer-assisted menu planning.

    Science.gov (United States)

    Petot, G J; Marling, C; Sterling, L

    1998-09-01

    Planning nutritious and appetizing menus is a complex task that researchers have tried to computerize since the early 1960s. We have attempted to facilitate computer-assisted menu planning by modeling the reasoning an expert dietitian uses to plan menus. Two independent expert systems were built, each designed to plan a daily menu meeting the nutrition needs and personal preferences of an individual client. One system modeled rule-based, or logical, reasoning, whereas the other modeled case-based, or experiential, reasoning. The 2 systems were evaluated and their strengths and weaknesses identified. A hybrid system was built, combining the best of both systems. The hybrid system represents an important step forward because it plans daily menus in accordance with a person's needs and preferences; the Reference Daily Intakes; the Dietary Guidelines for Americans; and accepted aesthetic standards for color, texture, temperature, taste, and variety. Additional work to expand the system's scope and to enhance the user interface will be needed to make it a practical tool. Our system framework could be applied to special-purpose menu planning for patients in medical settings or adapted for institutional use. We conclude that an artificial intelligence approach has practical use for computer-assisted menu planning. PMID:9739801

  17. Spike: Artificial intelligence scheduling for Hubble space telescope

    Science.gov (United States)

    Johnston, Mark; Miller, Glenn; Sponsler, Jeff; Vick, Shon; Jackson, Robert

    1990-01-01

    Efficient utilization of spacecraft resources is essential, but the accompanying scheduling problems are often computationally intractable and are difficult to approximate because of the presence of numerous interacting constraints. Artificial intelligence techniques were applied to the scheduling of the NASA/ESA Hubble Space Telescope (HST). This presents a particularly challenging problem since a yearlong observing program can contain some tens of thousands of exposures which are subject to a large number of scientific, operational, spacecraft, and environmental constraints. New techniques were developed for machine reasoning about scheduling constraints and goals, especially in cases where uncertainty is an important scheduling consideration and where resolving conflicts among conflicting preferences is essential. These technique were utilized in a set of workstation based scheduling tools (Spike) for HST. Graphical displays of activities, constraints, and schedules are an important feature of the system. High level scheduling strategies using both rule based and neural network approaches were developed. While the specific constraints implemented are those most relevant to HST, the framework developed is far more general and could easily handle other kinds of scheduling problems. The concept and implementation of the Spike system are described along with some experiments in adapting Spike to other spacecraft scheduling domains.

  18. Using artificial intelligence methods to design new conducting polymers

    Directory of Open Access Journals (Sweden)

    Ronaldo Giro

    2003-12-01

    Full Text Available In the last years the possibility of creating new conducting polymers exploring the concept of copolymerization (different structural monomeric units has attracted much attention from experimental and theoretical points of view. Due to the rich carbon reactivity an almost infinite number of new structures is possible and the procedure of trial and error has been the rule. In this work we have used a methodology able of generating new structures with pre-specified properties. It combines the use of negative factor counting (NFC technique with artificial intelligence methods (genetic algorithms - GAs. We present the results for a case study for poly(phenylenesulfide phenyleneamine (PPSA, a copolymer formed by combination of homopolymers: polyaniline (PANI and polyphenylenesulfide (PPS. The methodology was successfully applied to the problem of obtaining binary up to quinternary disordered polymeric alloys with a pre-specific gap value or exhibiting metallic properties. It is completely general and can be in principle adapted to the design of new classes of materials with pre-specified properties.

  19. Artificial Intelligence SVC Based Control of Two Machine Transmission System

    Directory of Open Access Journals (Sweden)

    Reza Bayat

    2013-07-01

    Full Text Available The main target in this paper is to present, design fuzzy logic controller (FLC applied to static var compensator (SVC on two machine transmission system to improve transient stability and rapid damping oscillations of synchronous generators, when power generators sudden changes occur.stability that also played important role in power systems. static var compensator with fuzzy logic controller (SVCFLC is a new control strategy can help improve transient stability.The effect of three phase fault causes instability on power system. By and large, it is very difficult to control machine speeds ,rotor angle and voltage during three-phase fault.SVCFLC is a voltage stablizer using three static var compensator which are controlled by SVC with fuzzy logic controller(FLC.The FLC is an effective device for transient stability of two-mashine transmission system. The nonlinear model dynamic formulation problem in unstable system can be solved by using artificial intelligence theorem. Fuzzy logic theory is used to improve the system stability . simulation results of three-phase fault in power system show that SVCFLC caused to increase the stability and damp out the oscillation of machine, compared with effective of SVC in the presence of power system stabilizer(PSS.

  20. Artificial Intelligent Control for a Novel Advanced Microwave Biodiesel Reactor

    Energy Technology Data Exchange (ETDEWEB)

    Wali, W A; Hassan, K H; Cullen, J D; Al-Shamma' a, A I; Shaw, A; Wylie, S R, E-mail: w.wali@2009.ljmu.ac.uk [Built Environment and Sustainable Technologies Institute (BEST), School of the Built Environment, Faculty of Technology and Environment Liverpool John Moores University, Byrom Street, Liverpool L3 3AF (United Kingdom)

    2011-08-17

    Biodiesel, an alternative diesel fuel made from a renewable source, is produced by the transesterification of vegetable oil or fat with methanol or ethanol. In order to control and monitor the progress of this chemical reaction with complex and highly nonlinear dynamics, the controller must be able to overcome the challenges due to the difficulty in obtaining a mathematical model, as there are many uncertain factors and disturbances during the actual operation of biodiesel reactors. Classical controllers show significant difficulties when trying to control the system automatically. In this paper we propose a comparison of artificial intelligent controllers, Fuzzy logic and Adaptive Neuro-Fuzzy Inference System(ANFIS) for real time control of a novel advanced biodiesel microwave reactor for biodiesel production from waste cooking oil. Fuzzy logic can incorporate expert human judgment to define the system variables and their relationships which cannot be defined by mathematical relationships. The Neuro-fuzzy system consists of components of a fuzzy system except that computations at each stage are performed by a layer of hidden neurons and the neural network's learning capability is provided to enhance the system knowledge. The controllers are used to automatically and continuously adjust the applied power supplied to the microwave reactor under different perturbations. A Labview based software tool will be presented that is used for measurement and control of the full system, with real time monitoring.

  1. APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN PROCESS FAULT DIAGNOSIS

    Directory of Open Access Journals (Sweden)

    M.A. HUSSAIN

    2007-12-01

    Full Text Available Chemical processes are systems that include complicated network of material, energy and process flow. As time passes, the performance of chemical process gradually degrades due to the deterioration of process equipments and components. The early detection and diagnosis of faults in chemical processes is very important both from the viewpoint of plant safety as well as reduced manufacturing costs. The conventional way used in fault detection and diagnosis is through the use of models of the process, which is not easy to be achieved in many cases. In recent years, an artificial intelligence technique such as neural network has been successfully used for pattern recognition and as such it can be suitable for use in fault diagnosis of processes [1]. The application of neural network methods in process fault detection and diagnosis is demonstrated in this work in two case studies using simulated chemical plant systems. Both systems were successfully diagnosed of the faults introduced in them. The neural networks were able to generalise to successfully diagnosed fault combinations it was not explicitly trained upon. Thus, neural network can be fully applied in industries as it has shown several advantages over the conventional way in fault diagnosis.

  2. Brown's transport up to third order aberration by artificial intelligence

    International Nuclear Information System (INIS)

    Brown's TRANSPORT is a first and second order matrix multiplication computer program intended for the design of accelerator beam transport systems, neglecting the third order aberration. Recently a new method was developed to derive analytically any order aberration coefficients of general charged particle optic system, applicable to any practical systems, such as accelerators, electron microscopes, lithographs, including those unknown systems yet to be invented. An artificial intelligence program in Turbo Prolog was implemented on IBM-PC 286 or 386 machine to generate automatically the analytical expression of any order aberration coefficients of general charged particle optic system. Based on this new method and technique, Brown's TRANSPORT is extended beyond the second order aberration effect by artificial intelligence, outputting automatically all the analytical expressions up to the third order aberration coefficients

  3. Research on artificial intelligence systems for nuclear installations

    International Nuclear Information System (INIS)

    The development and utilization of atomic energy in Japan has be advanced in conformity with the long term plan of atomic energy development and utilization decided in 1987. As one of the basic targets, the upbringing of creative and innovative science and technology is put up. Artificial intelligence technology has been positioned as one of the important basic technologies for promoting future atomic energy development. The research and development of artificial intelligence technology have been advanced aiming at making nuclear power stations autonomous, by the guidance of Science and Technology Agency and the cooperation of several research institutes. The upbringing of creative science and technology, the preponderant development of basic technology, the concept of developing the basic technology for atomic energy, the concept of autonomous plants, the standard for autonomy, the approach to autonomous plants, the present state of the researches in respective research institutes on autonomous operation and autonomous maintenance are described. (K.I.)

  4. Evaluation of Artificial Intelligence Based Models for Chemical Biodegradability Prediction

    Directory of Open Access Journals (Sweden)

    Aleksandar Sabljic

    2004-12-01

    Full Text Available This study presents a review of biodegradability modeling efforts including a detailed assessment of two models developed using an artificial intelligence based methodology. Validation results for these models using an independent, quality reviewed database, demonstrate that the models perform well when compared to another commonly used biodegradability model, against the same data. The ability of models induced by an artificial intelligence methodology to accommodate complex interactions in detailed systems, and the demonstrated reliability of the approach evaluated by this study, indicate that the methodology may have application in broadening the scope of biodegradability models. Given adequate data for biodegradability of chemicals under environmental conditions, this may allow for the development of future models that include such things as surface interface impacts on biodegradability for example.

  5. Artificial Intelligence Application in Power Generation Industry: Initial considerations

    Science.gov (United States)

    Ismail, Rahmat Izaizi B.; Ismail Alnaimi, Firas B.; AL-Qrimli, Haidar F.

    2016-03-01

    With increased competitiveness in power generation industries, more resources are directed in optimizing plant operation, including fault detection and diagnosis. One of the most powerful tools in faults detection and diagnosis is artificial intelligence (AI). Faults should be detected early so correct mitigation measures can be taken, whilst false alarms should be eschewed to avoid unnecessary interruption and downtime. For the last few decades there has been major interest towards intelligent condition monitoring system (ICMS) application in power plant especially with AI development particularly in artificial neural network (ANN). ANN is based on quite simple principles, but takes advantage of their mathematical nature, non-linear iteration to demonstrate powerful problem solving ability. With massive possibility and room for improvement in AI, the inspiration for researching them are apparent, and literally, hundreds of papers have been published, discussing the findings of hybrid AI for condition monitoring purposes. In this paper, the studies of ANN and genetic algorithm (GA) application will be presented.

  6. Brown's TRANSPORT up to third order aberration by artificial intelligence

    International Nuclear Information System (INIS)

    Brown's TRANSPORT is a first and second order matrix multiplication computer program intended for the design of accelerator beam transport systems, neglecting the third order aberration. Recently a new method was developed to derive analytically any order aberration coefficients of general charged particle optic system, applicable to any practical systems, such as accelerators, electron microscopes, lithographs, etc., including those unknown systems yet to be invented. An artificial intelligence program in Turbo Prolog was implemented on IBM-PC 286 or 386 machine to generate automatically the analytical expression of any order aberration coefficients of general charged particle optic system. Based on this new method and technique, Brown's TRANSPORT is extended beyond the second order aberration effects by artificial intelligence, outputing automatically all the analytical expressions up to the third order aberration coefficients

  7. 11th International Conference on Distributed Computing and Artificial Intelligence

    CERN Document Server

    Bersini, Hugues; Corchado, Juan; Rodríguez, Sara; Pawlewski, Paweł; Bucciarelli, Edgardo

    2014-01-01

    The 11th International Symposium on Distributed Computing and Artificial Intelligence 2014 (DCAI 2014) is a forum to present applications of innovative techniques for studying and solving complex problems. The exchange of ideas between scientists and technicians from both the academic and industrial sector is essential to facilitate the development of systems that can meet the ever-increasing demands of today’s society. The present edition brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. This year’s technical program presents both high quality and diversity, with contributions in well-established and evolving areas of research (Algeria, Brazil, China, Croatia, Czech Republic, Denmark, France, Germany, Ireland, Italy, Japan, Malaysia, Mexico, Poland, Portugal, Republic of Korea, Spain, Taiwan, Tunisia, Ukraine, United Kingdom), representing ...

  8. A quick overview of artificial intelligence and expert systems

    International Nuclear Information System (INIS)

    Artificial intelligence (AI) is almost a household word these days. There have been several conferences held in this country over the last two years on artificial intelligence and its applications. The international AI conference at Snowbird, Utah, in 1987 centered on AI applications in the nuclear industry. This paper serves as an introductory overview of the subject of AI for this state-of-the-art review of AI applications in the nuclear industry. We introduce the subject in a way that will be relevant to many people in the nuclear industry who have heard of AI but are not familiar with it and are looking for answers to several simple questions. We attempt to answer those simple questions here and prepare the reader so that he or she can appreciate the following sections on AI applications in the nuclear field. (orig./GL)

  9. Future of artificial intelligence -- Art, not Science

    CERN Document Server

    Kupervasser, Oleg

    2011-01-01

    Now in the world the technologies relating to design of systems of artificial intellect (AI) actively develop. In this paper it would be desirable to consider not tactical, but strategic problems of this process. Now not many interesting papers on this topic are available, but they exist [1]. It is relating to a fact that most of serious experts is occupied by a solution of tactical problems and often does not think about farther prospects. However the situation at the beginning of cybernetics origin was not that. Then these problems were actively considered. Therefore we will construct our paper as a review of problems of cybernetics as they saw to participants of the symposium in 1961 [2]. We will try to give the review of these prospects from the point of view of the up-to-date physical and cybernetic science and its last reachings.

  10. Meaning of cognitive processes for creating artificial intelligence

    OpenAIRE

    Smutný, Zdeněk

    2009-01-01

    This diploma thesis brings an integral view at cognitive processes connected with artificial intelligence systems, and makes a comparison with the processes observed in nature, including human being. A historical background helps us to look at the whole issue from a certain point of view. The main axis of interest comes after the historical overview and includes the following: environment -- stimulations -- processing -- reflection in the cognitive system -- reaction to stimulation; I balance...

  11. Analysis of dynamic conflicts by techniques of artificial intelligence

    OpenAIRE

    Shinar, Josef

    1989-01-01

    Dynamic conflicts exhibit differentiel game characteristics and their analysis by any method which disregards this feature may be, by definition, futile. Unfortunately, realistic conflicts may have an intricate information structure and a complex hierarchy which don't fit in the classical differential game formulation. Moreover, in many cases even well formulated differential games are not solvable. In the recent years great progress has been made in artificial intelligence techniques, put in...

  12. PRONET: Basic concepts of a system of Artificial Intelligence

    OpenAIRE

    S. Lasai

    1999-01-01

    In the work are expounded the principles and basic elements of a system of artificial intelligence. Knowledge representation develops according to the method settled for processing. A thing, a phenomenon can be determined or established by more modules subject to their state as well as the links and relations between them. The system creates a set of blocks (modules) for which the concurrent work is pre- established. The volume of knowledge can be also increased without increasing the number ...

  13. Implementing Human-like Intuition Mechanism in Artificial Intelligence

    OpenAIRE

    Dundas, Jitesh; Chik, David

    2011-01-01

    Human intuition has been simulated by several research projects using artificial intelligence techniques. Most of these algorithms or models lack the ability to handle complications or diversions. Moreover, they also do not explain the factors influencing intuition and the accuracy of the results from this process. In this paper, we present a simple series based model for implementation of human-like intuition using the principles of connectivity and unknown entities. By using Poker hand data...

  14. Application of artificial intelligence techniques to TRR operation

    International Nuclear Information System (INIS)

    It has been over ten years since TRR had its initial critical. To collect the experiences of shift operators and technique staffs and transfer these experts' knowledge to a computer and build an expert system is a typical application of artificial intelligence techniques to nuclear business. The system can provide the correct information of TRR operation for shift personnel, new staffs and other technical people

  15. The 1991 Goddard Conference on Space Applications of Artificial Intelligence

    Science.gov (United States)

    Rash, James L. (Editor)

    1991-01-01

    The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in this proceeding fall into the following areas: Planning and scheduling, fault monitoring/diagnosis/recovery, machine vision, robotics, system development, information management, knowledge acquisition and representation, distributed systems, tools, neural networks, and miscellaneous applications.

  16. Experiments with microcomputer-based artificial intelligence environments

    Science.gov (United States)

    Summers, E.G.; MacDonald, R.A.

    1988-01-01

    The U.S. Geological Survey (USGS) has been experimenting with the use of relatively inexpensive microcomputers as artificial intelligence (AI) development environments. Several AI languages are available that perform fairly well on desk-top personal computers, as are low-to-medium cost expert system packages. Although performance of these systems is respectable, their speed and capacity limitations are questionable for serious earth science applications foreseen by the USGS. The most capable artificial intelligence applications currently are concentrated on what is known as the "artificial intelligence computer," and include Xerox D-series, Tektronix 4400 series, Symbolics 3600, VAX, LMI, and Texas Instruments Explorer. The artificial intelligence computer runs expert system shells and Lisp, Prolog, and Smalltalk programming languages. However, these AI environments are expensive. Recently, inexpensive 32-bit hardware has become available for the IBM/AT microcomputer. USGS has acquired and recently completed Beta-testing of the Gold Hill Systems 80386 Hummingboard, which runs Common Lisp on an IBM/AT microcomputer. Hummingboard appears to have the potential to overcome many of the speed/capacity limitations observed with AI-applications on standard personal computers. USGS is a Beta-test site for the Gold Hill Systems GoldWorks expert system. GoldWorks combines some high-end expert system shell capabilities in a medium-cost package. This shell is developed in Common Lisp, runs on the 80386 Hummingboard, and provides some expert system features formerly available only on AI-computers including frame and rule-based reasoning, on-line tutorial, multiple inheritance, and object-programming. ?? 1988 International Association for Mathematical Geology.

  17. Artificial intelligence issues related to automated computing operations

    Science.gov (United States)

    Hornfeck, William A.

    1989-01-01

    Large data processing installations represent target systems for effective applications of artificial intelligence (AI) constructs. The system organization of a large data processing facility at the NASA Marshall Space Flight Center is presented. The methodology and the issues which are related to AI application to automated operations within a large-scale computing facility are described. Problems to be addressed and initial goals are outlined.

  18. Artificial intelligence techniques for industrial applications in job shop scheduling.

    OpenAIRE

    Townsend, Wade Benton

    1983-01-01

    The application of AI (artificial intelligence) techniques to the scheduling of industrial production operations offers a promising new approach to a scheduling problem of great magnitude and complexity. Foremost among these techniques is a powerful knowledge representation language that is capable of modeling the production environment at all levels of detail. The capturing of such complexity in the data base enables the computer to generate feasible schedules from a very large solution spac...

  19. A Survey of Artificial Intelligence Research at the IIIA

    OpenAIRE

    Lopez de Mantaras, Ramon; Spanish Council for Scientific Research (CSIC)

    2014-01-01

    The IIIA is a public research centre, belonging to the Spanish National Research Council (CSIC), dedicated to AI research. We focus our activities on a few well-defined sub-domains of Artificial Intelligence, positively avoiding dispersion and keeping a good balance between basic research and applications, and paying particular attention to training PhD students and technology transfer. In this article, we survey some of the most relevant results we have obtained during the last 12 years.

  20. The Innovative Applications of Artificial Intelligence Conference: Past and Future

    OpenAIRE

    Shrobe, Howard

    1996-01-01

    This article is a reflection on the goals and focus of the Innovative Applications of Artificial Intelligence (IAAI) Conference. The author begins with an historical review of the conference. He then goes on to discuss the role of the IAAI conference, including an examination of the relationship between AI scientific research and the application of AI technology. He concludes with a presentation of the new vision for the IAAI conference.

  1. The Dartmouth College Artificial Intelligence Conference: The Next Fifty Years

    OpenAIRE

    Moor, James

    2006-01-01

    The Dartmouth College Artificial Intelligence Conference: The Next 50 Years (AI@50) took place July 13-15, 2006. The conference had three objectives: to celebrate the Dartmouth Summer Research Project, which occurred in 1956; to assess how far AI has progressed; and to project where AI is going or should be going. AI@50 was generously funded by the office of the Dean of Faculty and the office of the Provost at Dartmouth College, by DARPA, and by some private donors.

  2. Use of Artificial Intelligence in Real Property Valuation

    OpenAIRE

    Dr. N. B. Chaphalkar; Sayali Sandbhor

    2013-01-01

    Real properties possess value which is dependent on numerous factors. Investors and owners of the property are interested in the maximum returns, it would fetch. Considering the amount of money involved in real estate, there is a need of accurate prediction of returns and associated risks. This necessitates use of Artificial Intelligence (AI) prediction models. This study attempts to analyze and summarize AI techniques, which gives insight to application of various techniques for prediction r...

  3. Artificial Decision Making Under Uncertainty in Intelligent Buildings

    OpenAIRE

    Boman, Magnus; Davidsson, Paul; Younes, Hakan L.

    2013-01-01

    Our hypothesis is that by equipping certain agents in a multi-agent system controlling an intelligent building with automated decision support, two important factors will be increased. The first is energy saving in the building. The second is customer value---how the people in the building experience the effects of the actions of the agents. We give evidence for the truth of this hypothesis through experimental findings related to tools for artificial decision making. A number of assumptions ...

  4. Artificial intelligence, expert systems, computer vision, and natural language processing

    Science.gov (United States)

    Gevarter, W. B.

    1984-01-01

    An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

  5. Experiments with microcomputer-based artificial intelligence environments

    Energy Technology Data Exchange (ETDEWEB)

    Summers, E.G.; MacDonald, R.A.

    1988-11-01

    The US Geological Survey (USGS) has been experimenting with the use of relatively inexpensive microcomputers as artificial intelligence (AI) development environments. Several AI languages are available that perform fairly well on desk-top personal computers, as are low-to-medium cost expert system packages. Although performance of these systems is respectable, their speed and capacity limitations are questionable for serious earth science applications foreseen by the USGS. The most capable artificial intelligence applications currently are concentrated on what is known as the artificial intelligence computer, and include Xerox D-series, Tektronix 4400 series, Symbolics 3600, VAX, LMI, and Texas Instruments Explorer. The artificial intelligence computer runs expert system shells and Lisp, Prolog, and Smalltalk programming languages. However, these AI environments are expensive. Recently inexpensive 32-bit hardware has become available for the IBM/AT microcomputer. USGS has acquired and recently completed Beta-testing of the Golf Hill Systems 80386 Hummingboard, which runs Common Lisp on an IBM/AT microcomputer. Hummingboard appears to have the potential to overcome many of the speed/capacity limitations observed with AI-applications on standard personal computers. USGS is a Beta-test site for the Gold Hill Systems GoldWorks expert system. GoldWorks combines some high-end expert system shell capabilities in a medium-cost package. This shell is developed in Common Lisp, runs on the 80386 Hummingboard, and provides some expert system features formerly available only on AI-computers including frame and rule-based reasoning, on-line tutorial, multiple inheritance, and object-programming.

  6. A PHILOSOPHICAL APPROACH TO ARTIFICIAL INTELLIGENCE AND ISLAMIC VALUES

    OpenAIRE

    2012-01-01

    Artificial Intelligence has the potential to empower humans through enhanced learning and performance. But if this potential is to be realized and accepted, the ethical aspects as well as the technical must be addressed. Many engineers claim that AI will be smarter than human brains, including scientific creativity, general wisdom and social skills, so we must consider it an important factor for making decisions in our social life and especially in our Islamic societies. The most important ch...

  7. Artificial Intelligence in Information Services: Revolution or Survival?

    OpenAIRE

    Mess, John A

    2012-01-01

    The evolution of society places a growing demand on access to information. Libraries have been pivotal in shaping society by providing this access, but now that role has been altered by information dynamics and knowledge economics. The rapid advances in computer technology and software design, especially in artificial intelligence, have shifted libraries to a "demand" economy. Unless libraries begin exploiting the technologies and innovate manage information and knowledge, they may face obsol...

  8. Control Strategies and Artificial Intelligence in Rehabilitation Robotics

    OpenAIRE

    Novak, Domen; University of Wyoming; Riener, Robert; Swiss Federal Institute of Technology (ETH) in Zurich

    2015-01-01

    Rehabilitation robots physically support and guide a patient's limb during motor therapy, but require sophisticated control algorithms and artificial intelligence to do so. This article provides an overview of the state of the art in this area. It begins with the dominant paradigm of assistive control, from impedance-based cooperative controller through electromyography and intention estimation. It then covers challenge-based algorithms, which provide more difficult and complex tasks for the ...

  9. Real-Time Connect 4 Game Using Artificial Intelligence

    OpenAIRE

    Ahmad M. Sarhan; Adnan Shaout; Michele Shock

    2009-01-01

    Problem statement: The study presented a design that converted connect 4 game into a real-time game by incorporating time restraints. Approach: The design used Artificial Intelligence (AI) in implementing the connect 4 game. The AI for this game was based on influence mapping. Results: A waterfall-based AI software was developed for a Connect 4 game. Conclusion: A real time connect 4 game was successfully designed and implanted with GUI using C++ programming language.

  10. An Artificial Intelligence-Based Distance Education System: Artimat

    OpenAIRE

    NABIYEV, Vasif; Karal, Hasan; Arslan, Selahattin; ERUMIT, Ali Kürsat; Ayça CEBI

    2013-01-01

    The purpose of this study is to evaluate the artificial intelligence-based distance education system called as ARTIMAT, which has been prepared in order to improve mathematical problem solving skills of the students, in terms of conceptual proficiency and ease of use with the opinions of teachers and students. The implementation has been performed with 4 teachers and 59 students in 10th grade in an Anatolian High School in Trabzon. Many institutions and organizations in the world approach...

  11. 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.

  12. Exodus - Distributed artificial intelligence for Shuttle firing rooms

    Science.gov (United States)

    Heard, Astrid E.

    1990-01-01

    This paper describes the Expert System for Operations Distributed Users (EXODUS), a knowledge-based artificial intelligence system developed for the four Firing Rooms at the Kennedy Space Center. EXODUS is used by the Shuttle engineers and test conductors to monitor and control the sequence of tasks required for processing and launching Shuttle vehicles. In this paper, attention is given to the goals and the design of EXODUS, the operational requirements, and the extensibility of the technology.

  13. Artificial Intelligence- Is our future bright or bleak?

    OpenAIRE

    Gaurav Keswani

    2013-01-01

    The paper reviews the meaning of artificial intelligence and its various advantages and disadvantages. It also considers the current progress of this technology in the real world and discusses the applications of AI in the fields of heavy industries, gaming, aviation, weather forecasting, expert systems and heuristic classification, with the focus being on expert systems. This is because Expert Systems are primarily being used for cyber defence as information stored in computers and in transi...

  14. Artificial intelligence methods for discovery of relationships in genetic data

    OpenAIRE

    Juvan, Peter

    2005-01-01

    This dissertation reports on research and design of artificial intelligence and bioinformatics approaches and their application in the field of functional genomics. A novel approach to construction of genetic networks from data on mutations is proposed. Network construction involves two steps. The first step, inference of relations between genes, is characterized as abductive. Genetic experiments are the observations that need to be explained and relations between genes are abduced in order t...

  15. Artificial intelligence programming languages for computer aided manufacturing

    Science.gov (United States)

    Rieger, C.; Samet, H.; Rosenberg, J.

    1979-01-01

    Eight Artificial Intelligence programming languages (SAIL, LISP, MICROPLANNER, CONNIVER, MLISP, POP-2, AL, and QLISP) are presented and surveyed, with examples of their use in an automated shop environment. Control structures are compared, and distinctive features of each language are highlighted. A simple programming task is used to illustrate programs in SAIL, LISP, MICROPLANNER, and CONNIVER. The report assumes reader knowledge of programming concepts, but not necessarily of the languages surveyed.

  16. Real-Time Connect 4 Game Using Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Ahmad M. Sarhan

    2009-01-01

    Full Text Available Problem statement: The study presented a design that converted connect 4 game into a real-time game by incorporating time restraints. Approach: The design used Artificial Intelligence (AI in implementing the connect 4 game. The AI for this game was based on influence mapping. Results: A waterfall-based AI software was developed for a Connect 4 game. Conclusion: A real time connect 4 game was successfully designed and implanted with GUI using C++ programming language.

  17. Artificial intelligence and virtual environment application for materials design methodology

    OpenAIRE

    L.A. Dobrzański; R. Honysz

    2010-01-01

    Purpose: The purpose of this study is to develop a methodology for material design, enabling the selection of the chemical elements concentration, heat and plastic treatment conditions and geometrical dimensions to ensure the required mechanical properties of structural steels specified by the designer of machinery and equipment as the basis for the design of material components manufactured from these steels, by using a computational model developed with use of artificial intelligence method...

  18. Artificial Intelligence Research at the University of California, Los Angeles

    OpenAIRE

    Dyer, Michael G.

    1985-01-01

    Research in AI within the Computer Science Department at the University of California, Los Angeles is loosely composed of three interacting and cooperating groups: (1) the Artificial Intelligence Laboratory, at 3677 Boelter Hall, which is concerned mainly with natural language processing and cognitive modelling, (2) the Cognitive Systems Laboratory, at 4731 Boelter Hall, which studies the nature of search, logic programming, heuristics, and formal methods, and (3) the Robotics and Vision Labo...

  19. Application of artificial intelligence to triple quadrupole mass spectrometry (TQMS)

    International Nuclear Information System (INIS)

    At Lawrence Livermore National Laboratory the authors have designed a totally computerized triple quadrupole mass spectrometer with the ultimate goal of using it as a prototype for ''knowledge-based'' instrument control. As an ''intelligent'' instrument, with its computer-based data acquisition and control system, it has the ability to learn and respond quickly. The intelligence is encoded in the system using the representation and rule-based reasoning heuristic techniques of Artificial Intelligence. These techniques are used to encode heuristic knowledge, or the intuition, formal and informal rules, and experiential knowledge that the human expert normally uses to make decisions and arrive at solutions in a specific domain problem. In this specific case, the knowledge the authors are encoding is a tuning procedure for the spectrometer, including heuristics to describe a self-adaptive, feedback control process for real-time optimization or tuning of the data acquisition procedure throughout the entire data collection process

  20. An artificial intelligence approach to accelerator control systems

    International Nuclear Information System (INIS)

    An experiment was recently started at LAMPF to evaluate the power and limitations of using artificial intelligence techniques to solve problems in accelerator control and operation. A knowledge base was developed to describe the characteristics and the relationships of the first 30 devices in the LAMPF H+ beam line. Each device was categorized and pertinent attributes for each category defined. Specific values were assigned in the knowledge base to represent each actual device. Relationships between devices are modeled using the artificial intelligence techniques of rules, active values, and object-oriented methods. This symbolic model, built using the Knowledge Engineering Environment (KEE) system, provides a framework for analyzing faults, tutoring trainee operators, and offering suggestions to assist in beam tuning. Based on information provided by the domain expert responsible for tuning this portion of the beam line, additional rules were written to describe how he tunes, how he analyzes what is actually happening, and how he deals with failures. Initial results have shown that artificial intelligence techniques can be a useful adjunct to traditional methods of numerical simulation. Successful and efficient operation of future accelerators may depend on the proper merging of symbolic reasoning and conventional numerical control algorithms

  1. A REVIEW ON ARTIFICIAL INTELLIGENT SYSTEM FOR BEARING CONDITION MONITORING

    Directory of Open Access Journals (Sweden)

    PIYUSH M. PATEL,

    2011-02-01

    Full Text Available Artificial Intelligence (AI is an emerging technology. Research in AI is focused on developing computational approaches to intelligent behavior. The computer programs with which AI could be associated are primarily processes associated with complexity, ambiguity, ndecisiveness, and uncertainty. This present paper surveys the development of a condition monitoring procedure for different types ofbearings, which involves an artificial intelligence method as well as reviewed in order to examine the capability of AI methods and techniques to effectively address various hard-to-solve design tasks and issues relating different types of bearing fault. Although this review cannot be collectively exhaustive, it may be considered as a valuable guide for researchers who are interested in the domain of AI and wish to explore the opportunities offered by fuzzy logic, artificial neural networks and genetic algorithms for further improvement of conditioning monitoring for different types of bearing under different operating conditioning. Recent trends in research on conditioning monitoring using AI for different bearing have also been included.

  2. Neuro-Based Artificial Intelligence Model for Loan Decisions

    Directory of Open Access Journals (Sweden)

    Shorouq F. Eletter

    2010-01-01

    Full Text Available Problem statement: Despite the increase in consumer loans defaults and competition in the banking market, most of the Jordanian commercial banks are reluctant to use artificial intelligence software systems for supporting loan decisions. Approach: This study developed a proposed model that identifies artificial neural network as an enabling tool for evaluating credit applications to support loan decisions in the Jordanian Commercial banks. A multi-layer feed-forward neural network with backpropagation learning algorithm was used to build up the proposed model. Results: Different representative cases of loan applications were considered based on the guidelines of different banks in Jordan, to validate the neural network model. Conclusion: The results indicated that artificial neural networks are a successful technology that can be used in loan application evaluation in the Jordanian commercial banks.

  3. Space Communication Artificial Intelligence for Link Evaluation Terminal (SCAILET)

    Science.gov (United States)

    Shahidi, Anoosh K.; Schlegelmilch, Richard F.; Petrik, Edward J.; Walters, Jerry L.

    1992-01-01

    A software application to assist end-users of the high burst rate (HBR) link evaluation terminal (LET) for satellite communications is being developed. The HBR LET system developed at NASA Lewis Research Center is an element of the Advanced Communications Technology Satellite (ACTS) Project. The HBR LET is divided into seven major subsystems, each with its own expert. Programming scripts, test procedures defined by design engineers, set up the HBR LET system. These programming scripts are cryptic, hard to maintain and require a steep learning curve. These scripts were developed by the system engineers who will not be available for the end-users of the system. To increase end-user productivity a friendly interface needs to be added to the system. One possible solution is to provide the user with adequate documentation to perform the needed tasks. With the complexity of this system the vast amount of documentation needed would be overwhelming and the information would be hard to retrieve. With limited resources, maintenance is another reason for not using this form of documentation. An advanced form of interaction is being explored using current computer techniques. This application, which incorporates a combination of multimedia and artificial intelligence (AI) techniques to provided end-users with an intelligent interface to the HBR LET system, is comprised of an intelligent assistant, intelligent tutoring, and hypermedia documentation. The intelligent assistant and tutoring systems address the critical programming needs of the end-user.

  4. Making smart cities smarter using artificial intelligence techniques for smarter mobility

    OpenAIRE

    Vázquez Salceda, Javier; Álvarez Napagao, Sergio; Tejeda Gómez, José Arturo; Oliva Felipe, Luis Javier; Garcia Gasulla, Dario; Gómez Sebastià, Ignasi; Codina Busquet, Víctor

    2014-01-01

    The term Smart City is tipically applied to urban and metropolitan areas where Information and Communication Technologies provide ways to enable social, cultural and urban development, improving social and political capacities and/or efficiency. In this paper we will show the potential of Artificial Intelligence techniques for augmenting ICT solutions to both increase the cities competiveness but also the active participation of citizens in those processes, making Smart Cities smarter. As exa...

  5. Artificial intelligence. Application of the Statistical Neural Networks computer program in nuclear medicine

    International Nuclear Information System (INIS)

    Artificial Neural Networks (ANN) may be a tool alternative and complementary to typical statistical analysis. However, in spite of many computer application of various ANN algorithms ready for use, artificial intelligence is relatively rarely applied to data processing. In this paper practical aspects of scientific application of ANN in medicine using the Statistical Neural Networks Computer program, were presented. Several steps of data analysis with the above ANN software package were discussed shortly, from material selection and its dividing into groups to the types of obtained results. The typical problems connected with assessing scintigrams by ANN were also described. (author)

  6. Artificial intelligence methods in process plant layout

    OpenAIRE

    McBrien, Andrew

    1994-01-01

    The thesis describes "Plant Layout System" or PLS, an Expert System which automates all aspects of conceptual layout of chemical process plant, from sizing equipment using process data to deriving the equipment items' elevation and plan positions. PLS has been applied to a test process of typical size and complexity and which encompasses a wide range of layout issues and problems. The thesis presents the results of the tests to show that PLS generates layouts that are entirely satisfactory an...

  7. Applying Artificial Neural Networks for Face Recognition

    Directory of Open Access Journals (Sweden)

    Thai Hoang Le

    2011-01-01

    Full Text Available This paper introduces some novel models for all steps of a face recognition system. In the step of face detection, we propose a hybrid model combining AdaBoost and Artificial Neural Network (ABANN to solve the process efficiently. In the next step, labeled faces detected by ABANN will be aligned by Active Shape Model and Multi Layer Perceptron. In this alignment step, we propose a new 2D local texture model based on Multi Layer Perceptron. The classifier of the model significantly improves the accuracy and the robustness of local searching on faces with expression variation and ambiguous contours. In the feature extraction step, we describe a methodology for improving the efficiency by the association of two methods: geometric feature based method and Independent Component Analysis method. In the face matching step, we apply a model combining many Neural Networks for matching geometric features of human face. The model links many Neural Networks together, so we call it Multi Artificial Neural Network. MIT + CMU database is used for evaluating our proposed methods for face detection and alignment. Finally, the experimental results of all steps on CallTech database show the feasibility of our proposed model.

  8. Artificial intelligence and virtual environment application for materials design methodology

    Directory of Open Access Journals (Sweden)

    L.A. Dobrzański

    2010-10-01

    Full Text Available Purpose: The purpose of this study is to develop a methodology for material design, enabling the selection of the chemical elements concentration, heat and plastic treatment conditions and geometrical dimensions to ensure the required mechanical properties of structural steels specified by the designer of machinery and equipment as the basis for the design of material components manufactured from these steels, by using a computational model developed with use of artificial intelligence methods and virtual environment. The model is designed to provide impact examinations of these factors on the mechanical properties of steel only in the computing environment.Design/methodology/approach: A virtual research environment built with use of computational model describing relationships between chemical composition, heat and plastic treatment conditions and product geometric dimensions and mechanical properties of the examined group of steel was developed and practical applied. This model enables the design of new structural steel by setting the values of mechanical properties based on material production descriptors and allows the selection of production descriptors on the basis of the mechanical properties without the need for additional tests or experimental studies in reality.Findings: Virtual computing environment allows full usage of the developed intelligent model of non-alloy and alloy structural steel properties and provides an easy, intuitive and user-friendly way to designate manufacturing descriptors and mechanical properties for products.Research limitations/implications:The proposed solutions allow the usage of developed virtual environment as a new medium in both, the scientific work performed remotely, as well as in education during classes.Practical implications: The new material design methodology has practical application in the development of materials and modelling of steel descriptors in aim to improve the mechanical properties and

  9. An intelligent remote monitoring system for artificial heart.

    Science.gov (United States)

    Choi, Jaesoon; Park, Jun W; Chung, Jinhan; Min, Byoung G

    2005-12-01

    A web-based database system for intelligent remote monitoring of an artificial heart has been developed. It is important for patients with an artificial heart implant to be discharged from the hospital after an appropriate stabilization period for better recovery and quality of life. Reliable continuous remote monitoring systems for these patients with life support devices are gaining practical meaning. The authors have developed a remote monitoring system for this purpose that consists of a portable/desktop monitoring terminal, a database for continuous recording of patient and device status, a web-based data access system with which clinicians can access real-time patient and device status data and past history data, and an intelligent diagnosis algorithm module that noninvasively estimates blood pump output and makes automatic classification of the device status. The system has been tested with data generation emulators installed on remote sites for simulation study, and in two cases of animal experiments conducted at remote facilities. The system showed acceptable functionality and reliability. The intelligence algorithm also showed acceptable practicality in an application to animal experiment data. PMID:16379373

  10. The application of artificial intelligence to astronomical scheduling problems

    Science.gov (United States)

    Johnston, Mark D.

    1992-01-01

    Efficient utilization of expensive space- and ground-based observatories is an important goal for the astronomical community; the cost of modern observing facilities is enormous, and the available observing time is much less than the demand from astronomers around the world. The complexity and variety of scheduling constraints and goals has led several groups to investigate how artificial intelligence (AI) techniques might help solve these kinds of problems. The earliest and most successful of these projects was started at Space Telescope Science Institute in 1987 and has led to the development of the Spike scheduling system to support the scheduling of Hubble Space Telescope (HST). The aim of Spike at STScI is to allocate observations to timescales of days to a week observing all scheduling constraints and maximizing preferences that help ensure that observations are made at optimal times. Spike has been in use operationally for HST since shortly after the observatory was launched in Apr. 1990. Although developed specifically for HST scheduling, Spike was carefully designed to provide a general framework for similar (activity-based) scheduling problems. In particular, the tasks to be scheduled are defined in the system in general terms, and no assumptions about the scheduling timescale are built in. The mechanisms for describing, combining, and propagating temporal and other constraints and preferences are quite general. The success of this approach has been demonstrated by the application of Spike to the scheduling of other satellite observatories: changes to the system are required only in the specific constraints that apply, and not in the framework itself. In particular, the Spike framework is sufficiently flexible to handle both long-term and short-term scheduling, on timescales of years down to minutes or less. This talk will discuss recent progress made in scheduling search techniques, the lessons learned from early HST operations, the application of Spike

  11. Hybrid Systems Knowledge Representation Using Modelling Environment System Techniques Artificial Intelligence

    OpenAIRE

    Latif, Kamran

    2014-01-01

    Knowledge-based or Artificial Intelligence techniques are used increasingly as alternatives to more classical techniques to model ENVIRONMENTAL SYSTEMS. Use of Artificial Intelligence (AI) in environmental modelling has increased with recognition of its potential. In this paper we examine the DIFFERENT TECHNIQUES of Artificial intelligence with profound examples of human perception, learning and reasoning to solve complex problems. However with the increase of complexity better methods are re...

  12. The impact of soft computing for the progress of artificial intelligence

    OpenAIRE

    Cordón, Oscar; Gámez Martín, José Antonio; Hoffmann, Frank; Fernández Caballero, Antonio

    2011-01-01

    This special issue encompasses five papers devoted to the different existing relationships between soft computing branches and classical artificial intelligence. The issue originated from the ?50 years of artificial intelligence: campus in multidisciplinary perception and intelligence, CMPI-2006? multi-conference (http://www.info-ab.uclm.es/cmpi/1024x768/overview.htm), that was held in Albacete, Spain, during 10?14 July 2006, to commemorate the 50th anniversary of the creation of artificial i...

  13. Artificial Intelligence Research Capabilities of the Air Force Institute of Technology

    OpenAIRE

    Milne, Robert; Cross, Stephen

    1985-01-01

    The Air Force Institute of Technology (AFIT) provides master's degree education to Air Force and Army Officers in various engineering fields It is in a unique position to educate and perform research in the area of applications of artificial intelligence to military problems. Its two AI faculty members are the only military officers with PhD's in Artificial Intelligence. In the past two years, the artificial intelligence Laboratory of AFIT has become a major focal point for AI research and ap...

  14. The Artificial Intelligence Course at the Faculty of Computer Science in the Polytechnic University of Madrid

    OpenAIRE

    A. GÓMEZ-PÉREZ; Juristo, N.

    1994-01-01

    This paper presents the experience of teaching an Artificial Intelligence course at the Faculty of Computer Science in the Polytechnic University of Madrid, Spain. The objective of this course is to introduce the students to this field, to prepare them to contribute to the evolution of the technology, and to qualify them to solve problems in the real world using Artificial Intelligence technology. The curriculum of the Artificial Intelligence course, which is integrate...

  15. Analysis of Computer-Aided and Artificial Intelligence Technologies and Solutions in Service Industries in Russia

    OpenAIRE

    Rezanov, Vladislav

    2013-01-01

    The primary objective of this research study was to investigate the relationship between Computer-Aided and Artificial Intelligence Technologies and customer satisfaction in the context of businesses in Russia. The research focuses on methods of Artificial Intelligence technology application in business and its effect on customer satisfaction. The researcher introduces Artificial Intelligence and studies the forecasting approaches in relation to business operations. The rese...

  16. Enhancing nuclear power plant performance through the use of artificial intelligence

    International Nuclear Information System (INIS)

    The objective of this research is to advance the state-of-the-art of applying artificial intelligence technology (both expert systems and neural networks) to enhancing the performance (safety, efficiency, control and management) of nuclear power plants. A second, but equally important, objective is to build a broadly based critical mass of expertise in the artificial intelligence field that can be brought to bear on the technology of nuclear power plants. This means the production of graduates at the B.S., M.S., and Ph.D. levels in Nuclear Engineering and related fields. The research undertaken for this program is particularly appropriate for the M.S. theses and Ph.D. dissertations. A third objective is to transfer the technology developed to the ''nuclear power community,'' as well as the ''scientific and technological community,'' through publications in appropriate journals and proceedings and through presentations at national and international meetings

  17. Continuous surveillance of transformers using artificial intelligence methods; Surveillance continue des transformateurs: application des methodes d'intelligence artificielle

    Energy Technology Data Exchange (ETDEWEB)

    Schenk, A.; Germond, A. [Ecole Polytechnique Federale de Lausanne, Lausanne (Switzerland); Boss, P.; Lorin, P. [ABB Secheron SA, Geneve (Switzerland)

    2000-07-01

    The article describes a new method for the continuous surveillance of power transformers based on the application of artificial intelligence (AI) techniques. An experimental pilot project on a specially equipped, strategically important power transformer is described. Traditional surveillance methods and the use of mathematical models for the prediction of faults are described. The article describes the monitoring equipment used in the pilot project and the AI principles such as self-organising maps that are applied. The results obtained from the pilot project and methods for their graphical representation are discussed.

  18. Artificial intelligence support for scientific model-building

    Science.gov (United States)

    Keller, Richard M.

    1992-01-01

    Scientific model-building can be a time-intensive and painstaking process, often involving the development of large and complex computer programs. Despite the effort involved, scientific models cannot easily be distributed and shared with other scientists. In general, implemented scientific models are complex, idiosyncratic, and difficult for anyone but the original scientific development team to understand. We believe that artificial intelligence techniques can facilitate both the model-building and model-sharing process. In this paper, we overview our effort to build a scientific modeling software tool that aids the scientist in developing and using models. This tool includes an interactive intelligent graphical interface, a high-level domain specific modeling language, a library of physics equations and experimental datasets, and a suite of data display facilities.

  19. Application of AI (Artificial Intelligence) to management and analysis problems

    Energy Technology Data Exchange (ETDEWEB)

    DeLozier, R.C.

    1987-01-01

    This paper concerns the on-going development of the Naval Aviation Integrated Logistic (NAIL) package and the applications of Artificial Intelligence (AI) techniques using the PROLOG language. This package is being developed at the Oak Ridge National Laboratory (ORNL) for the Naval Aviation Logistic Center (NALC) to aid in projecting equipment repair and replacement requirements under assumed scenarios. Although NAIL is being designed for Naval applications, it can be used in virtually any large-scale operating environment, e.g., chemical manufacturing processes.

  20. ARTIFICIAL NEURAL NETWORKS BASED GEARS MATERIAL SELECTION HYBRID INTELLIGENT SYSTEM

    Institute of Scientific and Technical Information of China (English)

    X.C. Li; W.X. Zhu; G. Chen; D.S. Mei; J. Zhang; K.M. Chen

    2003-01-01

    An artificial neural networks(ANNs) based gear material selection hybrid intelligent system is established by analyzing the individual advantages and weakness of expert system (ES) and ANNs and the applications in material select of them. The system mainly consists of tow parts: ES and ANNs. By being trained with much data samples,the back propagation (BP) ANN gets the knowledge of gear materials selection, and is able to inference according to user input. The system realizes the complementing of ANNs and ES. Using this system, engineers without materials selection experience can conveniently deal with gear materials selection.

  1. PRONET: Basic concepts of a system of Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    S. Lasai

    1999-12-01

    Full Text Available In the work are expounded the principles and basic elements of a system of artificial intelligence. Knowledge representation develops according to the method settled for processing. A thing, a phenomenon can be determined or established by more modules subject to their state as well as the links and relations between them. The system creates a set of blocks (modules for which the concurrent work is pre- established. The volume of knowledge can be also increased without increasing the number of blocks.

  2. ICON: An artificial intelligence approach to radiologic differential diagnosis

    International Nuclear Information System (INIS)

    ICON is a computer system, developed using artificial intelligence techniques, that is designed to help radiologists manage the large body of knowledge needed to perform differential diagnosis in radiology. The system's domain is lung disease in patients with lymphoproliferative disorders. The radiologist proposes a diagnostic hypothesis which he or she thinks explains the known clinical and chest radiographic findings. ICON responds with an English-language prose critique that discusses how and why the proposed diagnosis is or is not supported by the clinical literature and suggests further findings or clinical information that might make the diagnosis more secure

  3. Chips challenging champions games, computers and artificial intelligence

    CERN Document Server

    Schaeffer, J

    2002-01-01

    One of the earliest dreams of the fledgling field of artificial intelligence (AI) was to build computer programs that could play games as well as or better than the best human players. Despite early optimism in the field, the challenge proved to be surprisingly difficult. However, the 1990s saw amazing progress. Computers are now better than humans in checkers, Othello and Scrabble; are at least as good as the best humans in backgammon and chess; and are rapidly improving at hex, go, poker, and shogi. This book documents the progress made in computers playing games and puzzles. The book is the

  4. The role of artificial intelligence techniques in scheduling systems

    Science.gov (United States)

    Geoffroy, Amy L.; Britt, Daniel L.; Gohring, John R.

    1990-01-01

    Artificial Intelligence (AI) techniques provide good solutions for many of the problems which are characteristic of scheduling applications. However, scheduling is a large, complex heterogeneous problem. Different applications will require different solutions. Any individual application will require the use of a variety of techniques, including both AI and conventional software methods. The operational context of the scheduling system will also play a large role in design considerations. The key is to identify those places where a specific AI technique is in fact the preferable solution, and to integrate that technique into the overall architecture.

  5. Artificial intelligence and expert systems in-flight software testing

    Science.gov (United States)

    Demasie, M. P.; Muratore, J. F.

    1991-01-01

    The authors discuss the introduction of advanced information systems technologies such as artificial intelligence, expert systems, and advanced human-computer interfaces directly into Space Shuttle software engineering. The reconfiguration automation project (RAP) was initiated to coordinate this move towards 1990s software technology. The idea behind RAP is to automate several phases of the flight software testing procedure and to introduce AI and ES into space shuttle flight software testing. In the first phase of RAP, conventional tools to automate regression testing have already been developed or acquired. There are currently three tools in use.

  6. Using artificial intelligence to control fluid flow computations

    Science.gov (United States)

    Gelsey, Andrew

    1992-01-01

    Computational simulation is an essential tool for the prediction of fluid flow. Many powerful simulation programs exist today. However, using these programs to reliably analyze fluid flow and other physical situations requires considerable human effort and expertise to set up a simulation, determine whether the output makes sense, and repeatedly run the simulation with different inputs until a satisfactory result is achieved. Automating this process is not only of considerable practical importance but will also significantly advance basic artificial intelligence (AI) research in reasoning about the physical world.

  7. Artificial intelligence techniques for scheduling Space Shuttle missions

    Science.gov (United States)

    Henke, Andrea L.; Stottler, Richard H.

    1994-01-01

    Planning and scheduling of NASA Space Shuttle missions is a complex, labor-intensive process requiring the expertise of experienced mission planners. We have developed a planning and scheduling system using combinations of artificial intelligence knowledge representations and planning techniques to capture mission planning knowledge and automate the multi-mission planning process. Our integrated object oriented and rule-based approach reduces planning time by orders of magnitude and provides planners with the flexibility to easily modify planning knowledge and constraints without requiring programming expertise.

  8. The application of artificial intelligence technology to aeronautical system design

    Science.gov (United States)

    Bouchard, E. E.; Kidwell, G. H.; Rogan, J. E.

    1988-01-01

    This paper describes the automation of one class of aeronautical design activity using artificial intelligence and advanced software techniques. Its purpose is to suggest concepts, terminology, and approaches that may be useful in enhancing design automation. By understanding the basic concepts and tasks in design, and the technologies that are available, it will be possible to produce, in the future, systems whose capabilities far exceed those of today's methods. Some of the tasks that will be discussed have already been automated and are in production use, resulting in significant productivity benefits. The concepts and techniques discussed are applicable to all design activity, though aeronautical applications are specifically presented.

  9. Teaching Artificial Intelligence and Logic Programming in a Competitive Environment

    Directory of Open Access Journals (Sweden)

    Pedro RIBEIRO

    2009-04-01

    Full Text Available Motivation plays a key role in the learning process. This paper describes an experience in the context of undergraduate teaching of Artificial Intelligence at the Computer Science Department of the Faculty of Sciences in the University of Porto. A sophisticated competition framework, which involved Prolog programmed contenders and game servers, including an appealing GUI, was developed to motivate students on the deepening of the topics covered in class. We report on the impact that such a competitive setup caused on students' commitment, which surpassed our most optimistic expectations.

  10. Artificial Intelligence in the service of system administrators

    CERN Document Server

    CERN. Geneva

    2012-01-01

    Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called “self objectives” supposed to lead to “autonomic computing”. In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way  Linux-based systems and their interaction with software. Moreover, the multi agent approach we use, coupled with a "object oriented paradigm" architecture should increase a lot our learning speed, and highlight relations between probl...

  11. Artificial intelligence program in a computer application supporting reactor operations

    International Nuclear Information System (INIS)

    Improving nuclear reactor power plant operability is an ever-present concern for the nuclear industry. The definition of plant operability involves a complex interaction of the ideas of reliability, safety, and efficiency. This paper presents observations concerning the issues involved and the benefits derived from the implementation of a computer application which combines traditional computer applications with artificial intelligence (AI) methodologies. A system, the Component Configuration Control System (CCCS), is being installed to support nuclear reactor operations at the Experimental Breeder Reactor II

  12. Application of artificial intelligence to improve plant availability

    International Nuclear Information System (INIS)

    Using artificial intelligence software techniques, Management Analysis Company (MAC) has developed two complementary software packages that together provide a workstation environment for maintenance and operations personnel to dramatically reduce inadvertent reactor trips. They are called the Reactor Trip Simulation Environment (RTSE) and the Key Component Generation Environment (KCGE). They are not proposed or being designed. They are in use today. The plants component and process interdependencies are modeled within RTSE - using modeling practices and notations familiar to engineers which accelerated the acceptance of the software. KCGE provides the groups of key components that would cause a reactor trip

  13. Narrative Generation in Entertainment: Using Artificial Intelligence Planning

    OpenAIRE

    George, Richard A.

    2015-01-01

    From the field of artificial intelligence (AI) there is a growing stream of technology capable of being embedded in software that will reshape the way we interact with our environment in our everyday lives. This ‘AI software’ is often used to tackle more mundane tasks that are otherwise dangerous or meticulous for a human to accomplish. One particular area, explored in this paper, is for AI software to assist in supporting the enjoyable aspects of the lives of humans. Entertainment is one of ...

  14. Using Artificial Intelligence Technology in Failsafe Realtime Systems

    Science.gov (United States)

    Nejdl, Wolfgang; Neuhold, Erich J.; Theuretzbacher, Norbert

    1987-04-01

    This paper is concerned with the use of artificial intelligence technology to increase system safety in failsafe realtime systems. A safety module for a failsafe realtime system is specified which uses a production system to implement the necessary security checks. The task of this safety module is to guarantee the safety of the system. To implement the safety module production system the AI language OPS83 is used. A complete prototype for use in the Electronic Interlocking System "ELEKTRA" from ITT-Austria is being built comprising approximately 100 to 200 safety assertions in the form of production rules.

  15. THE POTENTIAL OF ARTIFICIAL INTELLIGENCE IN SOUTH AFRICAN MANUFACTURING

    Directory of Open Access Journals (Sweden)

    A.R. Greef

    2012-01-01

    Full Text Available This paper provides an introduction to the most commonly used Knowledge Based Systems (KBS's called Rule Based Systems, presents some benefits of using these systems if the application warrants their attention and provides an over-view of current R&D as well as industrial systems already implemented. Areas of manUfacturing that could use KES's within the South African context are suggested. A research programme investigating the use of KBS's in robotics in progress at the University of Stellenbosch demonstrating a number of useful properties associated with programming Artificial Intelligence (AI techniques using logic programming, is discussed.

  16. Artificial Intelligence For A Safer And More Efficient Car Driving

    Science.gov (United States)

    Adorni, Giovanni

    1989-03-01

    In this paper a project, PROMETHEUS, is described in which fourteen of Europe's leading car manufacturers are to join with approximately forty research institutes and governmental agencies to make the traffic of Europe safer, more efficient and more economical. PROMETHEUS project is divided into seven areas. In this paper one of the seven areas, PRO-ART, is described. PRO-ART is aimed at clarifying the need for and the principles of the artificial intelligence to be used in the next generation automobile. After a brief description of the overhall project, the description of the seven years PRO-ART Italian research programme will be given.

  17. The Use of Artificial Intelligence on Finacial Market

    OpenAIRE

    Surynek, Jiří

    2013-01-01

    Diplomová práce se zabývá problematikou a následnou aplikací metod umělé inteligence na finančních trzích. Konkrétně se jedná o využití umělých neuronových sítí za účelem predikce hodnoty a určení trendu vývoje vybraného investičního nástroje. Vlastní řešení je vytvořeno ve vývojovém prostředí Matlab. This thesis focuses on the problem and application of artificial intelligence on the financial market. Especially, the use of artificial neural networks to forecast values and determine the t...

  18. A genetic-neural artificial intelligence approach to resins optimization

    International Nuclear Information System (INIS)

    This work presents a preliminary study about the viability and adequacy of a new methodology for the definition of one of the main properties of ion exchange resins used for isotopic separation. Basically, the main problem is the definition of pelicule diameter in case of pelicular ion exchange resins, in order to achieve the best performance in the shortest time. In order to achieve this, a methodology was developed, based in two classic techniques of Artificial Intelligence (AI). At first, an artificial neural network (NN) was trained to map the existing relations between the nucleus radius and the resin's efficiency associated with the exchange time. Later on, a genetic algorithm (GA) was developed in order to find the best pelicule dimension. Preliminary results seem to confirm the potential of the method, and this can be used in any chemical process employing ion exchange resins. (author)

  19. Outlier Detection with a Hybrid Artificial Intelligence Method

    Science.gov (United States)

    Mejía-Lavalle, Manuel; Obregón, Ricardo Gómez; Vivar, Atlántida Sánchez

    We propose a simple and efficient hybrid artificial intelligence method to detect exceptional data. The proposed method includes a novel end-user explanation feature. After various attempts, the best design was based on an unsupervised learning schema, which uses an hybrid adaptation of the Artificial Neural Network paradigms, the Case Based Reasoning methodology, the Data Mining area, and the Expert System shells. In our method, the cluster that contains the smaller number of instances is considered as outlier data. The method provides an explanation to the end user about why this cluster is exceptional regarding to the data universe. The proposed method has been tested and compared successfully not only with well-known academic data, but also with a real and very large financial database that contains attributes with numerical and categorical values.

  20. Artificial intelligence implementation in the APS process diagnostic

    International Nuclear Information System (INIS)

    Thermal spray process is a technique of coating manufacturing implementing a wide variety of materials and processes. This technique is characterized by up to 150 processing parameters influencing the coating properties. The control of the coating quality is needed through the consideration of a robust methodology that takes into account the parameter interdependencies, the process variability and offers the ability to quantify the processing parameter-process response relationships. The aim of this work is to introduce a new approach based on artificial intelligence responding to these requirements. A detailed procedure is presented considering an artificial neural network (ANN) structure which encodes implicitly the physical phenomena governing the process. The implementation of such a structure was coupled to experimental results of an optic sensor controlling the powder particle fusion state before the coating formation. The optimization steps were discussed and the predicted results were compared to the experimental ones allowing the identification of the control factors

  1. Applying a natural intelligence pattern in cognitive robots

    OpenAIRE

    Seyedeh Negar Jafari; Jafar Jafari Amirbandi; Amir Masoud Rahmani

    2013-01-01

    Human brain was always a mysterious subject to explore, as it has still got lots to be discovered, and a good topic to be studied in many aspects, by different branches of science. In other hand, one of the biggest concerns of the future generation of Artificial Intelligence (AI) is to build robots who can think like human. To achieve this AI engineers used the theories inspired by human intelligent, which were suggested by well-known psychologists, to improve the intelligence systems. To con...

  2. AN ARTIFICIAL INTELLIGENCE-BASED DISTANCE EDUCATION SYSTEM: Artimat

    Directory of Open Access Journals (Sweden)

    Vasif NABIYEV

    2013-04-01

    Full Text Available The purpose of this study is to evaluate the artificial intelligence-based distance education system called as ARTIMAT, which has been prepared in order to improve mathematical problem solving skills of the students, in terms of conceptual proficiency and ease of use with the opinions of teachers and students. The implementation has been performed with 4 teachers and 59 students in 10th grade in an Anatolian High School in Trabzon. Many institutions and organizations in the world approach seriously to distance education besides traditional education. It is inevitable to use the distance education in teaching the problem solving skills in this different dimension of the education. In the studies in Turkey and abroad in the field of mathematics teaching, problem solving skills are generally stated not to be at the desired level and often expressed to have difficulty in teaching. For this reason, difficulties of the students in problem solving have initially been evaluated and the system has been prepared utilizing artificial intelligence algorithms according to the obtained results. In the evaluation of the findings obtained from the application, it has been concluded that the system is responsive to the needs of the students and is successful in general, but that conceptual changes should be made in order that students adapt to the system quickly.

  3. Detection of drugs and explosives using neutron computerized tomography and artificial intelligence techniques

    International Nuclear Information System (INIS)

    In this study the development of a methodology to detect illicit drugs and plastic explosives is described with the objective of being applied in the realm of public security. For this end, non-destructive assay with neutrons was used and the technique applied was the real time neutron radiography together with computerized tomography. The system is endowed with automatic responses based upon the application of an artificial intelligence technique. In previous tests using real samples, the system proved capable of identifying 97% of the inspected materials.

  4. Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-01-01

    Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

  5. Proceedings of the 18th Irish Conference on Artificial Intelligence and Cognitive Science

    OpenAIRE

    Delany, Sarah Jane; Madden, Michael

    2009-01-01

    These proceedings contain the papers that were accepted for publication at AICS-2007, the 18th Annual Conference on Artificial Intelligence and Cognitive Science, which was held in the Dublin Institute of Technology; Dublin, Ireland; on the 29th to the 31st August 2007. AICS is the annual conference of the Artificial Intelligence Association of Ireland (AIAI).

  6. The application of artificial intelligence in optimisation of automotive components for reuse

    Directory of Open Access Journals (Sweden)

    D.A. Wahab

    2008-12-01

    Full Text Available Purpose: Automotive component reuse as one of the product recovery strategy is now gaining importance in viewof its impact on the environment. Research and development on components design and manufacturing as wellas tools and methods to facilitate reuse are under way in many countries. To enable reuse, components have to beassessed and its reliability and life time predicted. This paper presents the development work on an optimisationmodel for assessing potential automotive components for reuse using artificial intelligence approaches.Design/methodology/approach: As a part of the study, the paper currently focuses on initial study on ease ofdisassembly design. The model for predicting reliability and durability of reuse components is then developedusing Artificial Neural Networks (ANNs and further optimised for reliability and life cycle cost using GeneticAlgorithm (GA.Findings: The proposed model will enable the local automotive industry to effectively assess potentialcomponents for reuse in support of further design and manufacturing improvements.Research limitations/implications: This study hopes to contribute to design for reuse by assessing highpotential and reliable reuse components at the lowest costs.Originality/value: Artificial intelligence methods, such as artificial neural networks (ANNs and geneticalgorithm (GA, can be applied to solve problem as they can provide satisfactory and acceptable solutions formany complex problems.

  7. Where Artificial Intelligence and Neuroscience Meet: The Search for Grounded Architectures of Cognition

    Directory of Open Access Journals (Sweden)

    Frank van der Velde

    2010-01-01

    Full Text Available The collaboration between artificial intelligence and neuroscience can produce an understanding of the mechanisms in the brain that generate human cognition. This article reviews multidisciplinary research lines that could achieve this understanding. Artificial intelligence has an important role to play in research, because artificial intelligence focuses on the mechanisms that generate intelligence and cognition. Artificial intelligence can also benefit from studying the neural mechanisms of cognition, because this research can reveal important information about the nature of intelligence and cognition itself. I will illustrate this aspect by discussing the grounded nature of human cognition. Human cognition is perhaps unique because it combines grounded representations with computational productivity. I will illustrate that this combination requires specific neural architectures. Investigating and simulating these architectures can reveal how they are instantiated in the brain. The way these architectures implement cognitive processes could also provide answers to fundamental problems facing the study of cognition.

  8. A Multilayered Model for Artificial Intelligence of Game Character as Agent Architecture

    OpenAIRE

    Miyake, Youichiro; Miyake, Yoichiro

    2015-01-01

    As all mathematics have a beautiful structure, an inner mind model of Artificial Intelligence has a grand architecture. It consists of information flow and software modules. In this twenty years, an agent's inner intelligence model has been researched and developed by many game AI programmers in game titles. A whole image of an agent's intelligent model is explained.

  9. Robotics and autonomous systems in the 50th anniversary of artificial intelligence

    OpenAIRE

    Casals, Alicia; Fernández Caballero, Antonio

    2007-01-01

    The special issue on ?Robotics and Autonomous Systems in the 50th Anniversary of Artificial Intelligence? collects a subset of the best papers in the fields of Robotics and Autonomous Systems presented at the Campus Multidisciplinary in Perception and Intelligence, CMPI-2006. The CMPI-2006 international conference, held in Albacete, Spain, from July 10 to 14, 2006, resulted in a forum for scientists in commemoration of the 50th Anniversary of Artificial Intelligence, which successfully report...

  10. Report on the First Conference on Artificial General Intelligence (AGI-08)

    OpenAIRE

    de Garis, Hugo Roland; Xiamen University; Goertzel, Ben; Novamente LLC

    2009-01-01

    The First Conference on Artificial General Intelligence (AGI-08) was held on March 1-3, 2008, at the University of Memphis. The overall goal of the conference was to work toward a common understanding of the most promising paths toward creating AI systems with general intelligence at the human level and beyond, and to share interim results and ideas achieved by researchers actively working toward powerful artificial general intelligence.

  11. Space applications of artificial intelligence; 1990 Goddard Conference, Greenbelt, MD, May 1, 2, 1990, Selected Papers

    Science.gov (United States)

    Rash, James L. (Editor)

    1990-01-01

    The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

  12. Evolvable mathematical models: A new artificial Intelligence paradigm

    Science.gov (United States)

    Grouchy, Paul

    We develop a novel Artificial Intelligence paradigm to generate autonomously artificial agents as mathematical models of behaviour. Agent/environment inputs are mapped to agent outputs via equation trees which are evolved in a manner similar to Symbolic Regression in Genetic Programming. Equations are comprised of only the four basic mathematical operators, addition, subtraction, multiplication and division, as well as input and output variables and constants. From these operations, equations can be constructed that approximate any analytic function. These Evolvable Mathematical Models (EMMs) are tested and compared to their Artificial Neural Network (ANN) counterparts on two benchmarking tasks: the double-pole balancing without velocity information benchmark and the challenging discrete Double-T Maze experiments with homing. The results from these experiments show that EMMs are capable of solving tasks typically solved by ANNs, and that they have the ability to produce agents that demonstrate learning behaviours. To further explore the capabilities of EMMs, as well as to investigate the evolutionary origins of communication, we develop NoiseWorld, an Artificial Life simulation in which interagent communication emerges and evolves from initially noncommunicating EMM-based agents. Agents develop the capability to transmit their x and y position information over a one-dimensional channel via a complex, dialogue-based communication scheme. These evolved communication schemes are analyzed and their evolutionary trajectories examined, yielding significant insight into the emergence and subsequent evolution of cooperative communication. Evolved agents from NoiseWorld are successfully transferred onto physical robots, demonstrating the transferability of EMM-based AIs from simulation into physical reality.

  13. The role of the artificial intelligence within the context of the human factors in the nuclear safety

    International Nuclear Information System (INIS)

    The effective evaluation of a human-machine system depends heavily on a cognitive model of the human behaviour. The basic question is: How can we model the human cognition? The response should be found in the five disciplines that form the Cognitive Sciences: Artificial Intelligence, Cognitive Psychology, Neurophysiology, Linguistic, and Philosophy. Among them, the Artificial Intelligence appears as the catalyzer of the contributions and discoveries in the other four, trying to realize that cognitive model with the tools of the Computer Science. Sometimes, it seems as if these disciplines spoke different languages to describe the same ideas. It is necessary a holistic treatment of such questions that include the human cognition and its modelling. This becomes more clear when we observe that there are nowadays different methodologies that must be integrated in some way. This is the case of the symbolic approach (artificial intelligence), connectionist approach (neural networks) and the fuzzy logic. This paper makes a review of the available methodologies, showing the problems and the current solutions to answer the following question. How is possible to develop a human-machine system and an intelligent interface based on the Artificial Intelligence that fulfills the following characteristics: human-centered design, cognitive simulation of the human behaviour, and dynamic function allocation. This paper concludes with proposals of national projects to be applied to the Brazilian situation. (author). 28 refs

  14. BNAIC 2008: Proceedings 20th Belgian-Netherlands Conference on Artificial Intelligence

    OpenAIRE

    Nijholt, Anton; Pantic, Maja; Poel, Mannes; Hondorp, Hendri

    2008-01-01

    This book contains the proceedings of the 20th edition of the Belgian-Netherlands Conference on Artificial Intelligence. The conference was organized by the Human Media Interaction group of the University of Twente. As usual, the conference was under the auspices of the Belgian-Dutch Association for Artificial Intelligence (BNVKI) and the Dutch Research School for Information and Knowledge Systems (SIKS). The conference aims at presenting an overview of state-of-the-art research in artificial...

  15. AIonAI: a humanitarian law of artificial intelligence and robotics.

    Science.gov (United States)

    Ashrafian, Hutan

    2015-02-01

    The enduring progression of artificial intelligence and cybernetics offers an ever-closer possibility of rational and sentient robots. The ethics and morals deriving from this technological prospect have been considered in the philosophy of artificial intelligence, the design of automatons with roboethics and the contemplation of machine ethics through the concept of artificial moral agents. Across these categories, the robotics laws first proposed by Isaac Asimov in the twentieth century remain well-recognised and esteemed due to their specification of preventing human harm, stipulating obedience to humans and incorporating robotic self-protection. However the overwhelming predominance in the study of this field has focussed on human-robot interactions without fully considering the ethical inevitability of future artificial intelligences communicating together and has not addressed the moral nature of robot-robot interactions. A new robotic law is proposed and termed AIonAI or artificial intelligence-on-artificial intelligence. This law tackles the overlooked area where future artificial intelligences will likely interact amongst themselves, potentially leading to exploitation. As such, they would benefit from adopting a universal law of rights to recognise inherent dignity and the inalienable rights of artificial intelligences. Such a consideration can help prevent exploitation and abuse of rational and sentient beings, but would also importantly reflect on our moral code of ethics and the humanity of our civilisation. PMID:24414678

  16. Application of Artificial Intelligence to Reservoir Characterization - An Interdisciplinary Approach

    Energy Technology Data Exchange (ETDEWEB)

    Kelkar, B.G.; Gamble, R.F.; Kerr, D.R.; Thompson, L.G.; Shenoi, S.

    2000-01-12

    The primary goal of this project is to develop a user-friendly computer program to integrate geological and engineering information using Artificial Intelligence (AI) methodology. The project is restricted to fluvially dominated deltaic environments. The static information used in constructing the reservoir description includes well core and log data. Using the well core and the log data, the program identifies the marker beds, and the type of sand facies, and in turn, develops correlation's between wells. Using the correlation's and sand facies, the program is able to generate multiple realizations of sand facies and petrophysical properties at interwell locations using geostatistical techniques. The generated petrophysical properties are used as input in the next step where the production data are honored. By adjusting the petrophysical properties, the match between the simulated and the observed production rates is obtained.

  17. Artificial Intelligence techniques for mission planning for mobile robots

    International Nuclear Information System (INIS)

    This work focuses on Spatial Modelization Techniques and on Control Software Architectures, in order to deal efficiently with the Navigation and Perception problems encountered in Mobile Autonomous Robotics. After a brief survey of the current various approaches for these techniques, we expose ongoing simulation works for a specific mission in robotics. Studies in progress used for Spatial Reasoning are based on new approaches combining Artificial Intelligence and Geometrical techniques. These methods deal with the problem of environment modelization using three types of models: geometrical topological and semantic models at different levels. The decision making processes of control are presented as the result of cooperation between a group of decentralized agents that communicate by sending messages. (author)

  18. Classification of artificial intelligence ids for smurf attack

    CERN Document Server

    Ugtakhbayar, N; Sodbileg, Sh

    2012-01-01

    Many methods have been developed to secure the network infrastructure and communication over the Internet. Intrusion detection is a relatively new addition to such techniques. Intrusion detection systems (IDS) are used to find out if someone has intrusion into or is trying to get it the network. One big problem is amount of Intrusion which is increasing day by day. We need to know about network attack information using IDS, then analysing the effect. Due to the nature of IDSs which are solely signature based, every new intrusion cannot be detected; so it is important to introduce artificial intelligence (AI) methods / techniques in IDS. Introduction of AI necessitates the importance of normalization in intrusions. This work is focused on classification of AI based IDS techniques which will help better design intrusion detection systems in the future. We have also proposed a support vector machine for IDS to detect Smurf attack with much reliable accuracy.

  19. Artificial intelligence for multi-mission planetary operations

    Science.gov (United States)

    Atkinson, David J.; Lawson, Denise L.; James, Mark L.

    1990-01-01

    A brief introduction is given to an automated system called the Spacecraft Health Automated Reasoning Prototype (SHARP). SHARP is designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for evaluation of the prototype in a real-time operations setting during the Voyager spacecraft encounter with Neptune in August, 1989. The preliminary results of the SHARP project and plans for future application of the technology are discussed.

  20. Implementing Artificial Intelligence Behaviors in a Virtual World

    Science.gov (United States)

    Krisler, Brian; Thome, Michael

    2012-01-01

    In this paper, we will present a look at the current state of the art in human-computer interface technologies, including intelligent interactive agents, natural speech interaction and gestural based interfaces. We describe our use of these technologies to implement a cost effective, immersive experience on a public region in Second Life. We provision our Artificial Agents as a German Shepherd Dog avatar with an external rules engine controlling the behavior and movement. To interact with the avatar, we implemented a natural language and gesture system allowing the human avatars to use speech and physical gestures rather than interacting via a keyboard and mouse. The result is a system that allows multiple humans to interact naturally with AI avatars by playing games such as fetch with a flying disk and even practicing obedience exercises using voice and gesture, a natural seeming day in the park.

  1. An intercomparison of artificial intelligence approaches for polar scene identification

    Science.gov (United States)

    Tovinkere, V. R.; Penaloza, M.; Logar, A.; Lee, J.; Weger, R. C.; Berendes, T. A.; Welch, R. M.

    1993-01-01

    The following six different artificial-intelligence (AI) approaches to polar scene identification are examined: (1) a feed forward back propagation neural network, (2) a probabilistic neural network, (3) a hybrid neural network, (4) a 'don't care' feed forward perception model, (5) a 'don't care' feed forward back propagation neural network, and (6) a fuzzy logic based expert system. The ten classes into which six AVHRR local-coverage arctic scenes were classified were: water, solid sea ice, broken sea ice, snow-covered mountains, land, stratus over ice, stratus over water, cirrus over water, cumulus over water, and multilayer cloudiness. It was found that 'don't care' back propagation neural network produced the highest accuracies. This approach has also low CPU requirement.

  2. SWARM INTELLIGENCE FROM NATURAL TO ARTIFICIAL SYSTEMS: ANT COLONY OPTIMIZATION

    Directory of Open Access Journals (Sweden)

    O. Deepa

    2016-03-01

    Full Text Available Successful applications coming from biologically inspired algorithm like Ant Colony Optimization (ACO based on artificial swarm intelligence which is inspired by the collective behavior of social insects. ACO has been inspired from natural ants system, their behavior, team coordination, synchronization for the searching of optimal solution and also maintains information of each ant. At present, ACO has emerged as a leading metaheuristic technique for the solution of combinatorial optimization problems which can be used to find shortest path through construction graph. This paper describe about various behavior of ants, successfully used ACO algorithms, applications and current trends. In recent years, some researchers have also focused on the application of ACO algorithms to design of wireless communication network, bioinformatics problem, dynamic problem and multi-objective problem.

  3. The use of artificial intelligence for safeguard fuel reprocessing plants

    International Nuclear Information System (INIS)

    Recorded process data from minirun campaigns conducted at the Barnwell Nuclear Fuels Plant have been utilized to study the suitability of computer-based artificial intelligence (AI) methods for process monitoring for safeguards purposes. The techniques of knowledge engineering were used to formulate the decision-making software. The computer software accepted as input process data customarily used for process operations that had previously been recorded on magnetic tape during the 1980 miniruns. The OPS5 AI language was used to construct an expert system for simulated monitoring of the process. Such expert systems facilitate the employment of the heuristic reasoning used by human observers to form reasoned conclusions from incomplete, inaccurate, or otherwise fuzzy data

  4. Artificial intelligence in the service of system administrators

    CERN Document Server

    Haen, Christophe; Bonaccorsi, E; Neufeld, N

    2012-01-01

    The LHCb online system relies on a large and heterogeneous IT infrastructure made from thousands of servers on which many different applications are running. They run a great variety of tasks: critical ones such as data taking and secondary ones like web servers. The administration of such a system and making sure it is working properly represents a very important workload for the small expert-operator team. Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called self objectives supposed to lead to autonomic computing. In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way Linux-based systems and their interaction with software. Moreover, the multi agent approach we use, coupled with an object oriented paradigm architecture should increase our learning speed a lot and highlight relations between problems.

  5. Damage Detection in a Composite Plate Using Modal Analysis and Artificial Intelligence

    Science.gov (United States)

    Nasiri, M. R.; Mahjoob, M. J.; Aghakasiri, A.

    2011-12-01

    The use of composite materials has vastly increased in recent years. Great interest is therefore developed in the damage detection of composites using non-destructive test methods. Several approaches have been applied to obtain information about the existence, location and growth of the faults. The main goal in this paper is to use the vibration response of a composite plate to detect and localize delamination defect based on the frequency response and modal analysis. The features extracted are used as the input data in an artificial intelligence scheme to identify the severity of the damages. Experiments are then conducted to validate the developed model.

  6. Smart Artificial Intelligence Computerized Models for Shelf Life Prediction of Processed Cheese

    Directory of Open Access Journals (Sweden)

    Sumit Goyal

    2012-06-01

    Full Text Available Linear Layer (Design and multiple linear regression artificial intelligence computerized models were developed for predicting shelf life of processed cheese stored at 7-8ºC. Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash - Sutcliffo Coefficient were applied for comparing the prediction ability of the developed models. The modelling results showed excellent agreement between the experimental data and predicted values with a high determination coefficient, suggesting that the Linear Layer (Design and MLR models are very efficient in predicting the shelf life of processed cheese stored at 7-8oC.

  7. Modeling river total bed material load discharge using artificial intelligence approaches (based on conceptual inputs)

    Science.gov (United States)

    Roushangar, Kiyoumars; Mehrabani, Fatemeh Vojoudi; Shiri, Jalal

    2014-06-01

    This study presents Artificial Intelligence (AI)-based modeling of total bed material load through developing the accuracy level of the predictions of traditional models. Gene expression programming (GEP) and adaptive neuro-fuzzy inference system (ANFIS)-based models were developed and validated for estimations. Sediment data from Qotur River (Northwestern Iran) were used for developing and validation of the applied techniques. In order to assess the applied techniques in relation to traditional models, stream power-based and shear stress-based physical models were also applied in the studied case. The obtained results reveal that developed AI-based models using minimum number of dominant factors, give more accurate results than the other applied models. Nonetheless, it was revealed that k-fold test is a practical but high-cost technique for complete scanning of applied data and avoiding the over-fitting.

  8. River Trip Optimization Scheduling Based on Artificial Intelligence Simulation and the Bee-Swarm Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Zhan Wenting

    2012-09-01

    Full Text Available The study on the impacts of human activities on natural resources is of critical importance in constructing effective management strategies in rafting trips. The Camping Schedule Intelligent Generator (CSIG, the computer program developed in the study, which successfully models the complex, dynamic human-environment interactions in the rafting river. This generator includes two parts: artificial intelligence simulation and BSGA-based Optimization. It employs artificial intelligence in creating an individual-based modeling system. With the help of BSGA, this simulation system successfully models the recreatinal rafting behavior and captures the decision making of rafting trips as they responsively seek to optimize their functions. After modeling, the paper applys CSIG to the Colorado River, which is a famous rafting river and find that: the numbers of short motor-trips (6-8 day and long-oar trips (15-18 day are obviously larger than the other two. Finally, the study analyzes the sensitivity of the model and finds that when the water velocity varies in the actual range.

  9. Predicting chick body mass by artificial intelligence-based models

    Directory of Open Access Journals (Sweden)

    Patricia Ferreira Ponciano Ferraz

    2014-07-01

    Full Text Available The objective of this work was to develop, validate, and compare 190 artificial intelligence-based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside four climate-controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21-day-old chicks - with the variables dry-bulb air temperature, duration of thermal stress (days, chick age (days, and the daily body mass of chicks - was used for network training, validation, and tests of models based on artificial neural networks (ANNs and neuro-fuzzy networks (NFNs. The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The ANNs enable the simulation of different scenarios, which can assist in managerial decision-making, and they can be embedded in the heating control systems.

  10. An application of artificial intelligence for rainfall–runoff modeling

    Indian Academy of Sciences (India)

    Ali Aytek; M Asce; Murat Alp

    2008-04-01

    This study proposes an application of two techniques of artificial intelligence (AI) for rainfall–runoff modeling: the artificial neural networks (ANN) and the evolutionary computation (EC). Two different ANN techniques, the feed forward back propagation (FFBP) and generalized regression neural network (GRNN) methods are compared with one EC method, Gene Expression Programming (GEP) which is a new evolutionary algorithm that evolves computer programs. The daily hydrometeorological data of three rainfall stations and one streamflow station for Juniata River Basin in Pennsylvania state of USA are taken into consideration in the model development. Statistical parameters such as average, standard deviation, coefficient of variation, skewness, minimum and maximum values, as well as criteria such as mean square error (MSE) and determination coefficient (2) are used to measure the performance of the models. The results indicate that the proposed genetic programming (GP) formulation performs quite well compared to results obtained by ANNs and is quite practical for use. It is concluded from the results that GEP can be proposed as an alternative to ANN models.

  11. Improved RMR Rock Mass Classification Using Artificial Intelligence Algorithms

    Science.gov (United States)

    Gholami, Raoof; Rasouli, Vamegh; Alimoradi, Andisheh

    2013-09-01

    Rock mass classification systems such as rock mass rating (RMR) are very reliable means to provide information about the quality of rocks surrounding a structure as well as to propose suitable support systems for unstable regions. Many correlations have been proposed to relate measured quantities such as wave velocity to rock mass classification systems to limit the associated time and cost of conducting the sampling and mechanical tests conventionally used to calculate RMR values. However, these empirical correlations have been found to be unreliable, as they usually overestimate or underestimate the RMR value. The aim of this paper is to compare the results of RMR classification obtained from the use of empirical correlations versus machine-learning methodologies based on artificial intelligence algorithms. The proposed methods were verified based on two case studies located in northern Iran. Relevance vector regression (RVR) and support vector regression (SVR), as two robust machine-learning methodologies, were used to predict the RMR for tunnel host rocks. RMR values already obtained by sampling and site investigation at one tunnel were taken into account as the output of the artificial networks during training and testing phases. The results reveal that use of empirical correlations overestimates the predicted RMR values. RVR and SVR, however, showed more reliable results, and are therefore suggested for use in RMR classification for design purposes of rock structures.

  12. Comparison of three artificial intelligence techniques for discharge routing

    Science.gov (United States)

    Khatibi, Rahman; Ghorbani, Mohammad Ali; Kashani, Mahsa Hasanpour; Kisi, Ozgur

    2011-06-01

    SummaryThe inter-comparison of three artificial intelligence (AI) techniques are presented using the results of river flow/stage timeseries, that are otherwise handled by traditional discharge routing techniques. These models comprise Artificial Neural Network (ANN), Adaptive Nero-Fuzzy Inference System (ANFIS) and Genetic Programming (GP), which are for discharge routing of Kizilirmak River, Turkey. The daily mean river discharge data with a period between 1999 and 2003 were used for training and testing the models. The comparison includes both visual and parametric approaches using such statistic as Coefficient of Correlation (CC), Mean Absolute Error (MAE) and Mean Square Relative Error (MSRE), as well as a basic scoring system. Overall, the results indicate that ANN and ANFIS have mixed fortunes in discharge routing, and both have different abilities in capturing and reproducing some of the observed information. However, the performance of GP displays a better edge over the other two modelling approaches in most of the respects. Attention is given to the information contents of recorded timeseries in terms of their peak values and timings, where one performance measure may capture some of the information contents but be ineffective in others. Thus, this makes a case for compiling knowledge base for various modelling techniques.

  13. ARTIFICIAL INTELLIGENCE IN SPORTS BIOMECHANICS: NEW DAWN OR FALSE HOPE?

    Directory of Open Access Journals (Sweden)

    Roger Bartlett

    2006-12-01

    Full Text Available This article reviews developments in the use of Artificial Intelligence (AI in sports biomechanics over the last decade. It outlines possible uses of Expert Systems as diagnostic tools for evaluating faults in sports movements ('techniques' and presents some example knowledge rules for such an expert system. It then compares the analysis of sports techniques, in which Expert Systems have found little place to date, with gait analysis, in which they are routinely used. Consideration is then given to the use of Artificial Neural Networks (ANNs in sports biomechanics, focusing on Kohonen self-organizing maps, which have been the most widely used in technique analysis, and multi-layer networks, which have been far more widely used in biomechanics in general. Examples of the use of ANNs in sports biomechanics are presented for javelin and discus throwing, shot putting and football kicking. I also present an example of the use of Evolutionary Computation in movement optimization in the soccer throw in, which predicted an optimal technique close to that in the coaching literature. After briefly overviewing the use of AI in both sports science and biomechanics in general, the article concludes with some speculations about future uses of AI in sports biomechanics.

  14. Demonstrating artificial intelligence for space systems - Integration and project management issues

    Science.gov (United States)

    Hack, Edmund C.; Difilippo, Denise M.

    1990-01-01

    As part of its Systems Autonomy Demonstration Project (SADP), NASA has recently demonstrated the Thermal Expert System (TEXSYS). Advanced real-time expert system and human interface technology was successfully developed and integrated with conventional controllers of prototype space hardware to provide intelligent fault detection, isolation, and recovery capability. Many specialized skills were required, and responsibility for the various phases of the project therefore spanned multiple NASA centers, internal departments and contractor organizations. The test environment required communication among many types of hardware and software as well as between many people. The integration, testing, and configuration management tools and methodologies which were applied to the TEXSYS project to assure its safe and successful completion are detailed. The project demonstrated that artificial intelligence technology, including model-based reasoning, is capable of the monitoring and control of a large, complex system in real time.

  15. Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

    Science.gov (United States)

    Broderick, Ron

    1997-01-01

    The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network

  16. Virtual Reality for Artificial Intelligence: human-centered simulation for social science.

    Science.gov (United States)

    Cipresso, Pietro; Riva, Giuseppe

    2015-01-01

    There is a long last tradition in Artificial Intelligence as use of Robots endowing human peculiarities, from a cognitive and emotional point of view, and not only in shape. Today Artificial Intelligence is more oriented to several form of collective intelligence, also building robot simulators (hardware or software) to deeply understand collective behaviors in human beings and society as a whole. Modeling has also been crucial in the social sciences, to understand how complex systems can arise from simple rules. However, while engineers' simulations can be performed in the physical world using robots, for social scientist this is impossible. For decades, researchers tried to improve simulations by endowing artificial agents with simple and complex rules that emulated human behavior also by using artificial intelligence (AI). To include human beings and their real intelligence within artificial societies is now the big challenge. We present an hybrid (human-artificial) platform where experiments can be performed by simulated artificial worlds in the following manner: 1) agents' behaviors are regulated by the behaviors shown in Virtual Reality involving real human beings exposed to specific situations to simulate, and 2) technology transfers these rules into the artificial world. These form a closed-loop of real behaviors inserted into artificial agents, which can be used to study real society. PMID:26799903

  17. A Modular Artificial Intelligence Inference Engine System (MAIS) for support of on orbit experiments

    Science.gov (United States)

    Hancock, Thomas M., III

    1994-01-01

    This paper describes a Modular Artificial Intelligence Inference Engine System (MAIS) support tool that would provide health and status monitoring, cognitive replanning, analysis and support of on-orbit Space Station, Spacelab experiments and systems.

  18. Color Regeneration from Reflective Color Sensor Using an Artificial Intelligent Technique

    OpenAIRE

    Hayriye Altural; Ömer Galip Saracoglu

    2010-01-01

    A low-cost optical sensor based on reflective color sensing is presented. Artificial neural network models are used to improve the color regeneration from the sensor signals. Analog voltages of the sensor are successfully converted to RGB colors. The artificial intelligent models presented in this work enable color regeneration from analog outputs of the color sensor. Besides, inverse modeling supported by an intelligent technique enables the sensor probe for use of a colorimetric sensor that...

  19. Cognitive communications distributed artificial intelligence (DAI), regulatory policy and economics, implementation

    CERN Document Server

    Grace, David

    2012-01-01

    This book discusses in-depth the concept of distributed artificial intelligence (DAI) and its application to cognitive communications In this book, the authors present an overview of cognitive communications, encompassing both cognitive radio and cognitive networks, and also other application areas such as cognitive acoustics. The book also explains the specific rationale for the integration of different forms of distributed artificial intelligence into cognitive communications, something which is often neglected in many forms of technical contributions available today. Furthermore, t

  20. Enaction-Based Artificial Intelligence: Toward Co-evolution with Humans in the Loop

    OpenAIRE

    De Loor, Pierre; Manac'H, Kristen; Tisseau, Jacques

    2009-01-01

    This article deals with the links between the enaction paradigm and artificial intelligence. Enaction is considered a metaphor for artificial intelligence, as a number of the notions which it deals with are deemed incompatible with the phenomenal field of the virtual. After explaining this stance, we shall review previous works regarding this issue in terms of artifical life and robotics. We shall focus on the lack of recognition of co-evolution at the heart of these approaches. We propose to...

  1. The application of neural networks with artificial intelligence technique in the modeling of industrial processes

    International Nuclear Information System (INIS)

    Neural networks are a relatively new artificial intelligence technique that emulates the behavior of biological neural systems in digital software or hardware. These networks can 'learn', automatically, complex relationships among data. This feature makes the technique very useful in modeling processes for which mathematical modeling is difficult or impossible. The work described here outlines some examples of the application of neural networks with artificial intelligence technique in the modeling of industrial processes.

  2. Analysis on the Application of Artificial Intelligence Technology in Modern Physical Education

    OpenAIRE

    Yipai Jiang

    2014-01-01

    In this study, the artificial intelligence and modern technology of physical education have researched and discussed which in order to provide the ideal theoretical basis for the modern technology of physical construction and development. As we all know, artificial intelligence belongs to a strong frontier disciplines which is developing but also one of the main direction of the computer and its related technologies interdisciplinary research, influencing the entire teaching progress. Artific...

  3. The 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies

    Science.gov (United States)

    Hostetter, Carl F. (Editor)

    1995-01-01

    This publication comprises the papers presented at the 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland, on May 9-11, 1995. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

  4. On-line fault diagnosis of industrial processes based on artificial intelligence techniques

    OpenAIRE

    Calado, J. M. F.

    1996-01-01

    In this research the application of artificial intelligence techniques for on-line process control and fault detection and diagnosis are investigated. The majority of the research is on using artificial intelligence techniques in on-line fault detection and diagnosis of industrial processes. Several on-line approaches, including a rule based controller and several fault detection and diagnosis systems, have been developed and implemented and are described throughout this thesis. The research ...

  5. On the Future Possibilities of Artificial Intelligence Based M-Learning Content Development

    OpenAIRE

    KÖSE, Utku; TÜFEKÇİ, Aslıhan

    2015-01-01

    Abstract—Artificial Intelligence is widely used in almost every field of the modern life; in order to provide effective solutions for real-world problems. It can be definitely said that this research field has a remarkable power on shaping the future of the humankind. When we take today's technologies into consideration, it is also seen that usage of Artificial Intelligence and mobile applications together is a key element for many future applications. At this point, main objective of this st...

  6. Reports on the Twenty-First National Conference on Artificial Intelligence (AAAI-06) Workshop Program

    OpenAIRE

    Achtner, Wolfgang; Aimeur , Esma; Anand, Sarabjot Singh; Appelt, Doug; Ashish, Naveen; Barnes, Tiffany; Beck, Joseph E.; Dias, M. Bernardine; Doshi, Prashant; Drummond, Chris; Elazmeh, William; Felner, Ariel; Freitag, Dayne; Geffner, Hector; Geib, Christopher W.

    2006-01-01

    The Workshop program of the Twenty-First Conference on Artificial Intelligence was held July 16-17, 2006 in Boston, Massachusetts. The program was chaired by Joyce Chai and Keith Decker. The titles of the 17 workshops were AIDriven Technologies for Service-Oriented Computing; Auction Mechanisms for Robot Coordination; Cognitive Modeling and Agent-Based Social Simulations, Cognitive Robotics; Computational Aesthetics: Artificial Intelligence Approaches to Beauty and Happiness; Educational Data...

  7. On Super-Turing Computing Power and Hierarchies of Artificial General Intelligence Systems

    Czech Academy of Sciences Publication Activity Database

    Wiedermann, Jiří

    Amsterdam: Atlantis Press, 2010 - (Baum, E.; Hutter, M.; Kitzelmann, E.), s. 196-197 ISBN 978-90-78677-36-9. [AGI 2010. International Conference on Artificial General Intelligence /3./. Lugano (CH), 05.03.2010-08.03.2010] R&D Projects: GA ČR GAP202/10/1333 Institutional research plan: CEZ:AV0Z10300504 Keywords : artificial intelligence * non-uniform complexity * hierarchy Subject RIV: IN - Informatics, Computer Science

  8. The Workshop Program at the Nineteenth National Conference on Artificial Intelligence

    OpenAIRE

    Muslea, Ion; Dignum, Virginia; Corkill, Daniel; Jonker, Catholijn; Dignum, Frank; Coradeschi, Silvia; Saffiotti, Alessandro; Fu, Dan; Orkin, Jeff; Cheetham, William E.; Goebel, Kai; Bonissone, Piero; Soh, Leen-Kiat; Jones, Randolph M.; Wray, Robert E.

    2005-01-01

    AAAI presented the AAAI-04 workshop program on July 25-26, 2004 in San Jose, California. This program included twelve workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were as follows: (1) Adaptive Text Extraction and Mining; (2) Agent Organizations: Theory and Practice; (3) Anchoring Symbols to Sensor Data; (4) Challenges in Game AI; (5) Fielding Applications of Artificial Intelligence; (6) Forming and Maintaining Coalitions in Adaptive Multiag...

  9. ARTIFICIAL INTELLIGENCE SELECTION WITH CAPABILITY OF EDITING A NEW PARAMETER FOR EOR SCREENING CRITERIA

    OpenAIRE

    ELRADI ABASS; CHENG LIN SONG

    2011-01-01

    This paper describes the application of an Artificial Intelligence (AI) technique to assist in the selection of an Enhanced Oil Recovery method (EOR). The structure of an expert systems selection based on a new formulated screening criteria, Artificial Intelligence selection developed by a computer software called (EKORA), with an easily and friendly user interface by using visual Basic-6 environment tools is presented. An additional capability provided by this software is the ability of chan...

  10. Analysis of Boiler Operational Variables Prior to Tube Leakage Fault by Artificial Intelligent System

    OpenAIRE

    Al-Kayiem Hussain H.; Al-Naimi Firas B. I.; Amat Wan N. Bt Wan

    2014-01-01

    Steam boilers are considered as a core of any steam power plant. Boilers are subjected to various types of trips leading to shut down of the entire plant. The tube leakage is the worse among the common boiler faults, where the shutdown period lasts for around four to five days. This paper describes the rules of the Artificial Intelligent Systems to diagnosis the boiler variables prior to tube leakage occurrence. An Intelligent system based on Artificial Neural Network was designed and coded i...

  11. Towards common-sense reasoning via conditional simulation: legacies of Turing in Artificial Intelligence

    OpenAIRE

    Freer, Cameron E.; Roy, Daniel M.; Tenenbaum, Joshua B.

    2012-01-01

    The problem of replicating the flexibility of human common-sense reasoning has captured the imagination of computer scientists since the early days of Alan Turing's foundational work on computation and the philosophy of artificial intelligence. In the intervening years, the idea of cognition as computation has emerged as a fundamental tenet of Artificial Intelligence (AI) and cognitive science. But what kind of computation is cognition? We describe a computational formalism centered around a ...

  12. Applications of artificial intelligence V; Proceedings of the Meeting, Orlando, FL, May 18-20, 1987

    Science.gov (United States)

    Gilmore, John F. (Editor)

    1987-01-01

    The papers contained in this volume focus on current trends in applications of artificial intelligence. Topics discussed include expert systems, image understanding, artificial intelligence tools, knowledge-based systems, heuristic systems, manufacturing applications, and image analysis. Papers are presented on expert system issues in automated, autonomous space vehicle rendezvous; traditional versus rule-based programming techniques; applications to the control of optional flight information; methodology for evaluating knowledge-based systems; and real-time advisory system for airborne early warning.

  13. Text Analytics: the convergence of Big Data and Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Antonio Moreno

    2016-03-01

    Full Text Available The analysis of the text content in emails, blogs, tweets, forums and other forms of textual communication constitutes what we call text analytics. Text analytics is applicable to most industries: it can help analyze millions of emails; you can analyze customers’ comments and questions in forums; you can perform sentiment analysis using text analytics by measuring positive or negative perceptions of a company, brand, or product. Text Analytics has also been called text mining, and is a subcategory of the Natural Language Processing (NLP field, which is one of the founding branches of Artificial Intelligence, back in the 1950s, when an interest in understanding text originally developed. Currently Text Analytics is often considered as the next step in Big Data analysis. Text Analytics has a number of subdivisions: Information Extraction, Named Entity Recognition, Semantic Web annotated domain’s representation, and many more. Several techniques are currently used and some of them have gained a lot of attention, such as Machine Learning, to show a semisupervised enhancement of systems, but they also present a number of limitations which make them not always the only or the best choice. We conclude with current and near future applications of Text Analytics.

  14. Artificial intelligence in the service of system administrators

    International Nuclear Information System (INIS)

    The LHCb online system relies on a large and heterogeneous IT infrastructure made from thousands of servers on which many different applications are running. They run a great variety of tasks: critical ones such as data taking and secondary ones like web servers. The administration of such a system and making sure it is working properly represents a very important workload for the small expert-operator team. Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called “self objectives” supposed to lead to “autonomic computing”. In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way Linux-based systems and their interaction with software. Moreover, the multi agent approach we use, coupled with an “object oriented paradigm” architecture should increase our learning speed a lot and highlight relations between problems.

  15. Artificial Intelligence (AI) Based Tactical Guidance for Fighter Aircraft

    Science.gov (United States)

    McManus, John W.; Goodrich, Kenneth H.

    1990-01-01

    A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range (WVR) air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS), a second generation TDG, is presented. The Knowledge-Based Systems used by CLAWS to aid in the tactical decision-making process are outlined in detail, and the results of tests to evaluate the performance of CLAWS versus a baseline TDG developed in FORTRAN to run in real-time in the Langley Differential Maneuvering Simulator (DMS), are presented. To date, these test results have shown significant performance gains with respect to the TDG baseline in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify and maintain than the baseline FORTRAN TDG programs. Alternate computing environments and programming approaches, including the use of parallel algorithms and heterogeneous computer networks are discussed, and the design and performance of a prototype concurrent TDG system are presented.

  16. Parameter tuning of PVD process based on artificial intelligence technique

    Science.gov (United States)

    Norlina, M. S.; Diyana, M. S. Nor; Mazidah, P.; Rusop, M.

    2016-07-01

    In this study, an artificial intelligence technique is proposed to be implemented in the parameter tuning of a PVD process. Due to its previous adaptation in similar optimization problems, genetic algorithm (GA) is selected to optimize the parameter tuning of the RF magnetron sputtering process. The most optimized parameter combination obtained from GA's optimization result is expected to produce the desirable zinc oxide (ZnO) thin film from the sputtering process. The parameters involved in this study were RF power, deposition time and substrate temperature. The algorithm was tested to optimize the 25 datasets of parameter combinations. The results from the computational experiment were then compared with the actual result from the laboratory experiment. Based on the comparison, GA had shown that the algorithm was reliable to optimize the parameter combination before the parameter tuning could be done to the RF magnetron sputtering machine. In order to verify the result of GA, the algorithm was also been compared to other well known optimization algorithms, which were, particle swarm optimization (PSO) and gravitational search algorithm (GSA). The results had shown that GA was reliable in solving this RF magnetron sputtering process parameter tuning problem. GA had shown better accuracy in the optimization based on the fitness evaluation.

  17. Crack identification based on synthetic artificial intelligent technique

    Energy Technology Data Exchange (ETDEWEB)

    Shim, Mun Bo; Suh, Myung Won [Sungkyunkwan Univ., Suwon (Korea, Republic of)

    2001-07-01

    It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a Continuous Evolutionary Algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

  18. Implementing embedded artificial intelligence rules within algorithmic programming languages

    Science.gov (United States)

    Feyock, Stefan

    1988-01-01

    Most integrations of artificial intelligence (AI) capabilities with non-AI (usually FORTRAN-based) application programs require the latter to execute separately to run as a subprogram or, at best, as a coroutine, of the AI system. In many cases, this organization is unacceptable; instead, the requirement is for an AI facility that runs in embedded mode; i.e., is called as subprogram by the application program. The design and implementation of a Prolog-based AI capability that can be invoked in embedded mode are described. The significance of this system is twofold: Provision of Prolog-based symbol-manipulation and deduction facilities makes a powerful symbolic reasoning mechanism available to applications programs written in non-AI languages. The power of the deductive and non-procedural descriptive capabilities of Prolog, which allow the user to describe the problem to be solved, rather than the solution, is to a large extent vitiated by the absence of the standard control structures provided by other languages. Embedding invocations of Prolog rule bases in programs written in non-AI languages makes it possible to put Prolog calls inside DO loops and similar control constructs. The resulting merger of non-AI and AI languages thus results in a symbiotic system in which the advantages of both programming systems are retained, and their deficiencies largely remedied.

  19. An artificial intelligence approach in designing new materials

    Directory of Open Access Journals (Sweden)

    W. Sitek

    2006-04-01

    Full Text Available Purpose: The paper presents the computer aided method of chemical composition designing the metallic materials with a required property.Design/methodology/approach: The purpose has been achieved in two stages. In the first stage a neural network model for calculating the Jominy curve on the basis of the chemical composition has been worked out. This model made possible to prepare, in the second stage, a representative set of data and to work out the neural classifier that would aid the selection of steel grade with the required hardenability.Findings: Obtained results show that AI tools used are effective and very useful in designing new metallic materials.Research limitations/implications: The presented models may be used in the ranges of mass concentrations of alloying elements presented in the paper. The methodology presented in the paper makes it possible to add new grades of steel to the models.Practical implications: The worked out models may be used in computer systems of steel selection and designing for the heat-treated machine parts.Originality/value: The use of the artificial intelligence method, particularly the neural networks as a tool for designing the chemical composition of steels with the required properties.

  20. Artificial intelligence applications to design validation and sneak function analysis

    International Nuclear Information System (INIS)

    An objective of the US space reactor program is to design systems with high reliability and safety of control over long operating lifetimes. Argonne National Laboratory (ANL) is a participant in the National Man-Machine Integration (MMI) program for Liquid Metal Fast Breeder Reactors (LMFBR). A purpose of this program is to promote the development of concepts and technologies that enhance the operational safety and reliability of fast-breeder reactors. Much of the work is directly applicable to the space reactor program. This paper reports on one of the MMI projects being developed by ANL. The project reported pertains to an automated system that demonstrates the use of artificial intelligence (AI) for design validation (DA) and sneak function analysis (SFA). The AI system models the design specification and the physical design of the cooling process assigned to the Argon Cooling System (ACS) at Experimental Breeder Reactor II (EBR-II). The models are developed using heuristic knowledge and natural laws. 13 refs

  1. Integrating artificial and human intelligence into tablet production process.

    Science.gov (United States)

    Gams, Matjaž; Horvat, Matej; Ožek, Matej; Luštrek, Mitja; Gradišek, Anton

    2014-12-01

    We developed a new machine learning-based method in order to facilitate the manufacturing processes of pharmaceutical products, such as tablets, in accordance with the Process Analytical Technology (PAT) and Quality by Design (QbD) initiatives. Our approach combines the data, available from prior production runs, with machine learning algorithms that are assisted by a human operator with expert knowledge of the production process. The process parameters encompass those that relate to the attributes of the precursor raw materials and those that relate to the manufacturing process itself. During manufacturing, our method allows production operator to inspect the impacts of various settings of process parameters within their proven acceptable range with the purpose of choosing the most promising values in advance of the actual batch manufacture. The interaction between the human operator and the artificial intelligence system provides improved performance and quality. We successfully implemented the method on data provided by a pharmaceutical company for a particular product, a tablet, under development. We tested the accuracy of the method in comparison with some other machine learning approaches. The method is especially suitable for analyzing manufacturing processes characterized by a limited amount of data. PMID:24970587

  2. Letter to the Editor: Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter

    OpenAIRE

    Russell, Stuart; University of California, Berkeley; Dietterich, Tom; Oregon State University; Horvitz, Eric; Microsoft; Selman, Bart; Cornell University; Rossi, Francesca; University of Padova; Hassabis, Demis; DeepMind; Legg, Shane; DeepMind; Suleyman, Mustafa; DeepMind; George, Dileep; Vicarious; Phoenix, Scott; Vicarious

    2015-01-01

    Artificial intelligence (AI) research has explored a variety of problems and approaches since its inception, but for the last 20 years or so has been focused on the problems surrounding the construction of intelligent agents — systems that perceive and act in some environment. In this context, "intelligence" is related to statistical and economic notions of rationality — colloquially, the ability to make good decisions, plans, or inferences. The adoption of probabilistic and decision-theoreti...

  3. On the track of Artificial Intelligence: Learning with Intelligent Personal Assistants

    Directory of Open Access Journals (Sweden)

    Nil Goksel Canbek

    2016-01-01

    Full Text Available In a technology dominated world, useful and timely information can be accessed quickly via Intelligent Personal Assistants (IPAs.  By the use of these assistants built into mobile operating systems, daily electronic tasks of a user can be accomplished 24/7. Such tasks like taking dictation, getting turn-by-turn directions, vocalizing email messages, reminding daily appointments, setting reminders, responding any factual questions and invoking apps can be completed by  IPAs such as Apple’s Siri, Google Now and Microsoft Cortana. The mentioned assistants programmed within Artificial Intelligence (AI do create an interaction between human and computer through a natural language used in digital communication. In this regard, the overall purpose of this study is to examine the potential use of IPAs that use advanced cognitive computing technologies and Natural Language Processing (NLP for learning. To achieve this purpose, the working system of IPAs is reviewed briefly within the scope of AI that has recently become smarter to predict, comprehend and carry out multi-step and complex requests of users.

  4. Artificial Neural Network applied to lightning flashes

    Science.gov (United States)

    Gin, R. B.; Guedes, D.; Bianchi, R.

    2013-05-01

    The development of video cameras enabled cientists to study lightning discharges comportment with more precision. The main goal of this project is to create a system able to detect images of lightning discharges stored in videos and classify them using an Artificial Neural Network (ANN)using C Language and OpenCV libraries. The developed system, can be split in two different modules: detection module and classification module. The detection module uses OpenCV`s computer vision libraries and image processing techniques to detect if there are significant differences between frames in a sequence, indicating that something, still not classified, occurred. Whenever there is a significant difference between two consecutive frames, two main algorithms are used to analyze the frame image: brightness and shape algorithms. These algorithms detect both shape and brightness of the event, removing irrelevant events like birds, as well as detecting the relevant events exact position, allowing the system to track it over time. The classification module uses a neural network to classify the relevant events as horizontal or vertical lightning, save the event`s images and calculates his number of discharges. The Neural Network was implemented using the backpropagation algorithm, and was trained with 42 training images , containing 57 lightning events (one image can have more than one lightning). TheANN was tested with one to five hidden layers, with up to 50 neurons each. The best configuration achieved a success rate of 95%, with one layer containing 20 neurons (33 test images with 42 events were used in this phase). This configuration was implemented in the developed system to analyze 20 video files, containing 63 lightning discharges previously manually detected. Results showed that all the lightning discharges were detected, many irrelevant events were unconsidered, and the event's number of discharges was correctly computed. The neural network used in this project achieved a

  5. Identification of Age, Temperature and Radiation Effect on Ferritic Steel Microstructure Based on Artificial Intelligence

    International Nuclear Information System (INIS)

    In the construction of nuclear installation, it is important to know the material condition used on it. Considering mechanical properties of these materials, there are some material change affected by ageing, temperature and radiation. For some years, austenitic stainless steel are used as a fuel cladding in fast breeder reactor. However this material will not sufficiently competitive from economic point of view for the next year. Experiment result on ferritic steel gave information of stronger structural properties compared to austenitic stainless steel. Modeling and simulation will support further identification of this material changing caused by such effects. Pattern recognition of these changes base on artificial intelligence is expected to support the research and development activities on nuclear structure materials. Material structure pattern of these materials, observed by SEM, are converted using image processing system. Its characteristic is then analyzed with principal component using perception method, which usually used on identifying and learning neural network system based on artificial intelligence. Specific design and input are needed to identify the change of material structure pattern before and after any applied effect. In this paper, simulation of changing identification on three types ferritic steel F17(17 Cr), EM 12 (9 CR-2 MoNbV), and EMI 0 (9 Cr-I Mo) were done. The microstructure data before and after effect are taken from some references. The whole pattern recognition process are done using MATLAB software package. (author)

  6. GDO Artificial Intelligence-Based Switching PID Baseline Feedback Linearization Method: Controlled PUMA Workspace

    Directory of Open Access Journals (Sweden)

    Farzin Piltan

    2012-10-01

    Full Text Available Congetive method is used in this research to create portfilo of movement robot manipulator. Gradient descent (GD artificial intelligence based switching feedback linearization controller was used and robot’s postures and trajectory were expected in MATLAB/SIMULINK environment. Feedback linearization controller (CTC is an influential nonlinear controller to certain systems which it is based on feedback linearization and computes the required torques using the nonlinear feedback control law in certain systems. Practically a large amount of systems have uncertainties accordingly this method has a challenge. Switching feedback linearization controller is a significant combination nonlinear stable-robust controller under condition of partly uncertain dynamic parameters of system. This technique is used to control of highly nonlinear systems especially in nonlinear time varient nonlinear dynamic system. To increase the stability and robustness with regards to improve the robustness switching methodology is applied to feedback linearization controller. Lyapunov stability is proved in proposed controller based on switching function. To compensate for the dependence on switching parameters baseline methodology is used.The nonlinear model dynamic formulation problem in uncertain system can be solved by using artificial intelligence theorem. Fuzzy logic theory is used to estimate the system dynamic. Forward kinematics implemented the manipulator's movements. Results validated the robot's range of possible postures and trajectories.

  7. Modeling Common-Sense Decisions in Artificial Intelligence

    Science.gov (United States)

    Zak, Michail

    2010-01-01

    A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation

  8. Integration of artificial intelligence and numerical optimization techniques for the design of complex aerospace systems

    International Nuclear Information System (INIS)

    A new software system called Engineous combines artificial intelligence and numerical methods for the design and optimization of complex aerospace systems. Engineous combines the advanced computational techniques of genetic algorithms, expert systems, and object-oriented programming with the conventional methods of numerical optimization and simulated annealing to create a design optimization environment that can be applied to computational models in various disciplines. Engineous has produced designs with higher predicted performance gains that current manual design processes - on average a 10-to-1 reduction of turnaround time - and has yielded new insights into product design. It has been applied to the aerodynamic preliminary design of an aircraft engine turbine, concurrent aerodynamic and mechanical preliminary design of an aircraft engine turbine blade and disk, a space superconductor generator, a satellite power converter, and a nuclear-powered satellite reactor and shield. 23 refs

  9. The use of artificially intelligent agents with bounded rationality in the study of economic markets

    Energy Technology Data Exchange (ETDEWEB)

    Rajan, V.; Slagle, J.R. [Univ. of Minnesota, Minneapolis, MN (United States)

    1996-12-31

    The concepts of {open_quote}knowledge{close_quote} and {open_quote}rationality{close_quote} are of central importance to fields of science that are interested in human behavior and learning, such as artificial intelligence, economics, and psychology. The similarity between artificial intelligence and economics - both are concerned with intelligent thought, rational behavior, and the use and acquisition of knowledge - has led to the use of economic models as a paradigm for solving problems in distributed artificial intelligence (DAI) and multi agent systems (MAS). What we propose is the opposite; the use of artificial intelligence in the study of economic markets. Over the centuries various theories of market behavior have been advanced. The prevailing theory holds that an asset`s current price converges to the risk adjusted value of the rationally expected dividend stream. While this rational expectations model holds in equilibrium or near-equilibrium conditions, it does not sufficiently explain conditions of market disequilibrium. An example of market disequilibrium is the phenomenon of a speculative bubble. We present an example of using artificially intelligent agents with bounded rationality in the study of speculative bubbles.

  10. Evaluation of an artificial intelligence program for estimating occupational exposures.

    Science.gov (United States)

    Johnston, Karen L; Phillips, Margaret L; Esmen, Nurtan A; Hall, Thomas A

    2005-03-01

    Estimation and Assessment of Substance Exposure (EASE) is an artificial intelligence program developed by UK's Health and Safety Executive to assess exposure. EASE computes estimated airborne concentrations based on a substance's vapor pressure and the types of controls in the work area. Though EASE is intended only to make broad predictions of exposure from occupational environments, some occupational hygienists might attempt to use EASE for individual exposure characterizations. This study investigated whether EASE would accurately predict actual sampling results from a chemical manufacturing process. Personal breathing zone time-weighted average (TWA) monitoring data for two volatile organic chemicals--a common solvent (toluene) and a specialty monomer (chloroprene)--present in this manufacturing process were compared to EASE-generated estimates. EASE-estimated concentrations for specific tasks were weighted by task durations reported in the monitoring record to yield TWA estimates from EASE that could be directly compared to the measured TWA data. Two hundred and six chloroprene and toluene full-shift personal samples were selected from eight areas of this manufacturing process. The Spearman correlation between EASE TWA estimates and measured TWA values was 0.55 for chloroprene and 0.44 for toluene, indicating moderate predictive values for both compounds. For toluene, the interquartile range of EASE estimates at least partially overlapped the interquartile range of the measured data distributions in all process areas. The interquartile range of EASE estimates for chloroprene fell above the interquartile range of the measured data distributions in one process area, partially overlapped the third quartile of the measured data in five process areas and fell within the interquartile range in two process areas. EASE is not a substitute for actual exposure monitoring. However, EASE can be used in conditions that cannot otherwise be sampled and in preliminary

  11. Intrusion Detection Systems Based on Artificial Intelligence Techniques in Wireless Sensor Networks

    OpenAIRE

    Nabil Ali Alrajeh; Lloret, J

    2013-01-01

    Intrusion detection system (IDS) is regarded as the second line of defense against network anomalies and threats. IDS plays an important role in network security. There are many techniques which are used to design IDSs for specific scenario and applications. Artificial intelligence techniques are widely used for threats detection. This paper presents a critical study on genetic algorithm, artificial immune, and artificial neural network (ANN) based IDSs techniques used in wireless sensor netw...

  12. Artificial intelligence and Internet of Things in a “smart home” context

    DEFF Research Database (Denmark)

    Lynggaard, Per

    We are currently witnessing an evolution from building and home automation to smart homes, driven by progressing maturity of the Internet of Things and the use of artificial intelligence. However, significant technological challenges such as immature home intelligence, huge network and central...... with autonomous behavior, parallel processing, context awareness, and node communication. In particular, it introduces a novel approach to adapt and distribute the artificial intelligence to match the distributed system architecture in the smart home. The proposed solution addresses important issues such as real......-time learning, temporal detection with a high probability, battery lifetime, network communication, integration with smart objects, and embedded processing power. A multi-agent smart object model is provided to support the artificial intelligence framework with a new distributed architecture. This model focuses...

  13. Global Research on Artificial Intelligence from 1990–2014: Spatially-Explicit Bibliometric Analysis

    Directory of Open Access Journals (Sweden)

    Jiqiang Niu

    2016-05-01

    Full Text Available In this article, we conducted the evaluation of artificial intelligence research from 1990–2014 by using bibliometric analysis. We introduced spatial analysis and social network analysis as geographic information retrieval methods for spatially-explicit bibliometric analysis. This study is based on the analysis of data obtained from database of the Science Citation Index Expanded (SCI-Expanded and Conference Proceedings Citation Index-Science (CPCI-S. Our results revealed scientific outputs, subject categories and main journals, author productivity and geographic distribution, international productivity and collaboration, and hot issues and research trends. The growth of article outputs in artificial intelligence research has exploded since the 1990s, along with increasing collaboration, reference, and citations. Computer science and engineering were the most frequently-used subject categories in artificial intelligence studies. The top twenty productive authors are distributed in countries with a high investment of research and development. The United States has the highest number of top research institutions in artificial intelligence, producing most single-country and collaborative articles. Although there is more and more collaboration among institutions, cooperation, especially international ones, are not highly prevalent in artificial intelligence research as expected. The keyword analysis revealed interesting research preferences, confirmed that methods, models, and application are in the central position of artificial intelligence. Further, we found interesting related keywords with high co-occurrence frequencies, which have helped identify new models and application areas in recent years. Bibliometric analysis results from our study will greatly facilitate the understanding of the progress and trends in artificial intelligence, in particular, for those researchers interested in domain-specific AI-driven problem-solving. This will be

  14. Artificial Intelligence Techniques for the Estimation of Direct Methanol Fuel Cell Performance

    Science.gov (United States)

    Hasiloglu, Abdulsamet; Aras, Ömür; Bayramoglu, Mahmut

    2016-04-01

    Artificial neural networks and neuro-fuzzy inference systems are well known artificial intelligence techniques used for black-box modelling of complex systems. In this study, Feed-forward artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are used for modelling the performance of direct methanol fuel cell (DMFC). Current density (I), fuel cell temperature (T), methanol concentration (C), liquid flow-rate (q) and air flow-rate (Q) are selected as input variables to predict the cell voltage. Polarization curves are obtained for 35 different operating conditions according to a statistically designed experimental plan. In modelling study, various subsets of input variables and various types of membership function are considered. A feed -forward architecture with one hidden layer is used in ANN modelling. The optimum performance is obtained with the input set (I, T, C, q) using twelve hidden neurons and sigmoidal activation function. On the other hand, first order Sugeno inference system is applied in ANFIS modelling and the optimum performance is obtained with the input set (I, T, C, q) using sixteen fuzzy rules and triangular membership function. The test results show that ANN model estimates the polarization curve of DMFC more accurately than ANFIS model.

  15. Daily water level forecasting using wavelet decomposition and artificial intelligence techniques

    Science.gov (United States)

    Seo, Youngmin; Kim, Sungwon; Kisi, Ozgur; Singh, Vijay P.

    2015-01-01

    Reliable water level forecasting for reservoir inflow is essential for reservoir operation. The objective of this paper is to develop and apply two hybrid models for daily water level forecasting and investigate their accuracy. These two hybrid models are wavelet-based artificial neural network (WANN) and wavelet-based adaptive neuro-fuzzy inference system (WANFIS). Wavelet decomposition is employed to decompose an input time series into approximation and detail components. The decomposed time series are used as inputs to artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for WANN and WANFIS models, respectively. Based on statistical performance indexes, the WANN and WANFIS models are found to produce better efficiency than the ANN and ANFIS models. WANFIS7-sym10 yields the best performance among all other models. It is found that wavelet decomposition improves the accuracy of ANN and ANFIS. This study evaluates the accuracy of the WANN and WANFIS models for different mother wavelets, including Daubechies, Symmlet and Coiflet wavelets. It is found that the model performance is dependent on input sets and mother wavelets, and the wavelet decomposition using mother wavelet, db10, can further improve the efficiency of ANN and ANFIS models. Results obtained from this study indicate that the conjunction of wavelet decomposition and artificial intelligence models can be a useful tool for accurate forecasting daily water level and can yield better efficiency than the conventional forecasting models.

  16. Importance of nonverbal expression to the emergence of emotive artificial intelligence systems

    Science.gov (United States)

    Pioggia, Giovanni; Hanson, David; Dinelli, Serena; Di Francesco, Fabio; Francesconi, R.; De Rossi, Danilo

    2002-07-01

    The nonverbal expression of the emotions, especially in the human face, has rapidly become an area of intense interest in computer science and robotics. Exploring the emotions as a link between external events and behavioural responses, artificial intelligence designers and psychologists are approaching a theoretical understanding of foundational principles which will be key to the physical embodiment of artificial intelligence. In fact, it has been well demonstrated that many important aspects of intelligence are grounded in intimate communication with the physical world- so-called embodied intelligence . It follows naturally, then, that recent advances in emotive artificial intelligence show clear and undeniable broadening in the capacities of biologically-inspired robots to survive and thrive in a social environment. The means by which AI may express its foundling emotions are clearly integral to such capacities. In effect: powerful facial expressions are critical to the development of intelligent, sociable robots. Following discussion the importance of the nonverbal expression of emotions in humans and robots, this paper describes methods used in robotically emulating nonverbal expressions using human-like robotic faces. Furthermore, it describes the potentially revolutionary impact of electroactive polymer (EAP) actuators as artificial muscles for such robotic devices.

  17. The Use of Means of Artificial Intelligence for the Decision Making Support on Financial Markets

    OpenAIRE

    Vrba, Patrik

    2013-01-01

    Diplomová práce se zaměřuje na aplikaci nástrojů umělé inteligence pro predikce vývoje finančních trhů. Hlavní důraz je kladen na vyhodnocení využitelnosti neuronových sítí, pro stanovení predikcí na devizových trzích. Zároveň je poskytnut návrh řešení, pro plně automatizované zpracování tržních dat a následné generování obchodních příkazů. This Master's thesis focuses on applying artificial intelligence tools for the prediction of development financial markets. Major emphasis is placed on...

  18. Assistance of Novel Artificial Intelligence in Optimization of Aluminum Matrix Nanocomposite by Genetic Algorithm

    Science.gov (United States)

    Mazahery, Ali; Shabani, Mohsen Ostad

    2012-12-01

    In this article, a genetic algorithm (GA) is used to predict the mechanical properties and to optimize the process conditions of Al nanocomposites. An artificial intelligence method is also implemented as an assisting tool for engineering tasks of GAs. The principle of the survival of the fittest is applied to produce successively superior approximations to a solution. A population of points at each iteration is generated. The population approaches an optimal solution. The next population by computations that involve random choices is selected. The optimal volume percentage of SiC, cooling rate, and temperature gradient are computed to be 2.84 pct, 283 K/s (10 °C/s), 1273 K/m (1000 °C/m), respectively.

  19. Application of the artificial intelligence to estimate the constructed wetland response to heavy metal removal

    International Nuclear Information System (INIS)

    Current design approaches lack essential parameters necessary to evaluate the removal of metals contained in wastewater which is discharged to constructed wetlands. As a result, there is no guideline for an accurate design of constructed wetlands. An artificial intelligence approach was used to assess constructed wetland design. For this purpose concentrations of bioavailable mercury were evaluated in conditions where initial concentrations of inorganic mercury, chloride concentrations and pH values changed. Fuzzy knowledge base was built based on results obtained from previous investigations performed in a greenhouse for floating plants, and from computations for mercury speciation. The Fuzzy Decision Support System (FDSS) used the knowledge base to find parameters that permit to generate the highest amount of mercury available for plants. The findings of this research can be applied to wetlands and all natural processes where correlations between them are uncertain. (author)

  20. An alarm processing system for a nuclear power plant using artificial intelligence techniques

    International Nuclear Information System (INIS)

    This paper reports on an alarm processing system (APS) developed that uses artificial intelligence techniques to help operators to make decisions. Alarms in nuclear power plants are classified into generalized and special alarms. Generalized alarms are further classified into global and local alarms. For each type of alarm, the specific processing rules are applied to filter and suppress unnecessary and potentially misleading alarms. The processing for the generalized alarms is based on model-based reasoning. The special alarms are processed by the cause-consequence check rules. The priorities of alarms are determined according to both the plant state and the consistencies among the alarms. This APS is built on a workstation using the Prolog language

  1. EXPERIMENTS AND RESULTS ON THE USE OF ONTOLOGIES IN THE ARTIFICIAL INTELLIGENCE DOMAIN

    Directory of Open Access Journals (Sweden)

    Vasile-Daniel Păvăloaia

    2012-10-01

    Full Text Available The field of agent-based systems as part of the Artificial Intelligence domain is, now-a-days, quite popular. There are specialized technologies required for building software agents and it should be communicative, capable, autonomous and adaptive. In fact, these are the key characteristics required to help make the Internet activity more successful. The limiting factors in building such systems are being overcome, and new approaches are emerging from information technology research laboratories around the world. The use of ontology has proven to be essential elements in many applications and thus, they have been successfully applied in agent systems technology, knowledge management systems, and e-commerce platforms. The current research aims to present besides some theoretical aspects and examples of using the web agents for two European cities.

  2. Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS): A conceptual framework

    Science.gov (United States)

    Parnell, Gregory S.; Rowell, William F.; Valusek, John R.

    1987-01-01

    In recent years there has been increasing interest in applying the computer based problem solving techniques of Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS) to analyze extremely complex problems. A conceptual framework is developed for successfully integrating these three techniques. First, the fields of AI, OR, and DSS are defined and the relationships among the three fields are explored. Next, a comprehensive adaptive design methodology for AI and OR modeling within the context of a DSS is described. These observations are made: (1) the solution of extremely complex knowledge problems with ill-defined, changing requirements can benefit greatly from the use of the adaptive design process, (2) the field of DSS provides the focus on the decision making process essential for tailoring solutions to these complex problems, (3) the characteristics of AI, OR, and DSS tools appears to be converging rapidly, and (4) there is a growing need for an interdisciplinary AI/OR/DSS education.

  3. An overview of Space Communication Artificial Intelligence for Link Evaluation Terminal (SCAILET) Project

    Science.gov (United States)

    Shahidi, Anoosh K.; Schlegelmilch, Richard F.; Petrik, Edward J.; Walters, Jerry L.

    1991-01-01

    A software application to assist end-users of the link evaluation terminal (LET) for satellite communications is being developed. This software application incorporates artificial intelligence (AI) techniques and will be deployed as an interface to LET. The high burst rate (HBR) LET provides 30 GHz transmitting/20 GHz receiving (220/110 Mbps) capability for wideband communications technology experiments with the Advanced Communications Technology Satellite (ACTS). The HBR LET can monitor and evaluate the integrity of the HBR communications uplink and downlink to the ACTS satellite. The uplink HBR transmission is performed by bursting the bit-pattern as a modulated signal to the satellite. The HBR LET can determine the bit error rate (BER) under various atmospheric conditions by comparing the transmitted bit pattern with the received bit pattern. An algorithm for power augmentation will be applied to enhance the system's BER performance at reduced signal strength caused by adverse conditions.

  4. Applying a natural intelligence pattern in cognitive robots

    Directory of Open Access Journals (Sweden)

    Seyedeh Negar Jafari

    2013-05-01

    Full Text Available Human brain was always a mysterious subject to explore, as it has still got lots to be discovered, and a good topic to be studied in many aspects, by different branches of science. In other hand, one of the biggest concerns of the future generation of Artificial Intelligence (AI is to build robots who can think like human. To achieve this AI engineers used the theories inspired by human intelligent, which were suggested by well-known psychologists, to improve the intelligence systems. To control this complicated system they can gain a lot of benefits from studying how human mind works. In this article, cognitive robots, which were equipped to a system that was built based on human brain’s function, searched in a virtual environment and tried to survive for longer. To build the cognitive system for these robots, the psychoanalysis theory of Sigmund Freud (id, ego, and super-ego was used. And at the end, the surviving period of cognitive robots and normal robots in similar environments were compared. The results of these simulations proved that cognitive robots had more chances of surviving.

  5. Artificial intelligence and design: Opportunities, research problems and directions

    Science.gov (United States)

    Amarel, Saul

    1990-01-01

    The issues of industrial productivity and economic competitiveness are of major significance in the U.S. at present. By advancing the science of design, and by creating a broad computer-based methodology for automating the design of artifacts and of industrial processes, we can attain dramatic improvements in productivity. It is our thesis that developments in computer science, especially in Artificial Intelligence (AI) and in related areas of advanced computing, provide us with a unique opportunity to push beyond the present level of computer aided automation technology and to attain substantial advances in the understanding and mechanization of design processes. To attain these goals, we need to build on top of the present state of AI, and to accelerate research and development in areas that are especially relevant to design problems of realistic complexity. We propose an approach to the special challenges in this area, which combines 'core work' in AI with the development of systems for handling significant design tasks. We discuss the general nature of design problems, the scientific issues involved in studying them with the help of AI approaches, and the methodological/technical issues that one must face in developing AI systems for handling advanced design tasks. Looking at basic work in AI from the perspective of design automation, we identify a number of research problems that need special attention. These include finding solution methods for handling multiple interacting goals, formation problems, problem decompositions, and redesign problems; choosing representations for design problems with emphasis on the concept of a design record; and developing approaches for the acquisition and structuring of domain knowledge with emphasis on finding useful approximations to domain theories. Progress in handling these research problems will have major impact both on our understanding of design processes and their automation, and also on several fundamental questions

  6. Detection of Anomalies in Hydrometric Data Using Artificial Intelligence Techniques

    Science.gov (United States)

    Lauzon, N.; Lence, B. J.

    2002-12-01

    This work focuses on the detection of anomalies in hydrometric data sequences, such as 1) outliers, which are individual data having statistical properties that differ from those of the overall population; 2) shifts, which are sudden changes over time in the statistical properties of the historical records of data; and 3) trends, which are systematic changes over time in the statistical properties. For the purpose of the design and management of water resources systems, it is important to be aware of these anomalies in hydrometric data, for they can induce a bias in the estimation of water quantity and quality parameters. These anomalies may be viewed as specific patterns affecting the data, and therefore pattern recognition techniques can be used for identifying them. However, the number of possible patterns is very large for each type of anomaly and consequently large computing capacities are required to account for all possibilities using the standard statistical techniques, such as cluster analysis. Artificial intelligence techniques, such as the Kohonen neural network and fuzzy c-means, are clustering techniques commonly used for pattern recognition in several areas of engineering and have recently begun to be used for the analysis of natural systems. They require much less computing capacity than the standard statistical techniques, and therefore are well suited for the identification of outliers, shifts and trends in hydrometric data. This work constitutes a preliminary study, using synthetic data representing hydrometric data that can be found in Canada. The analysis of the results obtained shows that the Kohonen neural network and fuzzy c-means are reasonably successful in identifying anomalies. This work also addresses the problem of uncertainties inherent to the calibration procedures that fit the clusters to the possible patterns for both the Kohonen neural network and fuzzy c-means. Indeed, for the same database, different sets of clusters can be

  7. Proceedings of intelligent engineering systems through artificial neural networks

    International Nuclear Information System (INIS)

    This book contains the edited versions of the technical presentation of ANNIE '91, the first international meeting on Artificial Neural Networks in Engineering. The conference covered the theory of Artificial Neural Networks and its contributions in the engineering domain and attracted researchers from twelve countries. The papers in this edited book are grouped into four categories: Artificial Neural Network Architectures; Pattern Recognition; Adaptive Control, Diagnosis and Process Monitoring; and Neuro-Engineering Systems

  8. Artificial Intelligence, Evolutionary Computing and Metaheuristics In the Footsteps of Alan Turing

    CERN Document Server

    2013-01-01

    Alan Turing pioneered many research areas such as artificial intelligence, computability, heuristics and pattern formation.  Nowadays at the information age, it is hard to imagine how the world would be without computers and the Internet. Without Turing's work, especially the core concept of Turing Machine at the heart of every computer, mobile phone and microchip today, so many things on which we are so dependent would be impossible. 2012 is the Alan Turing year -- a centenary celebration of the life and work of Alan Turing. To celebrate Turing's legacy and follow the footsteps of this brilliant mind, we take this golden opportunity to review the latest developments in areas of artificial intelligence, evolutionary computation and metaheuristics, and all these areas can be traced back to Turing's pioneer work. Topics include Turing test, Turing machine, artificial intelligence, cryptography, software testing, image processing, neural networks, nature-inspired algorithms such as bat algorithm and cuckoo sear...

  9. New Trends in Computing Anticipatory Systems : Emergence of Artificial Conscious Intelligence with Machine Learning Natural Language

    Science.gov (United States)

    Dubois, Daniel M.

    2008-10-01

    This paper deals with the challenge to create an Artificial Intelligence System with an Artificial Consciousness. For that, an introduction to computing anticipatory systems is presented, with the definitions of strong and weak anticipation. The quasi-anticipatory systems of Robert Rosen are linked to open-loop controllers. Then, some properties of the natural brain are presented in relation to the triune brain theory of Paul D. MacLean, and the mind time of Benjamin Libet, with his veto of the free will. The theory of the hyperincursive discrete anticipatory systems is recalled in view to introduce the concept of hyperincursive free will, which gives a similar veto mechanism: free will as unpredictable hyperincursive anticipation The concepts of endo-anticipation and exo-anticipation are then defined. Finally, some ideas about artificial conscious intelligence with natural language are presented, in relation to the Turing Machine, Formal Language, Intelligent Agents and Mutli-Agent System.

  10. Global Collective Intelligence in Technological Societies: as a result of Collaborative Knowledge in combination with Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Juan Carlos Piedra Calderón

    2013-12-01

    Full Text Available The big influence of Information and Communication Technologies (ICT, especially in area of construction of Technological Societies has generated big social changes. That is visible in the way of relating to people in different environments. These changes have the possibility to expand the frontiers of knowledge through sharing and cooperation. That has meaning the inherently creation of a new form of Collaborative Knowledge. The potential of this Collaborative Knowledge has been given through ICT in combination with Artificial Intelligence processes, from where is obtained a Collective Knowledge. When this kind of knowledge is shared, it gives the place to the Global Collective Intelligence.

  11. Use of artificial intelligence in analytical systems for the clinical laboratory

    OpenAIRE

    Place, John F.; Truchaud, Alain; Ozawa, Kyoichi; Pardue, Harry; Schnipelsky, Paul

    1995-01-01

    The incorporation of information-processing technology into analytical systems in the form of standard computing software has recently been advanced by the introduction of artificial intelligence (AI), both as expert systems and as neural networks. This paper considers the role of software in system operation, control and automation, and attempts to define intelligence. AI is characterized by its ability to deal with incomplete and imprecise information and to accumulate knowledge. Expert sys...

  12. The Chinese room revisited : artificial intelligence and the nature of mind

    OpenAIRE

    Gonzalez, Rodrigo

    2007-01-01

    Charles Babbage began the quest to build an intelligent machine in the nineteenth century. Despite finishing neither the Difference nor the Analytical engine, he was aware that the use of mental language for describing the functioning of such machines was figurative. In order to reverse this cautious stance, Alan Turing postulated two decisive ideas that contributed to give birth to Artificial Intelligence: the Turing machine and the Turing test. Nevertheless, a philosophical problem arises f...

  13. The Essential Turing Seminal Writings in Computing, Logic, Philosophy, Artificial Intelligence, and Artificial Life Plus the Secrets of Enigma

    CERN Document Server

    2004-01-01

    The ideas that gave birth to the computer age. Alan Turing, pioneer of computing and WWII codebreaker, was one of the most important and influential thinkers of the twentieth century. In this volume for the first time his key writings are made available to a broad, non-specialist readership. They make fascinating reading both in their own right and for their historic significance: contemporary computational theory, cognitive science, artificial intelligence, and artificial life all spring from this ground-breaking work, which is also rich. in philosophical and logical insight. An introduction

  14. Proceedings of the thirteenth national conference on artificial intelligence and the eighth innovative applications of artificial intelligence conference. Volume 1 and 2

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-12-31

    This report contain papers from the Thirteenth National Conference on Artificial Intelligence and the Eighth Conference on Innovative Applications of Artificial Intelligence collected in two volumes. General areas of research for these papers are: interaction; internet agents; multiagent learning; multiagent problem solving; negotiation and coalition; AI in art and entertainment; constraint satisfaction; data consistency; game-tree search; phase transition; search control; search and learning; stochastic search; temporal reasoning; education; information retrieval and natural language processing; knowledge-based systems; knowledge compilation; knowledge representation; belief and belief revision; description logics and probabilities reasoning; knowledge-base and context; nonmonotonic reasoning; reasoning about action; learning; mobile robots; model-based reasoning; natural language; preception; planning; rule-based reasoning and connectionism; uncertainty; robot competition; student abstracts; and case studies.

  15. Artificial intelligence applications in the nuclear field: Achievements and prospects: The new challenge

    International Nuclear Information System (INIS)

    The first applications of Artificial Intelligence in the nuclear field were expert systems dedicated to off-line problems of diagnosis and maintenance. A second step aimed at solving more ambitious problems related to plant design and operation, which improved methodologies and tools. By the end of this period, new limits appeared. To solve the problems faced in the late eighties, powerful principles and methods became available. These require extensive sources. The present book describes examples of large-scale applications of Artificial Intelligence in the nuclear field

  16. International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems

    CERN Document Server

    Dash, Subhransu; Panigrahi, Bijaya

    2015-01-01

      The book is a collection of high-quality peer-reviewed research papers presented in Proceedings of International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES 2014) held at Noorul Islam Centre for Higher Education, Kumaracoil, India. These research papers provide the latest developments in the broad area of use of artificial intelligence and evolutionary algorithms in engineering systems. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. It presents invited papers from the inventors/originators of new applications and advanced technologies.

  17. ARTIFICIAL INTELLIGENCE SELECTION WITH CAPABILITY OF EDITING A NEW PARAMETER FOR EOR SCREENING CRITERIA

    Directory of Open Access Journals (Sweden)

    ELRADI ABASS

    2011-10-01

    Full Text Available This paper describes the application of an Artificial Intelligence (AI technique to assist in the selection of an Enhanced Oil Recovery method (EOR. The structure of an expert systems selection based on a new formulated screening criteria, Artificial Intelligence selection developed by a computer software called (EKORA, with an easily and friendly user interface by using visual Basic-6 environment tools is presented. An additional capability provided by this software is the ability of changing and editing the parameters of EOR methods which emerged or tested in current implementation projects. Other commercial expert systems either offer limited or no capabilities for changing and editing the EOR parameters of screening rule.

  18. Artificial intelligence research in particle accelerator control systems for beam line tuning

    Energy Technology Data Exchange (ETDEWEB)

    Pieck, Martin [Los Alamos National Laboratory

    2008-01-01

    Tuning particle accelerators is time consuming and expensive, with a number of inherently non-linear interactions between system components. Conventional control methods have not been successful in this domain and the result is constant and expensive monitoring of the systems by human operators. This is particularly true for the start-up and conditioning phase after a maintenance period or an unexpected fault. In turn, this often requires a step-by-step restart of the accelerator. Surprisingly few attempts have been made to apply intelligent accelerator control techniques to help with beam tuning, fault detection, and fault recovery problems. The reason for that might be that accelerator facilities are rare and difficult to understand systems that require detailed expert knowledge about the underlying physics as well as months if not years of experience to understand the relationship between individual components, particularly if they are geographically disjoint. This paper will give an overview about the research effort in the accelerator community that has been dedicated to the use of artificial intelligence methods for accelerator beam line tuning.

  19. Development of an Accident Diagnostic Scheme Using Artificial Intelligence Techniques (I)

    International Nuclear Information System (INIS)

    As a means to effectively manage the severe nuclear accidents, it is important to identify and diagnose the accident initiating events during an initial short time interval after the accidents by observing the major controlling parameters. Main objective of this study is to develop the diagnostic approach for the accurate prediction of accident initiating events using artificial intelligence techniques. For this, first, a variety of artificial intelligence techniques such as Finn, Gmbh, and Sm were examined through this study. Among them, Sc and Gmbh model were assessed as a useful approach to predict the break location and the break size of Local. In order to verify the proposed algorithm, the 111 accident simulation data (based on Map) were applied to train the Sc and Gmbh models, and the test data was used to independently verify whether or not the SVC and GMDH models work well. The analysis of the maximum errors and RMS errors, and the performance of the GMDH according to the existence of measurement errors and SIS actuation showed that the proposed SVC and GMDH models can accurately classify the break locations and accurately predict the break size. As the time-integrated signals were used for inputs into the GMDH model within a period of 60 second after a reactor scram, the actuation of the safety systems such as safety injection system (SIS), auxiliary feed water system, and containment spray system, were not considered in this study. It is because the initial 60 second time-integrated signals were used and the safety systems usually start to actuate after a more than 60 second time delay after the reactor scram

  20. Smart Collections: Can Artificial Intelligence Tools and Techniques Assist with Discovering, Evaluating and Tagging Digital Learning Resources?

    Science.gov (United States)

    Leibbrandt, Richard; Yang, Dongqiang; Pfitzner, Darius; Powers, David; Mitchell, Pru; Hayman, Sarah; Eddy, Helen

    2010-01-01

    This paper reports on a joint proof of concept project undertaken by researchers from the Flinders University Artificial Intelligence Laboratory in partnership with information managers from the Education Network Australia (edna) team at Education Services Australia to address the question of whether artificial intelligence techniques could be…