Multi-Agent Coordination

Multi-Agent Coordination

Author: Arup Kumar Sadhu

Publisher: John Wiley & Sons

Published: 2020-12-01

Total Pages: 320

ISBN-13: 1119699029

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Discover the latest developments in multi-robot coordination techniques with this insightful and original resource Multi-Agent Coordination: A Reinforcement Learning Approach delivers a comprehensive, insightful, and unique treatment of the development of multi-robot coordination algorithms with minimal computational burden and reduced storage requirements when compared to traditional algorithms. The accomplished academics, engineers, and authors provide readers with both a high-level introduction to, and overview of, multi-robot coordination, and in-depth analyses of learning-based planning algorithms. You'll learn about how to accelerate the exploration of the team-goal and alternative approaches to speeding up the convergence of TMAQL by identifying the preferred joint action for the team. The authors also propose novel approaches to consensus Q-learning that address the equilibrium selection problem and a new way of evaluating the threshold value for uniting empires without imposing any significant computation overhead. Finally, the book concludes with an examination of the likely direction of future research in this rapidly developing field. Readers will discover cutting-edge techniques for multi-agent coordination, including: An introduction to multi-agent coordination by reinforcement learning and evolutionary algorithms, including topics like the Nash equilibrium and correlated equilibrium Improving convergence speed of multi-agent Q-learning for cooperative task planning Consensus Q-learning for multi-agent cooperative planning The efficient computing of correlated equilibrium for cooperative q-learning based multi-agent planning A modified imperialist competitive algorithm for multi-agent stick-carrying applications Perfect for academics, engineers, and professionals who regularly work with multi-agent learning algorithms, Multi-Agent Coordination: A Reinforcement Learning Approach also belongs on the bookshelves of anyone with an advanced interest in machine learning and artificial intelligence as it applies to the field of cooperative or competitive robotics.


Book Synopsis Multi-Agent Coordination by : Arup Kumar Sadhu

Download or read book Multi-Agent Coordination written by Arup Kumar Sadhu and published by John Wiley & Sons. This book was released on 2020-12-01 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the latest developments in multi-robot coordination techniques with this insightful and original resource Multi-Agent Coordination: A Reinforcement Learning Approach delivers a comprehensive, insightful, and unique treatment of the development of multi-robot coordination algorithms with minimal computational burden and reduced storage requirements when compared to traditional algorithms. The accomplished academics, engineers, and authors provide readers with both a high-level introduction to, and overview of, multi-robot coordination, and in-depth analyses of learning-based planning algorithms. You'll learn about how to accelerate the exploration of the team-goal and alternative approaches to speeding up the convergence of TMAQL by identifying the preferred joint action for the team. The authors also propose novel approaches to consensus Q-learning that address the equilibrium selection problem and a new way of evaluating the threshold value for uniting empires without imposing any significant computation overhead. Finally, the book concludes with an examination of the likely direction of future research in this rapidly developing field. Readers will discover cutting-edge techniques for multi-agent coordination, including: An introduction to multi-agent coordination by reinforcement learning and evolutionary algorithms, including topics like the Nash equilibrium and correlated equilibrium Improving convergence speed of multi-agent Q-learning for cooperative task planning Consensus Q-learning for multi-agent cooperative planning The efficient computing of correlated equilibrium for cooperative q-learning based multi-agent planning A modified imperialist competitive algorithm for multi-agent stick-carrying applications Perfect for academics, engineers, and professionals who regularly work with multi-agent learning algorithms, Multi-Agent Coordination: A Reinforcement Learning Approach also belongs on the bookshelves of anyone with an advanced interest in machine learning and artificial intelligence as it applies to the field of cooperative or competitive robotics.

Distributed Coordination of Multi-agent Networks

Distributed Coordination of Multi-agent Networks

Author: Wei Ren

Publisher: Springer Science & Business Media

Published: 2010-11-30

Total Pages: 312

ISBN-13: 0857291696

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Distributed Coordination of Multi-agent Networks introduces problems, models, and issues such as collective periodic motion coordination, collective tracking with a dynamic leader, and containment control with multiple leaders, and explores ideas for their solution. Solving these problems extends the existing application domains of multi-agent networks; for example, collective periodic motion coordination is appropriate for applications involving repetitive movements, collective tracking guarantees tracking of a dynamic leader by multiple followers in the presence of reduced interaction and partial measurements, and containment control enables maneuvering of multiple followers by multiple leaders.


Book Synopsis Distributed Coordination of Multi-agent Networks by : Wei Ren

Download or read book Distributed Coordination of Multi-agent Networks written by Wei Ren and published by Springer Science & Business Media. This book was released on 2010-11-30 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Distributed Coordination of Multi-agent Networks introduces problems, models, and issues such as collective periodic motion coordination, collective tracking with a dynamic leader, and containment control with multiple leaders, and explores ideas for their solution. Solving these problems extends the existing application domains of multi-agent networks; for example, collective periodic motion coordination is appropriate for applications involving repetitive movements, collective tracking guarantees tracking of a dynamic leader by multiple followers in the presence of reduced interaction and partial measurements, and containment control enables maneuvering of multiple followers by multiple leaders.

Multiagent Systems

Multiagent Systems

Author: Magdi S. Mahmoud

Publisher: CRC Press

Published: 2020-03-20

Total Pages: 244

ISBN-13: 1000078108

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Multiagent systems (MAS) are one of the most exciting and the fastest growing domains in the intelligent resource management and agent-oriented technology, which deals with modeling of autonomous decisions making entities. Recent developments have produced very encouraging results in the novel approach of handling multiplayer interactive systems. In particular, the multiagent system approach is adapted to model, control, manage or test the operations and management of several system applications including multi-vehicles, microgrids, multi-robots, where agents represent individual entities in the network. Each participant is modeled as an autonomous participant with independent strategies and responses to outcomes. They are able to operate autonomously and interact pro-actively with their environment. In recent works, the problem of information consensus is addressed, where a team of vehicles communicate with each other to agree on key pieces of information that enable them to work together in a coordinated fashion. The problem is challenging because communication channels have limited range and there are possibilities of fading and dropout. The book comprises chapters on synchronization and consensus in multiagent systems. It shows that the joint presentation of synchronization and consensus enables readers to learn about similarities and differences of both concepts. It reviews the cooperative control of multi-agent dynamical systems interconnected by a communication network topology. Using the terminology of cooperative control, each system is endowed with its own state variable and dynamics. A fundamental problem in multi-agent dynamical systems on networks is the design of distributed protocols that guarantee consensus or synchronization in the sense that the states of all the systems reach the same value. It is evident from the results that research in multiagent systems offer opportunities for further developments in theoretical, simulation and implementations. This book attempts to fill this gap and aims at presenting a comprehensive volume that documents theoretical aspects and practical applications.


Book Synopsis Multiagent Systems by : Magdi S. Mahmoud

Download or read book Multiagent Systems written by Magdi S. Mahmoud and published by CRC Press. This book was released on 2020-03-20 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiagent systems (MAS) are one of the most exciting and the fastest growing domains in the intelligent resource management and agent-oriented technology, which deals with modeling of autonomous decisions making entities. Recent developments have produced very encouraging results in the novel approach of handling multiplayer interactive systems. In particular, the multiagent system approach is adapted to model, control, manage or test the operations and management of several system applications including multi-vehicles, microgrids, multi-robots, where agents represent individual entities in the network. Each participant is modeled as an autonomous participant with independent strategies and responses to outcomes. They are able to operate autonomously and interact pro-actively with their environment. In recent works, the problem of information consensus is addressed, where a team of vehicles communicate with each other to agree on key pieces of information that enable them to work together in a coordinated fashion. The problem is challenging because communication channels have limited range and there are possibilities of fading and dropout. The book comprises chapters on synchronization and consensus in multiagent systems. It shows that the joint presentation of synchronization and consensus enables readers to learn about similarities and differences of both concepts. It reviews the cooperative control of multi-agent dynamical systems interconnected by a communication network topology. Using the terminology of cooperative control, each system is endowed with its own state variable and dynamics. A fundamental problem in multi-agent dynamical systems on networks is the design of distributed protocols that guarantee consensus or synchronization in the sense that the states of all the systems reach the same value. It is evident from the results that research in multiagent systems offer opportunities for further developments in theoretical, simulation and implementations. This book attempts to fill this gap and aims at presenting a comprehensive volume that documents theoretical aspects and practical applications.

Coordination of Large-Scale Multiagent Systems

Coordination of Large-Scale Multiagent Systems

Author: Paul Scerri

Publisher: Springer Science & Business Media

Published: 2005-10-17

Total Pages: 366

ISBN-13: 9780387261935

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Challenges arise when the size of a group of cooperating agents is scaled to hundreds or thousands of members. In domains such as space exploration, military and disaster response, groups of this size (or larger) are required to achieve extremely complex, distributed goals. To effectively and efficiently achieve their goals, members of a group need to cohesively follow a joint course of action while remaining flexible to unforeseen developments in the environment. Coordination of Large-Scale Multiagent Systems provides extensive coverage of the latest research and novel solutions being developed in the field. It describes specific systems, such as SERSE and WIZER, as well as general approaches based on game theory, optimization and other more theoretical frameworks. It will be of interest to researchers in academia and industry, as well as advanced-level students.


Book Synopsis Coordination of Large-Scale Multiagent Systems by : Paul Scerri

Download or read book Coordination of Large-Scale Multiagent Systems written by Paul Scerri and published by Springer Science & Business Media. This book was released on 2005-10-17 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Challenges arise when the size of a group of cooperating agents is scaled to hundreds or thousands of members. In domains such as space exploration, military and disaster response, groups of this size (or larger) are required to achieve extremely complex, distributed goals. To effectively and efficiently achieve their goals, members of a group need to cohesively follow a joint course of action while remaining flexible to unforeseen developments in the environment. Coordination of Large-Scale Multiagent Systems provides extensive coverage of the latest research and novel solutions being developed in the field. It describes specific systems, such as SERSE and WIZER, as well as general approaches based on game theory, optimization and other more theoretical frameworks. It will be of interest to researchers in academia and industry, as well as advanced-level students.

Intelligent Information Processing III

Intelligent Information Processing III

Author: K. Shimohara

Publisher: Springer Science & Business Media

Published: 2007-11-14

Total Pages: 584

ISBN-13: 0387446419

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Intelligent Information Processing supports the most advanced productive tools that are said to be able to change human life and the world itself. This book presents the proceedings of the 4th IFIP International Conference on Intelligent Information Processing. This conference provides a forum for engineers and scientists in academia, university and industry to present their latest research findings in all aspects of Intelligent Information Processing.


Book Synopsis Intelligent Information Processing III by : K. Shimohara

Download or read book Intelligent Information Processing III written by K. Shimohara and published by Springer Science & Business Media. This book was released on 2007-11-14 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Information Processing supports the most advanced productive tools that are said to be able to change human life and the world itself. This book presents the proceedings of the 4th IFIP International Conference on Intelligent Information Processing. This conference provides a forum for engineers and scientists in academia, university and industry to present their latest research findings in all aspects of Intelligent Information Processing.

Multi-Agent Coordination

Multi-Agent Coordination

Author: Arup Kumar Sadhu

Publisher: John Wiley & Sons

Published: 2020-12-03

Total Pages: 320

ISBN-13: 1119699037

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Discover the latest developments in multi-robot coordination techniques with this insightful and original resource Multi-Agent Coordination: A Reinforcement Learning Approach delivers a comprehensive, insightful, and unique treatment of the development of multi-robot coordination algorithms with minimal computational burden and reduced storage requirements when compared to traditional algorithms. The accomplished academics, engineers, and authors provide readers with both a high-level introduction to, and overview of, multi-robot coordination, and in-depth analyses of learning-based planning algorithms. You'll learn about how to accelerate the exploration of the team-goal and alternative approaches to speeding up the convergence of TMAQL by identifying the preferred joint action for the team. The authors also propose novel approaches to consensus Q-learning that address the equilibrium selection problem and a new way of evaluating the threshold value for uniting empires without imposing any significant computation overhead. Finally, the book concludes with an examination of the likely direction of future research in this rapidly developing field. Readers will discover cutting-edge techniques for multi-agent coordination, including: An introduction to multi-agent coordination by reinforcement learning and evolutionary algorithms, including topics like the Nash equilibrium and correlated equilibrium Improving convergence speed of multi-agent Q-learning for cooperative task planning Consensus Q-learning for multi-agent cooperative planning The efficient computing of correlated equilibrium for cooperative q-learning based multi-agent planning A modified imperialist competitive algorithm for multi-agent stick-carrying applications Perfect for academics, engineers, and professionals who regularly work with multi-agent learning algorithms, Multi-Agent Coordination: A Reinforcement Learning Approach also belongs on the bookshelves of anyone with an advanced interest in machine learning and artificial intelligence as it applies to the field of cooperative or competitive robotics.


Book Synopsis Multi-Agent Coordination by : Arup Kumar Sadhu

Download or read book Multi-Agent Coordination written by Arup Kumar Sadhu and published by John Wiley & Sons. This book was released on 2020-12-03 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the latest developments in multi-robot coordination techniques with this insightful and original resource Multi-Agent Coordination: A Reinforcement Learning Approach delivers a comprehensive, insightful, and unique treatment of the development of multi-robot coordination algorithms with minimal computational burden and reduced storage requirements when compared to traditional algorithms. The accomplished academics, engineers, and authors provide readers with both a high-level introduction to, and overview of, multi-robot coordination, and in-depth analyses of learning-based planning algorithms. You'll learn about how to accelerate the exploration of the team-goal and alternative approaches to speeding up the convergence of TMAQL by identifying the preferred joint action for the team. The authors also propose novel approaches to consensus Q-learning that address the equilibrium selection problem and a new way of evaluating the threshold value for uniting empires without imposing any significant computation overhead. Finally, the book concludes with an examination of the likely direction of future research in this rapidly developing field. Readers will discover cutting-edge techniques for multi-agent coordination, including: An introduction to multi-agent coordination by reinforcement learning and evolutionary algorithms, including topics like the Nash equilibrium and correlated equilibrium Improving convergence speed of multi-agent Q-learning for cooperative task planning Consensus Q-learning for multi-agent cooperative planning The efficient computing of correlated equilibrium for cooperative q-learning based multi-agent planning A modified imperialist competitive algorithm for multi-agent stick-carrying applications Perfect for academics, engineers, and professionals who regularly work with multi-agent learning algorithms, Multi-Agent Coordination: A Reinforcement Learning Approach also belongs on the bookshelves of anyone with an advanced interest in machine learning and artificial intelligence as it applies to the field of cooperative or competitive robotics.

Logic Programming

Logic Programming

Author: Bart Demoen

Publisher: Springer

Published: 2004-11-18

Total Pages: 492

ISBN-13: 3540277757

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This volume contains the papers presented at the 20th International Conference on Logic Programming,held in Saint-Malo,France,September 6-10,2004.Since the ?rst meeting in this series, held in Marseilles in 1982, ICLP has been the premier international conference for presenting research in logic programming. This year, we received 70 technical papers from countries all over the world, and the Program Committee accepted 28 of them for presentation;they are included in this volume. A stand-by-your-poster session took place during the conference. It served as a forum for presenting work in a more informal and interactive setting. Abstracts of the 16 posters selected by the Program Committee are included in this volume as well. The conference program also included invited talks and invited tutorials. We were privileged to have talks by three outstanding researchers and excellent speakers: Nachum Dershowitz (Tel Aviv University, Israel) talked on Ter- nation by Abstraction, Michael Gelfond (Texas Tech University, USA) on - swer Set Programming and the Design of Deliberative Agents,andG ́ erard Huet (INRIA, France) on Non-determinism Lessons. Two of the invited talks appear in these proceedings. The tutorials covered topics of high interest to the logic programming community: Ilkka Niemel ̈ a gave a tutorial on The Implementation of Answer Set Solvers, Andreas Podelskion Tree Automata in Program Analysis and Veri?cation, and Guillermo R. Simari on Defeasible Logic Programming and Belief Revision. Satellite workshops made the conference even more interesting. Six workshops collocated with ICLP 2004: - CICLOPS2004, Colloquium on Implementation of Constraint and Logic Programming Systems, organized by Manuel Carro. - COLOPS2004, 2nd International Workshop on Constraint & Logic Progr- ming in Security, organized by Frank Valencia. - MultiCPL2004, 3rd International Workshop on Multiparadigm Constraint, organized by Petra Hofstedt. - Teach LP2004,1st International Workshop on Teaching Logic Programming, organized by Dietmar Seipel.


Book Synopsis Logic Programming by : Bart Demoen

Download or read book Logic Programming written by Bart Demoen and published by Springer. This book was released on 2004-11-18 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers presented at the 20th International Conference on Logic Programming,held in Saint-Malo,France,September 6-10,2004.Since the ?rst meeting in this series, held in Marseilles in 1982, ICLP has been the premier international conference for presenting research in logic programming. This year, we received 70 technical papers from countries all over the world, and the Program Committee accepted 28 of them for presentation;they are included in this volume. A stand-by-your-poster session took place during the conference. It served as a forum for presenting work in a more informal and interactive setting. Abstracts of the 16 posters selected by the Program Committee are included in this volume as well. The conference program also included invited talks and invited tutorials. We were privileged to have talks by three outstanding researchers and excellent speakers: Nachum Dershowitz (Tel Aviv University, Israel) talked on Ter- nation by Abstraction, Michael Gelfond (Texas Tech University, USA) on - swer Set Programming and the Design of Deliberative Agents,andG ́ erard Huet (INRIA, France) on Non-determinism Lessons. Two of the invited talks appear in these proceedings. The tutorials covered topics of high interest to the logic programming community: Ilkka Niemel ̈ a gave a tutorial on The Implementation of Answer Set Solvers, Andreas Podelskion Tree Automata in Program Analysis and Veri?cation, and Guillermo R. Simari on Defeasible Logic Programming and Belief Revision. Satellite workshops made the conference even more interesting. Six workshops collocated with ICLP 2004: - CICLOPS2004, Colloquium on Implementation of Constraint and Logic Programming Systems, organized by Manuel Carro. - COLOPS2004, 2nd International Workshop on Constraint & Logic Progr- ming in Security, organized by Frank Valencia. - MultiCPL2004, 3rd International Workshop on Multiparadigm Constraint, organized by Petra Hofstedt. - Teach LP2004,1st International Workshop on Teaching Logic Programming, organized by Dietmar Seipel.

Multi-Agent Machine Learning

Multi-Agent Machine Learning

Author: H. M. Schwartz

Publisher: John Wiley & Sons

Published: 2014-08-26

Total Pages: 273

ISBN-13: 1118884485

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The book begins with a chapter on traditional methods of supervised learning, covering recursive least squares learning, mean square error methods, and stochastic approximation. Chapter 2 covers single agent reinforcement learning. Topics include learning value functions, Markov games, and TD learning with eligibility traces. Chapter 3 discusses two player games including two player matrix games with both pure and mixed strategies. Numerous algorithms and examples are presented. Chapter 4 covers learning in multi-player games, stochastic games, and Markov games, focusing on learning multi-player grid games—two player grid games, Q-learning, and Nash Q-learning. Chapter 5 discusses differential games, including multi player differential games, actor critique structure, adaptive fuzzy control and fuzzy interference systems, the evader pursuit game, and the defending a territory games. Chapter 6 discusses new ideas on learning within robotic swarms and the innovative idea of the evolution of personality traits. • Framework for understanding a variety of methods and approaches in multi-agent machine learning. • Discusses methods of reinforcement learning such as a number of forms of multi-agent Q-learning • Applicable to research professors and graduate students studying electrical and computer engineering, computer science, and mechanical and aerospace engineering


Book Synopsis Multi-Agent Machine Learning by : H. M. Schwartz

Download or read book Multi-Agent Machine Learning written by H. M. Schwartz and published by John Wiley & Sons. This book was released on 2014-08-26 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book begins with a chapter on traditional methods of supervised learning, covering recursive least squares learning, mean square error methods, and stochastic approximation. Chapter 2 covers single agent reinforcement learning. Topics include learning value functions, Markov games, and TD learning with eligibility traces. Chapter 3 discusses two player games including two player matrix games with both pure and mixed strategies. Numerous algorithms and examples are presented. Chapter 4 covers learning in multi-player games, stochastic games, and Markov games, focusing on learning multi-player grid games—two player grid games, Q-learning, and Nash Q-learning. Chapter 5 discusses differential games, including multi player differential games, actor critique structure, adaptive fuzzy control and fuzzy interference systems, the evader pursuit game, and the defending a territory games. Chapter 6 discusses new ideas on learning within robotic swarms and the innovative idea of the evolution of personality traits. • Framework for understanding a variety of methods and approaches in multi-agent machine learning. • Discusses methods of reinforcement learning such as a number of forms of multi-agent Q-learning • Applicable to research professors and graduate students studying electrical and computer engineering, computer science, and mechanical and aerospace engineering

Multiagent System Technologies

Multiagent System Technologies

Author: Ralph Bergmann

Publisher: Springer Science & Business Media

Published: 2008-09-12

Total Pages: 217

ISBN-13: 3540878041

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This book constitutes the refereed proceedings of the 6th German Conference on Multiagent Systems Technologies, MATES 2008, held in Kaiserslautern, Germany, in September 2008 - co-located with the 31st German Conference on Artificial Intelligence, KI 2008. The 16 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 35 submissions. The papers present and discuss the latest advances of research and development in the area of autonomous agents and multiagent systems ranging from theoretical and methodological issues to applications in various fields.


Book Synopsis Multiagent System Technologies by : Ralph Bergmann

Download or read book Multiagent System Technologies written by Ralph Bergmann and published by Springer Science & Business Media. This book was released on 2008-09-12 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th German Conference on Multiagent Systems Technologies, MATES 2008, held in Kaiserslautern, Germany, in September 2008 - co-located with the 31st German Conference on Artificial Intelligence, KI 2008. The 16 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 35 submissions. The papers present and discuss the latest advances of research and development in the area of autonomous agents and multiagent systems ranging from theoretical and methodological issues to applications in various fields.

Multiagent Systems, second edition

Multiagent Systems, second edition

Author: Gerhard Weiss

Publisher: MIT Press

Published: 2016-10-28

Total Pages: 917

ISBN-13: 0262533871

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The new edition of an introduction to multiagent systems that captures the state of the art in both theory and practice, suitable as textbook or reference. Multiagent systems are made up of multiple interacting intelligent agents—computational entities to some degree autonomous and able to cooperate, compete, communicate, act flexibly, and exercise control over their behavior within the frame of their objectives. They are the enabling technology for a wide range of advanced applications relying on distributed and parallel processing of data, information, and knowledge relevant in domains ranging from industrial manufacturing to e-commerce to health care. This book offers a state-of-the-art introduction to multiagent systems, covering the field in both breadth and depth, and treating both theory and practice. It is suitable for classroom use or independent study. This second edition has been completely revised, capturing the tremendous developments in multiagent systems since the first edition appeared in 1999. Sixteen of the book's seventeen chapters were written for this edition; all chapters are by leaders in the field, with each author contributing to the broad base of knowledge and experience on which the book rests. The book covers basic concepts of computational agency from the perspective of both individual agents and agent organizations; communication among agents; coordination among agents; distributed cognition; development and engineering of multiagent systems; and background knowledge in logics and game theory. Each chapter includes references, many illustrations and examples, and exercises of varying degrees of difficulty. The chapters and the overall book are designed to be self-contained and understandable without additional material. Supplemental resources are available on the book's Web site. Contributors Rafael Bordini, Felix Brandt, Amit Chopra, Vincent Conitzer, Virginia Dignum, Jürgen Dix, Ed Durfee, Edith Elkind, Ulle Endriss, Alessandro Farinelli, Shaheen Fatima, Michael Fisher, Nicholas R. Jennings, Kevin Leyton-Brown, Evangelos Markakis, Lin Padgham, Julian Padget, Iyad Rahwan, Talal Rahwan, Alex Rogers, Jordi Sabater-Mir, Yoav Shoham, Munindar P. Singh, Kagan Tumer, Karl Tuyls, Wiebe van der Hoek, Laurent Vercouter, Meritxell Vinyals, Michael Winikoff, Michael Wooldridge, Shlomo Zilberstein


Book Synopsis Multiagent Systems, second edition by : Gerhard Weiss

Download or read book Multiagent Systems, second edition written by Gerhard Weiss and published by MIT Press. This book was released on 2016-10-28 with total page 917 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new edition of an introduction to multiagent systems that captures the state of the art in both theory and practice, suitable as textbook or reference. Multiagent systems are made up of multiple interacting intelligent agents—computational entities to some degree autonomous and able to cooperate, compete, communicate, act flexibly, and exercise control over their behavior within the frame of their objectives. They are the enabling technology for a wide range of advanced applications relying on distributed and parallel processing of data, information, and knowledge relevant in domains ranging from industrial manufacturing to e-commerce to health care. This book offers a state-of-the-art introduction to multiagent systems, covering the field in both breadth and depth, and treating both theory and practice. It is suitable for classroom use or independent study. This second edition has been completely revised, capturing the tremendous developments in multiagent systems since the first edition appeared in 1999. Sixteen of the book's seventeen chapters were written for this edition; all chapters are by leaders in the field, with each author contributing to the broad base of knowledge and experience on which the book rests. The book covers basic concepts of computational agency from the perspective of both individual agents and agent organizations; communication among agents; coordination among agents; distributed cognition; development and engineering of multiagent systems; and background knowledge in logics and game theory. Each chapter includes references, many illustrations and examples, and exercises of varying degrees of difficulty. The chapters and the overall book are designed to be self-contained and understandable without additional material. Supplemental resources are available on the book's Web site. Contributors Rafael Bordini, Felix Brandt, Amit Chopra, Vincent Conitzer, Virginia Dignum, Jürgen Dix, Ed Durfee, Edith Elkind, Ulle Endriss, Alessandro Farinelli, Shaheen Fatima, Michael Fisher, Nicholas R. Jennings, Kevin Leyton-Brown, Evangelos Markakis, Lin Padgham, Julian Padget, Iyad Rahwan, Talal Rahwan, Alex Rogers, Jordi Sabater-Mir, Yoav Shoham, Munindar P. Singh, Kagan Tumer, Karl Tuyls, Wiebe van der Hoek, Laurent Vercouter, Meritxell Vinyals, Michael Winikoff, Michael Wooldridge, Shlomo Zilberstein