Multiagent Systems, Second Edition, 2e

ISBN: 9780262313551 | Copyright 2013

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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

...I find Multiagent Systems to be an excellent textbook for an experienced researcher or an advanced student, as well as a great reference tool for anyone interested in the field. I also want to emphasize once again the enormous scope of the book—to the best of my knowledge there is no comparable book on the market—it is as comprehensive as a book on multiagent systems can get without becoming more than one book.

Piotr Kazmierczak Künstliche Intelligenz
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Contents in Brief (pg. vii)
Contents (pg. xi)
List of Figures (pg. xxvii)
List of Tables (pg. xxxiii)
Preface (pg. xxxv)
The Subject of This Book (pg. xxxv)
Main Features of This Book (pg. xxxvii)
Readership and Prerequisites (pg. xxxvii)
Changes from the First Edition (pg. xxxviii)
Structure and Chapters (pg. xxxviii)
The Exercises (pg. xxxix)
How to Use This Book (pg. xl)
Slides and More – TheWebsite of the Book (pg. xli)
Acknowledgments (pg. xli)
Contributing Authors (pg. xliii)
Part I. Agent Architectures and Organizations (pg. 1)
Chapter 1. Intelligent Agents (pg. 3)
1. Introduction (pg. 3)
2. What Are Agents? (pg. 4)
3. Architectures for Intelligent Agents (pg. 13)
4. Conclusions (pg. 42)
5. Exercises (pg. 42)
References (pg. 45)
Chapter 2. Multiagent Organizations (pg. 51)
1. Introduction (pg. 51)
2. Background (pg. 53)
3. Multiagent Organizations (pg. 62)
4. Institutions (pg. 72)
5. Agents in Organizations (pg. 82)
6. Evolution of Organizations (pg. 85)
7. Conclusions (pg. 88)
Acknowledgments (pg. 89)
8. Exercises (pg. 89)
References (pg. 92)
Part II. Communication (pg. 99)
Chapter 3. Agent Communication (pg. 101)
1. Introduction (pg. 101)
2. Conceptual Foundations of Communication in MAS (pg. 106)
3. Traditional Software Engineering Approaches (pg. 108)
4. Traditional AI Approaches (pg. 114)
5. Commitment-Based Multiagent Approaches (pg. 118)
6. Engineering with Agent Communication (pg. 122)
7. Advanced Topics and Challenges (pg. 128)
8. Conclusions (pg. 130)
Acknowledgments (pg. 132)
9. Exercises (pg. 133)
References (pg. 136)
Chapter 4. Negotiation and Bargaining (pg. 143)
1. Introduction (pg. 143)
2. Aspects of Negotiation (pg. 144)
3. Game-Theoretic Approaches for Single-Issue Negotiation (pg. 146)
4. Game-Theoretic Approaches for Multi-Issue Negotiation (pg. 156)
5. Heuristic Approaches for Multi-Issue Negotiation (pg. 161)
6. Negotiating with Humans (pg. 165)
7. Argumentation-Based Negotiation (pg. 167)
8. Conclusions (pg. 169)
Acknowledgments (pg. 170)
9. Exercises (pg. 170)
References (pg. 171)
Chapter 5. Argumentation among Agents (pg. 177)
1. Introduction (pg. 177)
2. What Is an Argument? (pg. 178)
3. Evaluating an Argument (pg. 181)
4. Argumentation Protocols (pg. 185)
5. Strategic Argumentation and Game Theory (pg. 190)
6. The Argument Interchange Format (pg. 201)
7. Conclusion (pg. 204)
Acknowledgment (pg. 204)
8. Exercises (pg. 205)
References (pg. 206)
Part III. Basic Coordination (pg. 211)
Chapter 6. Computational Social Choice (pg. 213)
1. Introduction (pg. 213)
2. Preference Aggregation (pg. 219)
3. Voting (pg. 226)
4. Combinatorial Domains (pg. 241)
5. Fair Division (pg. 247)
6. Conclusion (pg. 257)
Acknowledgments (pg. 260)
7. Exercises (pg. 260)
References (pg. 266)
Chapter 7. Mechanism Design and Auctions (pg. 285)
1. Introduction (pg. 285)
2. Mechanism Design with Unrestricted Preferences (pg. 286)
3. Quasilinear Preferences (pg. 291)
4. Efficient Mechanisms (pg. 296)
5. Single-Good Auctions (pg. 304)
6. Position Auctions (pg. 312)
7. Combinatorial Auctions (pg. 315)
8. Conclusions (pg. 318)
9. Exercises (pg. 320)
References (pg. 325)
Chapter 8. Computational Coalition Formation (pg. 329)
1. Introduction (pg. 329)
2. Definitions (pg. 331)
3. Solution Concepts (pg. 335)
4. Representation Formalisms (pg. 343)
5. Coalition Structure Generation (pg. 352)
6. Conclusions (pg. 372)
7. Exercises (pg. 372)
References (pg. 374)
Chapter 9. Trust and Reputation in Multiagent Systems (pg. 381)
1. Introduction (pg. 381)
2. Computational Representation of Trust and Reputation Values (pg. 382)
3. Trust Processes in Multiagent Systems (pg. 388)
4. Reputation in Multiagent Societies (pg. 396)
5. Trust, Reputation, and Other Agreement Technologies (pg. 407)
6. Conclusions (pg. 413)
7. Exercises (pg. 414)
References (pg. 415)
Part IV. Distributed Cognitive Abilities (pg. 421)
Chapter 10. Multiagent Learning (pg. 423)
1. Introduction (pg. 423)
2. Challenges in Multiagent Learning (pg. 425)
3. Reinforcement Learning for Multiagent Systems (pg. 432)
4. Evolutionary Game Theory as a Multiagent Learning Paradigm (pg. 443)
5. Swarm Intelligence as a Multiagent Learning Paradigm (pg. 451)
6. Neuro-Evolution as a Multiagent Learning Paradigm (pg. 457)
7. Case Study: Air Traffic Control (pg. 460)
8. Conclusions (pg. 468)
9. Exercises (pg. 468)
References (pg. 475)
Chapter 11. Multiagent Planning, Control, and Execution (pg. 485)
1. Introduction (pg. 485)
2. Characterizing Multiagent Planning and Control (pg. 487)
3. Coordination Prior to Local Planning (pg. 488)
4. Local Planning Prior to Coordination (pg. 497)
5. Decision-Theoretic Multiagent Planning (pg. 512)
6. Multiagent Execution (pg. 527)
7. Conclusions (pg. 532)
8. Exercises (pg. 533)
Acknowledgments (pg. 539)
References (pg. 539)
Chapter 12. Distributed Constraint Handling and Optimization (pg. 547)
1. Introduction (pg. 547)
2. Distributed Constraint Handling (pg. 549)
3. Applications and Benchmarking Problems (pg. 551)
4. Solution Techniques: Complete Algorithms (pg. 554)
5. Solution Techniques: Approximate Algorithms (pg. 565)
6. Solution Techniques with Quality Guarantees (pg. 570)
7. Conclusions (pg. 577)
8. Exercises (pg. 578)
References (pg. 580)
Part V. Development and Engineering (pg. 585)
Chapter 13. Programming Multiagent Systems (pg. 587)
1. Introduction (pg. 587)
2. From AGENT0 to Modern Agent Languages (pg. 590)
3. Abstractions in the MAOP Paradigm (pg. 593)
4. Examples of Agent Programming Languages (pg. 596)
5. Organization and Environment Programming (pg. 609)
6. Example of Full MAOP in JaCaMo (pg. 620)
7. Conclusions (pg. 629)
Acknowledgments (pg. 630)
8. Exercises (pg. 630)
References (pg. 633)
Chapter 14. Specification and Verification of Multiagent Systems (pg. 641)
1. Introduction (pg. 641)
2. Agent Specification (pg. 644)
3. From Specifications to Implementations (pg. 656)
4. Formal Verification (pg. 659)
5. Deductive Verification of Agents (pg. 663)
6. Algorithmic Verification of Agent Models (pg. 667)
7. Algorithmic Verification of Agent Programs (pg. 676)
8. Conclusions (pg. 680)
9. Exercises (pg. 681)
References (pg. 683)
Chapter 15. Agent-Oriented Software Engineering (pg. 695)
1. Introduction (pg. 695)
2. Agent Concepts (pg. 700)
3. Running Example (pg. 702)
4. Requirements (pg. 704)
5. Design (pg. 710)
6. Detailed Design (pg. 717)
7. Implementation (pg. 727)
8. Assurance (pg. 728)
9. Software Maintenance (pg. 734)
10. Comparing Methodologies (pg. 735)
11. Conclusions (pg. 736)
12. Exercises (pg. 740)
Appendix: Agent UML Sequence Diagram Notation (pg. 742)
References (pg. 744)
Part VI. Technical Background (pg. 759)
Chapter 16. Logics for Multiagent Systems (pg. 761)
1. Introduction (pg. 761)
2. Representing Cognitive States (pg. 769)
3. Representing the Strategic Structure of a System (pg. 785)
4. Conclusion and Further Reading (pg. 797)
5. Exercises (pg. 799)
References (pg. 800)
Chapter 17. Game-Theoretic Foundations of Multiagent Systems (pg. 811)
1. Introduction (pg. 811)
2. Normal-Form Games (pg. 812)
3. Extensive-Form Games (pg. 828)
4. Bayesian Games (pg. 836)
5. Conclusions (pg. 842)
6. Exercises (pg. 842)
References (pg. 847)
Subject Index (pg. 849)
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