An Introduction to MultiAgent Systems 2e
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More About This Title An Introduction to MultiAgent Systems 2e

English

The eagerly anticipated updated resource on one of the most important areas of research and development: multi-agent systems

Multi-agent systems allow many intelligent agents to interact with each other, and this field of study has advanced at a rapid pace since the publication of the first edition of this book, which was nearly a decade ago. With this exciting new edition, the coverage of multi-agents is completely updated to include several areas that have come to prominence in the last several years, including auctions, computational social choice, and markov decision processes. In turn, a variety of topics that were initially considered critical have dwindled in importance, so the coverage of that subject matter is decreased with this new edition. The result of this redefined balance of coverage is a timely and essential resource on a popular topic.

  • Introduces you to the concept of agents and multi-agent systems and the main applications for which they are appropriate
  • Discusses the main issues surrounding the design of intelligent agents and a multi-agent society
  • Delves into a number of typical applications for agent technology
  • Addresses deductive reasoning agents, practical reasoning agents, reactive and hybrid agents, and more
  • Reviews multi-agent decision making, communication and cooperation, and intelligent autonomous agents

      By the end of the book, you will have a firm grasp on how agents are distinct from other software paradigms and understand the characteristics of applications that lend themselves to agent-oriented software.

  • English

    Michael Wooldridge is a Professor of Computer Science at the University of Liverpool, UK. He obtained his PhD in 1992 for work in the theory of multiagent systems and has, since then, been active in multiagent systems research.

    English

    Preface xiii

    Acknowledgements xxi

    Part I Setting the Scene 1

    1 Introduction 3

    1.1 The Vision Thing 6

    1.2 Some Views of the Field 9

    1.2.1 Agents as a paradigm for software engineering 9

    1.2.2 Agents as a tool for understanding human societies 12

    1.3 Frequently Asked Questions (FAQ) 12

    Part II Intelligent Autonomous Agents 19

    2 Intelligent Agents 21

    2.1 Intelligent Agents 26

    2.2 Agents and Objects 28

    2.3 Agents and Expert Systems 30

    2.4 Agents as Intentional Systems 31

    2.5 Abstract Architectures for Intelligent Agents 34

    2.6 How to Tell an Agent What to Do 38

    3 Deductive Reasoning Agents 49

    3.1 Agents as Theorem Provers 50

    3.2 Agent-Oriented Programming 55

    3.3 Concurrent MetateM 56

    4 Practical Reasoning Agents 65

    4.1 Practical Reasoning = Deliberation +Means–Ends Reasoning 65

    4.2 Means–Ends Reasoning 69

    4.3 Implementing a Practical Reasoning Agent 75

    4.4 The Procedural Reasoning System 79

    5 Reactive and Hybrid Agents 85

    5.1 Reactive Agents 85

    5.1.1 The subsumption architecture 86

    5.1.2 PENGI 90

    5.1.3 Situated automata 90

    5.1.4 The agent network architecture 91

    5.1.5 The limitations of reactive agents 92

    5.2 Hybrid Agents 92

    5.2.1 Touring Machines 94

    5.2.2 InteRRaP 96

    5.2.3 3T 98

    5.2.4 Stanley 99

    Part III Communication and Cooperation 105

    6 Understanding Each Other 107

    6.1 Ontology Fundamentals 108

    6.1.1 Ontology building blocks 108

    6.1.2 Anontology of ontologies 110

    6.2 Ontology Languages 113

    6.2.1 XML–adhoc ontologies 113

    6.2.2 OWL–The web ontology language 114

    6.2.3 KIF–ontologies in first-order logic 120

    6.3 RDF 121

    6.4 Constructing an Ontology 124

    6.5 Software Tools for Ontologies 127

    7 Communicating 131

    7.1 Speech Acts 132

    7.1.1 Austin 132

    7.1.2 Searle 133

    7.1.3 The plan-based theory of speech acts 134

    7.1.4 Speech acts as rational action 135

    7.2 Agent Communication Languages 136

    7.2.1 KQML 136

    7.2.2 The FIPA agent communication language  140

    7.2.3 JADE 146

    8 Working Together 151

    8.1 Cooperative Distributed Problem Solving 151

    8.2 Task Sharing and Result Sharing 153

    8.2.1 Task sharing in the Contract Net 156

    8.3 Result Sharing 159

    8.4 Combining Task and Result Sharing 159

    8.5 Handling Inconsistency 161

    8.6 Coordination 162

    8.6.1 Coordination through partial global planning 163

    8.6.2 Coordination through joint intentions 165

    8.6.3 Coordination by mutual modelling 170

    8.6.4 Coordination by norms and social laws 173

    8.7 Multiagent Planning and Synchronization 177

    9 Methodologies 183

    9.1 When is an Agent-Based Solution Appropriate? 183

    9.2 Agent-Oriented Analysis and Design 184

    9.2.1 The AAII methodology 184

    9.2.2 Gaia 186

    9.2.3 Tropos 187

    9.2.4 Prometheus 188

    9.2.5 Agent UML 188

    9.2.6 Agents in Z 189

    9.3 Pitfalls of Agent Development 190

    9.4 Mobile Agents 193

    10 Applications 201

    10.1 Agents for Workflow and Business Process Management 201

    10.2 Agents for Distributed Sensing 203

    10.3 Agents for Information Retrieval and Management 205

    10.4 Agents for Electronic Commerce 211

    10.5 Agents for Human–Computer Interfaces 213

    10.6 Agents for Virtual Environments 214

    10.7 Agents for Social Simulation 214

    10.8 Agents for X  218

    Part IV Multiagent Decision Making 221

    11 Multiagent Interactions 223

    11.1 Utilities and Preferences 223

    11.2 Setting the Scene 226

    11.3 Solution Concepts and Solution Properties 229

    11.3.1 Dominant strategies 230

    11.3.2 Nash equilibria 230

    11.3.3 Pareto efficiency 233

    11.3.4 Maximizing social welfare 235

    11.4 Competitive and Zero-Sum Interactions 235

    11.5 The Prisoner’s Dilemma 236

    11.5.1 The shadow of the future 240

    11.5.2 Program equilibria 243

    11.6 Other Symmetric 2 ×2Interactions 245

    11.7 Representing Multiagent Scenarios 248

    11.8 Dependence Relations in Multiagent Systems 249

    12 Making Group Decisions 253

    12.1 Social Welfare Functions and Social Choice Functions 253

    12.2 Voting Procedures 255

    12.2.1 Plurality 255

    12.2.2 Sequential majority elections 257

    12.2.3 The Borda count 260

    12.2.4 The Slater ranking 260

    12.3 Desirable Properties for Voting Procedures 261

    12.3.1 Arrow’s theorem 263

    12.4 Strategic Manipulation 264

    13 Forming Coalitions 269

    13.1 Cooperative Games 270

    13.1.1 The core 272

    13.1.2 The Shapley value 274

    13.2 Computational and Representational Issues 277

    13.3 Modular Representations 278

    13.3.1 Induced subgraphs 278

    13.3.2 Marginal contribution nets 280

    13.4 Representations for Simple Games 281

    13.4.1 Weighted voting games 282

    13.4.2 Network flow games 285

    13.5 Coalitional Games with Goals 287

    13.6 Coalition Structure Formation 288

    14 Allocating Scarce Resources 293

    14.1 Classifying Auctions 294

    14.2 Auctions for Single Items 295

    14.2.1 English auctions 295

    14.2.2 Dutch auctions 296

    14.2.3 First-price sealed-bid auctions 296

    14.2.4 Vickrey auctions 296

    14.2.5 Expected revenue 297

    14.2.6 Lies and collusion 298

    14.2.7 Counter speculation 299

    14.3 Combinatorial Auctions 299

    14.3.1 Bidding languages 302

    14.3.2 Winner determination 306

    14.3.3 The VCG mechanism 308

    14.4 Auctions in Practice 310

    14.4.1 Online auctions 310

    14.4.2 Adwords auctions 311

    14.4.3 The trading agent competition 312

    15 Bargaining 315

    15.1 Negotiation Parameters 315

    15.2 Bargaining for Resource Division 317

    15.2.1 Patient players 317

    15.2.2 Impatient players 320

    15.2.3 Negotiation decision functions 321

    15.2.4 Applications of alternating offers 323

    15.3 Bargaining for Task Allocation 323

    15.3.1 Themonotonic concession protocol 326

    15.3.2 The Zeuthen strategy 327

    15.3.3 Deception 329

    15.4 Bargaining for Resource Allocation 330

    16 Arguing 337

    16.1 Types of Argument 338

    16.2 Abstract Argumentation 338

    16.2.1 Preferred extensions 339

    16.2.2 Credulous and skeptical acceptance 341

    16.2.3 Preferences in abstract argument systems 343

    16.2.4 Values in abstract argument systems 344

    16.3 Deductive Argumentation Systems 345

    16.4 Dialogue Systems 348

    16.5 Implemented Argumentation Systems 350

    17 Logical Foundations 355

    17.1 Logics for Knowledge and Belief  355

    17.1.1 Possible-worlds semantics for modal logics 357

    17.1.2 Normal modal logics 358

    17.1.3 Normal modal logics as epistemic logics 361

    17.1.4 Logical omniscience 363

    17.1.5 Axioms for knowledge and belief 364

    17.1.6 Multiagent epistemic logics 365

    17.1.7 Common and distributed knowledge 367

    17.2 Logics for Mental States 369

    17.2.1 Cohen and Levesque’s intention logic 369

    17.2.2 Modelling speech acts 371

    17.3 Logics for Cooperation 373

    17.3.1 Incomplete information 375

    17.3.2 Cooperation logics for social choice 376

    17.4 Putting Logic to Work 376

    17.4.1 Logic in specification 377

    17.4.2 Logic in implementation 378

    17.4.3 Logic in verification 381

    Part V Coda 391

    A A History Lesson 393

    B Afterword 405

    Glossary of Key Terms 407

    References 425

    Index 453

    English

    “Nevertheless, despite these minor issues, this book is highly recommended to all socio-economic agent-based modellers, beginners or otherwise. Wooldridge’s scope, rigor, and well-respected experience at the current coalface means there’s plenty in here of interest for old-timers, while beginners can skip some of the maths and more bleeding-edge theory and concentrate easily on the implementation without loosing much.”  (Appl. Spatial Analysis, 2011)

     

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