The study of multi-agent systems (MAS) focuses on systems in which many intelligent agents interact with each other.  These agents are considered to be autonomous entities such as software programs or robots.  Their interactions can either be cooperative (for example as in an ant colony) or selfish (as in a free market economy).  This book assumes only basic knowledge of algorithms and discrete maths, both of which are taught as standard in the first or second year of computer science degree programmes.  A basic knowledge of artificial intelligence would useful to help understand some of the issues, but is not essential. The book’s main aims are: To introduce the student to the concept of agents and multi-agent systems, and the main applications for which they are appropriate To introduce the main issues surrounding the design of intelligent agents To introduce the main issues surrounding the design of a multi-agent society To introduce a number of typical applications for agent technology After reading the book the student should understand: The notion of an agent, how agents are distinct from other software paradigms (e.g. objects) and the characteristics of applications that lend themselves to agent-oriented software The key issues associated with constructing agents capable of intelligent autonomous action and the main approaches taken to developing such agents The key issues in designing societies of agents that can effectively cooperate in order to solve problems, including an understanding of the key types of multi-agent interactions possible in such systems The main application areas of agent-based systems

Table of Contents:
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