Multiagent systems: algorithmic, game-theoretic, and logical foundations

2009 ChoiceReviews  
than the book-and in particular has different page numbering-and has not been fully copy edited. Please treat the printed book as the definitive version. You are invited to use this electronic copy without restriction for on-screen viewing, but are requested to print it only under one of the following circumstances: • You live in a place that does not offer you access to the physical book; • The cost of the book is prohibitive for you; • You need only one or two chapters. Finally, we ask you
more » ... to link directly to the PDF or to distribute it electronically. Instead, we invite you to link to http://www.masfoundations.org. This will allow us to gauge the level of interest in the book and to update the PDF to keep it consistent with reprintings of the book. i To my wife Noa and my daughters Maia, Talia and Ella -YS To Jude -KLB Contents Credits and Acknowledgments xi Introduction xiii 1 Distributed Constraint Satisfaction 1 1.1 Defining distributed constraint satisfaction problems 2 1.2 Domain-pruning algorithms 4 1.3 Heuristic search algorithms 8 1.3.1 The asynchronous backtracking algorithm 10 1.3.2 A simple example 12 1.3.3 An extended example: the four queens problem 13 1.3.4 Beyond the ABT algorithm 17 1.4 History and references 18 2 Distributed Optimization 19 2.1 Distributed dynamic programming for path planning 19 2.1.1 Asynchronous dynamic programming 19 2.1.2 Learning real-time A * 20 2.2 Action selection in multiagent MDPs 22 2.3 Negotiation, auctions and optimization 28 2.3.1 From contract nets to auction-like optimization 28 2.3.2 The assignment problem and linear programming 30 2.3.3 The scheduling problem and integer programming 36 2.4 Social laws and conventions 44 2.5 History and references 46 3 Introduction to Noncooperative Game Theory: Games in Normal Form 47 3.1 Self-interested agents 47 3.1.1 Example: friends and enemies 48 3.1.2 Preferences and utility 49 3.2 Games in normal form 54 3.2.1 Example: the TCP user's game 54 iv Contents 3.2.2 Definition of games in normal form 55 3.2.3 More examples of normal-form games 56 3.2.4 Strategies in normal-form games 59 3.3 Analyzing games: from optimality to equilibrium 60 3.3.1 Pareto optimality 61 3.3.2 Defining best response and Nash equilibrium 62 3.3.3 Finding Nash equilibria 63 3.3.4 Nash's theorem: proving the existence of Nash equilibria 65 3.4 Further solution concepts for normal-form games 73 3.4.1 Maxmin and minmax strategies 73 3.4.2 Minimax regret 76 3.4.3 Removal of dominated strategies 78 3.4.4 Rationalizability 81 3.4.5 Correlated equilibrium 83 3.4.6 Trembling-hand perfect equilibrium 85 3.4.7 ǫ-Nash equilibrium 85 3.5 History and references 87 4 Computing Solution Concepts of Normal-Form Games 89 4.1 Computing Nash equilibria of two-player, zero-sum games 89 4.2 Computing Nash equilibria of two-player, general-sum games 91 4.2.1 Complexity of computing a sample Nash equilibrium 91 4.2.2 An LCP formulation and the Lemke-Howson algorithm 93 4.2.3 Searching the space of supports 101 4.2.4 Beyond sample equilibrium computation 104 4.3 Computing Nash equilibria of n-player, general-sum games 105 4.4 Computing maxmin and minmax strategies for two-player, general-sum games 108 4.5 Identifying dominated strategies 108 4.5.1 Domination by a pure strategy 109 4.5.2 Domination by a mixed strategy 110 4.5.3 Iterated dominance 112 4.6 Computing correlated equilibria 113 4.7 History and references 115
doi:10.5860/choice.46-5662 fatcat:pr2pmv7k2bad3pp5bxgogecgnq