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Table of Contents
Introduction 1
Multiagent Systems and Distributed AI 1
Characteristics of Multiagent Systems 1
Agent Design 1
Environment 2
Perception 2
Control 3
Knowledge 3
Communication 3
Applications 3
Challenging Issues 5
Notes and Further Reading 5
Rational Agents 7
What is an Agent? 7
Agents as Rational Decision Makers 7
Observable Worlds and the Markov Property 8
Observability 9
The Markov Property 10
Stochastic Transitions and Utilities 10
From Goals to Utilities 11
Decision Making in a Stochastic World 12
Example: A Toy World 12
Notes and Further Reading 13
Strategic Games 15
Game Theory 15
Strategic Games 16
Iterated Elimination of Dominated Actions 18
Nash Equilibrium 19
Notes and Further Reading 21
Coordination 23
Coordination Games 23
Social Conventions 24
Roles 25
Coordination Graphs 26
Coordination by Variable Elimination 28
Coordination by Message Passing 31
Notes and Further Reading 32
Partial Observability 35
Thinking Interactively 35
Information and Knowledge 36
Common Knowledge 39
Partial Observability and Actions 40
States and Observations 40
Observation Model 40
Actions and Policies 41
Payoffs 41
Notes and Further Reading 43
Mechanism Design 45
Self-Interested Agents 45
The Mechanism Design Problem 45
Example: An Auction 48
The Revelation Principle 49
Example: Second-price Sealed-bid (Vickrey) Auction 50
The Vickrey-Clarke-Groves Mechanism 50
Example: Shortest Path 51
Notes and Further Reading 52
Learning 53
Reinforcement Learning 53
Markov Decision Processes 53
Value Iteration 55
Q-learning 55
Markov Games 56
Independent Learning 57
Coupled Learning 57
Sparse Cooperative Q-learning 58
The Problem of Exploration 59
Notes and Further Reading 60
Bibliography 63
Author Biography 71