Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence

Name: Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence
Availability: OutOfStock
ISBN: 9781598295269

ISBN-10: 1598295268

ISBN-13: 9781598295269

Edition: 2007

Authors: Nikos Vlassis, Ronald Brachman, Thomas Dietterich

List price: $40.00

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Book details

List price: $40.00
Copyright year: 2007
Publisher: Morgan & Claypool Publishers
Publication date: 7/30/2007
Binding: Paperback
Pages: 71
Size: 7.25" wide x 9.00" long x 0.25" tall
Weight: 0.418
Language: English



Preface


Introduction


Multiagent Systems and Distributed AI


Characteristics of Multiagent Systems


Agent Design


Environment


Perception


Control


Knowledge


Communication


Applications


Challenging Issues


Notes and Further Reading


Rational Agents


What is an Agent?


Agents as Rational Decision Makers


Observable Worlds and the Markov Property


Observability


The Markov Property


Stochastic Transitions and Utilities


From Goals to Utilities


Decision Making in a Stochastic World


Example: A Toy World


Notes and Further Reading


Strategic Games


Game Theory


Strategic Games


Iterated Elimination of Dominated Actions


Nash Equilibrium


Notes and Further Reading


Coordination


Coordination Games


Social Conventions


Roles


Coordination Graphs


Coordination by Variable Elimination


Coordination by Message Passing


Notes and Further Reading


Partial Observability


Thinking Interactively


Information and Knowledge


Common Knowledge


Partial Observability and Actions


States and Observations


Observation Model


Actions and Policies


Payoffs


Notes and Further Reading


Mechanism Design


Self-Interested Agents


The Mechanism Design Problem


Example: An Auction


The Revelation Principle


Example: Second-price Sealed-bid (Vickrey) Auction


The Vickrey-Clarke-Groves Mechanism


Example: Shortest Path


Notes and Further Reading


Learning


Reinforcement Learning


Markov Decision Processes


Value Iteration


Q-learning


Markov Games


Independent Learning


Coupled Learning


Sparse Cooperative Q-learning


The Problem of Exploration


Notes and Further Reading


Bibliography


Author Biography