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A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence/ by Nikos Vlassis.
作者:	Vlassis, Nikos.
面頁冊數:	XII, 71 p.online resource. :
Contained By:	Springer Nature eBook
標題:	Mathematical Models of Cognitive Processes and Neural Networks. -
電子資源:	https://doi.org/10.1007/978-3-031-01543-4
ISBN:	9783031015434

A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence
Vlassis, Nikos.

A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence[electronic resource] /by Nikos Vlassis. - 1st ed. 2007. - XII, 71 p.online resource. - Synthesis Lectures on Artificial Intelligence and Machine Learning,1939-4616. - Synthesis Lectures on Artificial Intelligence and Machine Learning,.

Introduction -- Rational Agents -- Strategic Games -- Coordination -- Partial Observability -- Mechanism Design -- Learning.

Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introduction to the subject, covering the theoretical foundations as well as more recent developments in a coherent and readable manner. The text is centered on the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under uncertainty. Chapter 3 is a brief introduction to game theory, explaining classical concepts like Nash equilibrium. Chapter 4 deals with the fundamental problem of coordinating a team of collaborative agents. Chapter 5 studies the problem of multiagent reasoning and decision making under partial observability. Chapter 6 focuses on the design of protocols that are stable against manipulations by self-interested agents. Chapter 7 provides a short introduction to the rapidly expanding field of multiagent reinforcement learning. The material can be used for teaching a half-semester course on multiagent systems covering, roughly, one chapter per lecture.

ISBN: 9783031015434

Standard No.: 10.1007/978-3-031-01543-4doiSubjects--Topical Terms:

884110
Mathematical Models of Cognitive Processes and Neural Networks.

LC Class. No.: Q334-342

Dewey Class. No.: 006.3

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