A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence (Record no. 84800)

000 -LEADER
fixed length control field 03301nam a22005175i 4500
001 - CONTROL NUMBER
control field 978-3-031-01543-4
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730163623.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220601s2007 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031015434
-- 978-3-031-01543-4
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Vlassis, Nikos.
245 12 - TITLE STATEMENT
Title A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2007.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XII, 71 p.
490 1# - SERIES STATEMENT
Series statement Synthesis Lectures on Artificial Intelligence and Machine Learning,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- Rational Agents -- Strategic Games -- Coordination -- Partial Observability -- Mechanism Design -- Learning.
520 ## - SUMMARY, ETC.
Summary, etc 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.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-01543-4
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2007.
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-- txt
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-- computer
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-- rdamedia
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-- online resource
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-- text file
-- PDF
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650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Machine learning.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Neural networks (Computer science) .
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Machine Learning.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical Models of Cognitive Processes and Neural Networks.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1939-4616
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-- ZDB-2-SXSC

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