Agent-Based Optimization (Record no. 53521)

000 -LEADER
fixed length control field 03251nam a22004935i 4500
001 - CONTROL NUMBER
control field 978-3-642-34097-0
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421111156.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 121214s2013 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783642340970
-- 978-3-642-34097-0
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
245 10 - TITLE STATEMENT
Title Agent-Based Optimization
300 ## - PHYSICAL DESCRIPTION
Number of Pages X, 206 p.
490 1# - SERIES STATEMENT
Series statement Studies in Computational Intelligence,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Machine Learning and Multiagent Systems as Interrelated Technologies -- Ant Colony Optimization for the Multi-criteria Vehicle Navigation Problem -- Solving Instances of the Capacitated Vehicle Routing Problem Using Multi-Agent Non-Distributed and Distributed Environment -- Structure vs. Efficiency of the Cross-Entropy Based Population Learning Algorithm for Discrete-Continuous Scheduling with Continuous Resource Discretisation -- Triple-Action Agents Solving the MRCPSP/max Problem -- Team of A-Teams - a Study of the Cooperation Between Program Agents Solving Difficult Optimization Problems -- Distributed Bregman-Distance Algorithms for Min-Max Optimization -- A Probability Collectives Approach for Multi-Agent Distributed and Cooperative Optimization with Tolerance for Agent Failure.
520 ## - SUMMARY, ETC.
Summary, etc This volume presents a collection of original research works by leading specialists focusing on novel and promising approaches in which the multi-agent system paradigm is used to support, enhance or replace traditional approaches to solving difficult optimization problems. The editors have invited several well-known specialists to present their solutions, tools, and models falling under the common denominator of the agent-based optimization. The book consists of eight chapters covering examples of application of the multi-agent paradigm and respective customized tools to solve  difficult optimization problems arising in different areas such as machine learning, scheduling, transportation and, more generally, distributed and cooperative problem solving.
700 1# - AUTHOR 2
Author 2 Czarnowski, Ireneusz.
700 1# - AUTHOR 2
Author 2 Jędrzejowicz, Piotr.
700 1# - AUTHOR 2
Author 2 Kacprzyk, Janusz.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-642-34097-0
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2013.
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-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
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347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence (incl. Robotics).
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1860-949X ;
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-- ZDB-2-ENG

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