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121214s2013 gw | s |||| 0|eng d |
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|a 9783642340970
|9 978-3-642-34097-0
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|a 10.1007/978-3-642-34097-0
|2 doi
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|a Q342
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|2 23
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|a Czarnowski, Ireneusz.
|e editor.
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| 245 |
1 |
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|a Agent-Based Optimization
|c edited by Ireneusz Czarnowski, Piotr J drzejowicz, Janusz Kacprzyk.
|h [electronic resource] /
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| 264 |
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2013.
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| 300 |
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|a X, 203 p. 38 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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| 347 |
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|a text file
|b PDF
|2 rda
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| 490 |
1 |
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|a Studies in Computational Intelligence,
|v 456
|x 1860-949X ;
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| 505 |
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|a 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.
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| 520 |
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|a 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.
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| 650 |
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|a Engineering.
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| 650 |
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|a Artificial intelligence.
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| 650 |
1 |
4 |
|a Engineering.
|
| 650 |
2 |
4 |
|a Computational Intelligence.
|
| 650 |
2 |
4 |
|a Artificial Intelligence (incl. Robotics).
|
| 700 |
1 |
# |
|a J drzejowicz, Piotr.
|e editor.
|
| 700 |
1 |
# |
|a Kacprzyk, Janusz.
|e editor.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer eBooks
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| 776 |
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8 |
|i Printed edition:
|z 9783642340963
|
| 830 |
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|a Studies in Computational Intelligence,
|v 456
|x 1860-949X ;
|
| 856 |
4 |
0 |
|u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-34097-0
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| 912 |
# |
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|a ZDB-2-ENG
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| 950 |
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|a Engineering (Springer-11647)
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