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100710s2010 gw | s |||| 0|eng d |
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|a 9783642134258
|9 978-3-642-13425-8
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|a 10.1007/978-3-642-13425-8
|2 doi
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|a TA329-348
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|a TA640-643
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|a TBJ
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|a MAT003000
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|a 519
|2 23
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|a Sarker, Ruhul Amin.
|e editor.
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|a Agent-Based Evolutionary Search
|c edited by Ruhul Amin Sarker, Tapabrata Ray.
|h [electronic resource] /
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| 264 |
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1 |
|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg,
|c 2010.
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| 300 |
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|a 291p. 48 illus. in color.
|b online resource.
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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| 347 |
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|a text file
|b PDF
|2 rda
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| 490 |
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|a Adaptation, Learning, and Optimization,
|v 5
|x 1867-4534 ;
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| 505 |
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|a Agent Based Evolutionary Search: An Introduction -- Multi-agent Evolutionary Model for Global Numerical Optimization -- An Agent Based Evolutionary Approach for Nonlinear Optimization with Equality Constraints -- Multiagent-Based Approach for Risk Analysis in Mission Capability Planning -- Agent based Evolutionary Dynamic Optimization -- Divide and Conquer in Coevolution: A Difficult Balancing Act -- Complex Emergent Behaviour from Evolutionary Spatial Animat Agents -- An Agent-based Parallel Ant Algorithm with an Adaptive Migration Controller -- An attempt to Stochastic Modeling of Memetic Systems -- Searching for the Effective Bidding Strategy using Parameter Tuning in Genetic Algorithm -- PSO (Particle Swarm Optimization): One Method, Many Possible Applications -- VISPLORE: Exploring Particle Swarms by Visual Inspection.
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| 520 |
# |
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|a The performance of Evolutionary Algorithms can be enhanced by integrating the concept of agents. Agents and Multi-agents can bring many interesting features which are beyond the scope of traditional evolutionary process and learning. This book presents the state-of-the art in the theory and practice of Agent Based Evolutionary Search and aims to increase the awareness on this effective technology. This includes novel frameworks, a convergence and complexity analysis, as well as real-world applications of Agent Based Evolutionary Search, a design of multi-agent architectures and a design of agent communication and learning Strategy.
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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 |
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|a Mathematics.
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| 650 |
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|a Engineering mathematics.
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| 650 |
1 |
4 |
|a Engineering.
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| 650 |
2 |
4 |
|a Appl.Mathematics/Computational Methods of Engineering.
|
| 650 |
2 |
4 |
|a Artificial Intelligence (incl. Robotics).
|
| 650 |
2 |
4 |
|a Applications of Mathematics.
|
| 700 |
1 |
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|a Ray, Tapabrata.
|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 |
0 |
8 |
|i Printed edition:
|z 9783642134241
|
| 830 |
# |
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|a Adaptation, Learning, and Optimization,
|v 5
|x 1867-4534 ;
|
| 856 |
4 |
0 |
|u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-13425-8
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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)
|