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03229nam a22005055i 4500 |
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978-3-642-13425-8 |
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DE-He213 |
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20151204184726.0 |
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cr nn 008mamaa |
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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 519
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|a Agent-Based Evolutionary Search
|h [electronic resource] /
|c edited by Ruhul Amin Sarker, Tapabrata Ray.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg,
|c 2010.
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| 300 |
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|a 291 p. 48 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
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|a online resource
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|a text file
|b PDF
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|a Adaptation, Learning, and Optimization,
|x 1867-4534 ;
|v 5
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|a Agent Based Evolutionary Approach: 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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|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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|a Engineering.
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| 650 |
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|a Artificial intelligence.
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| 650 |
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|a Applied 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 |
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|a Appl.Mathematics/Computational Methods of Engineering.
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| 650 |
2 |
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|a Artificial Intelligence (incl. Robotics).
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| 650 |
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4 |
|a Applications of Mathematics.
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| 700 |
1 |
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|a Sarker, Ruhul Amin.
|e editor.
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| 700 |
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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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|t Springer eBooks
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| 776 |
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|i Printed edition:
|z 9783642134241
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| 830 |
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|a Adaptation, Learning, and Optimization,
|x 1867-4534 ;
|v 5
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| 856 |
4 |
0 |
|u http://dx.doi.org/10.1007/978-3-642-13425-8
|z Full Text via HEAL-Link
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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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