Agent-based evolutionary search

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...

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Detalles Bibliográficos
Outros autores: Sarker, Ruhul A. (Directeur de la publication), Ray, Tapabrata (Directeur de la publication)
Formato: Livre numérique
Idioma:Anglais
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
Edición:1st ed. 2010.
Series:Adaptation, Learning, and Optimization 5
Acceso en liña:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Nota: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Agent-Based Evolutionary Search, Texte imprimé, 9783642134241
• Agent-Based Evolutionary Search, Texte imprimé, 9783642263682
• Agent-Based Evolutionary Search, Texte imprimé, 9783642134265
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505 1 |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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520 |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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