模拟演化和学习LNCS-4247
2006-11-14
Springer
Wang, Tzai-der (EDT)/ Li, Xiaodong (EDT)/ Chen, Shu-Heng (EDT)/ Wang, Xufa (EDT)/ Abbass, Hussein A. (EDT)
940
This book constitutes the refereed proceedings of the 6th International Conference on Simulated Evolution and Learning, SEAL 2006, held in Hefei, China in October 2006. The 117 revised full papers presented were carefully reviewed and selected from 420 submissions. The papers are organized in topical sections on evolutionary learning, evolutionary optimisation, hybrid learning, adaptive systems, theoretical issues in evolutionary computation, and real-world applications of evolutionary computation techniques.
Evolutionary Learning Evolutionary Dynamics on Graphs：The Moran Process Generalized Embedded Landscape and Its Decomposed Representation Representative Selection for Cooperative Co—evolutionary Genetic Algorithms Kernel Matching Pursuit Based on Immune Clonal Algorithm for Image Recognition Power Quality Disturbance Detection and Classification Using Chirplet Transforms Ensemble Learning Classifier System and Compact Ruleset The Role of Early Stopping and Population Size in XCS for Intrusion Derection Improving Radial Basis Function Networks for Human Face Recognition Using a Soft Compl~ting Approach Solving Traveling Salesman Problems by Artificial Immune Response A Strategy of Mutation History Learning in Immune Clonal Selection Algorithm Quantum—Inspired Immune Clonal Algorithm for Multiuser Detection in DS—CDMA Systems Innate and Adaptive Principles for an Artificial Immune System Immune—Based Dynamic Intrusion Response Model Immune Multi—agent Active Defense Model for Network Intrusion An Immune Mobile Agent Based Grid Intrusion Detection Model Solving Optimization Problem Using Multi—agent Model Based on Belief Interaction Continuous Function Optimization Using Hybrid Ant Colony Approach with Orthogonal Design Scheme Niching for Dynamic Environments Using Particle Swarm Optimization A New Ant Colony Optimization Applied for the Multidimensional Knapsack Problem Numerical Optimization Using Organizational Particle Swarm Algorithm A Hybrid Discrete Particle Swarm Algorithm for Open—Shop Problems Particle Swarms Cooperative Optimization for Coalition Generation Problem……Evolurionary OptimisationHybrid LearningTheoretical Issue in Evolutionary ComprtationReal-World Applications of Evolutionary Computation TechnipuesAuthor Index
