Knowledge Incorporation in Evolutionary Computation
[Book]
edited by Yaochu Jin.
Berlin, Heidelberg :
Imprint: Springer,
2005.
Studies in Fuzziness and Soft Computing,
167
1434-9922 ;
From the contents: Part I: Introduction -- A Selected Introduction to Evolutionary Computation -- Part II: Knowledge Incorporation in Initialization, Recombination and Mutation -- The Use of Collective Memory in Genetic Programming -- A Cultural Algorithm for Solving the Job Shop Scheduling Problem -- Part III: Knowledge Incorporation in Selection and Reproduction -- Learning Probabilistic Models for Enhanced Evolutionary Computation -- Probabilistic Models for Linkage Learning in Forest Management -- Part IV: Knowledge Incorporation in Fitness Evaluations -- Neural Networks for Fitness Approximation in Evolutionary Optimization -- Part V: Knowledge Incorporation Through Lifetime Learning and Human-Computer Interactions -- Knowledge Incorporation Through Lifetime Learning -- Part VI: Preference Incorporation in Multi-objective Evolutionary Computation -- Integrating User Preferences into Evolutionary Multi-Objective Optimization.
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This carefully edited book puts together the state-of-the-art and recent advances in knowledge incorporation in evolutionary computation within a unified framework. The book provides a comprehensive self-contained view of knowledge incorporation in evolutionary computation including a concise introduction to evolutionary algorithms as well as knowledge representation methods. "Knowledge Incorporation in Evolutionary Computation" is a valuable reference for researchers, students and professionals from engineering and computer science, in particular in the areas of artificial intelligence, soft computing, natural computing, and evolutionary computation.