Evolutionary Computation

D. Dumitrescu, Beatrice Lazzerini (Universita' di Pisa, Italy), Lakhmi C. Jain , A. Dumitrescu (University of Savoie, Avignon, France)

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English

CRC Press Inc
22 June 2000

Algorithms & data structures; Machine learning

Series: International Series on Computational Intelligence

"Evolutionary computing uses genetic algorithms to solve problems through a learning process. Each cycle of the application builds on information learned in its previous run, therefore its problem-solving ""evolves"". In this book, the authors describe the basic principles of evolutionary computing, genetic algorithms, programming, and applications. Detailed coverage of binary and real encoding, including selection, crossover, and mutation, is included in two chapters. Discussion of evolution strategies covers strategy principles, mutations, recombination, and optimization. Applications for evolutionary computing are varied. Some of those covered in this book include: decision support, training & design of neural networks, pattern recognition, genetic programming, and cellular automata."

By: D. Dumitrescu, Beatrice Lazzerini (Universita' di Pisa, Italy), Lakhmi C. Jain, A. Dumitrescu (University of Savoie, Avignon, France)
Imprint: CRC Press Inc
Country of Publication: United States
Volume: 18
Dimensions: Height: 234mm, Width: 156mm, Spine: 28mm
Weight: 743g
ISBN: 9780849305887
ISBN 10: 0849305888
Series: International Series on Computational Intelligence
Pages: 420
Publication Date: 22 June 2000
Audience: College/higher education , Professional and scholarly , Further / Higher Education , Undergraduate
Format: Hardback
Publisher's Status: Active

Principles of Evolutionary Computation Genetic Algorithms Basic Selection Schemes in Evolutionary Algorithms Selection Based on Scaling and Ranking Mechanisms Further Selection Strategies Recombination Operators within Binary Encoding Mutation and other Search Operators Schema Theorem, Building Blocks and Related Topics Real-valued Encoding Hybridization, Parameter Setting and Adaptation Adaptive Representations: Messy Genetic Algorithms, Delta Coding and Diploidic Representation Evolution Strategies and Evolutionary Programming Population Models and Parallel Implementations Genetic Programming Learning Classifier Systems Applications of Evolutionary Computation

Beatrice Lazzerini, D. Dumitrescu, Lakhmi C. Jain. A. Dumitrescu

Reviews for Evolutionary Computation

offers a presentation of the main ideas, models, and algorithms of evolutionary computation. Anyone who is inspired by the work of L. Davis or D.E. Goldberg to use evolutionary computation as a tool in hos/her daily work will find a complete overview of techniques and strategiesAnyone interested in optimization or search problems can find useful ideas, methods, and algorithms. - Journal of Chemometrics, 2002