Parallel Problem Solving from Nature - PPSN III : International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature, Jerusalem, Israel, October 9 - 14, 1994. Proceedings. 1st ed. 1994

種類:

電子ブック

責任表示:

edited by Yuval Davidor, Hans-Paul Schwefel, Reinhard Männer

出版情報:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1994

著者名:

• Davidor, Yuval.
• Schwefel, Hans-Paul.
• Männer, Reinhard.
• SpringerLink (Online service)

シリーズ名:

Lecture Notes in Computer Science ; 866

ISBN:

9783540490012 [3540490019]    

注記:

Lamarckian evolution, the Baldwin effect and function optimization -- Control of parallel population dynamics by social-like behavior of GA-individuals -- Studying genotype-phenotype interactions: A model of the evolution of the cell regulation network -- A diploid genetic algorithm for preserving population diversity — Pseudo-Meiosis GA -- Co-evolutionary constraint satisfaction -- Towards a theory of ‘evolution strategies’: Results for (1 , + ?)-strategies on (nearly) arbitrary fitness functions -- Advanced correlation analysis of operators for the traveling salesman problem -- Genetic algorithms with multi-parent recombination -- On the mean convergence time of evolutionary algorithms without selection and mutation -- Estimating the heritability by decomposing the genetic variance -- Analyzing hyperplane synthesis in genetic algorithms using clustered schemata -- Convergence models of genetic algorithm selection schemes -- Optimal population size under constant computation cost -- An evolutionary algorithm
This volume comprises the 61 revised refereed papers accepted for presentation at the ICEC/PPSN III conferences held jointly in Jerusalem, Israel in October 1994. With the appearance of more and more powerful computers, there is increased interest in algorithms relying upon analogies to natural processes. This book presents a wealth of new theoretical and experimental results on artificial problem solving by applying evolutionary computation metaphors, including evolution strategies, evolutionary programming, genetic algorithms, genetic programming, and classifier systems. Topics such as simulated annealing, immune networks, neural networks, fuzzy systems, and complex, real-world optimization problems are also treated.

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