Evolutionary Programming V: Proceedings of the Fifth Annual Conference on Evolutionary Programming (Complex Adaptive Systems) - Tapa dura

 
9780262061902: Evolutionary Programming V: Proceedings of the Fifth Annual Conference on Evolutionary Programming (Complex Adaptive Systems)

Sinopsis

February 29-March 3, 1996, San Diego, California


Evolutionary programming, originally conceived by Lawrence J. Fogel in 1960, is a stochastic and optimization method similar to genetic algorithms, but instead emphasizes the behavioral linkage between parents and their offspring, rather than emulating specific genetic operators as observed in nature.

Evolutionary Programming V will serve as a reference and forum for researchers investigating applications and theory of evolutionary programming and other related areas in evolutionary and natural computation. Chapters describe original, unpublished research in evolutionary programming, evolution strategies, genetic algorithms and genetic programming, artificial life, cultural algorithms, and other dynamic models that rely on evolutionary principles.

Topics include the use of evolutionary simulations in optimization, neural network training and design, automatic control, image processing and other applications, as well as mathematical theory or empirical analysis providing insight into the behavior of such algorithms. Of particular interest are applications of simulated evolution to problems in biology and economics.

A Bradfor Book. Complex Adaptive Systems series

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Reseña del editor

Evolutionary programming, originally conceived by Lawrence J. Fogel in 1960, is a stochastic and optimization method similar to genetic algorithms, but instead emphasizes the behavioural linkage between parents and their offspring, rather than emulating specific genetic operators as observed in nature. "Evolutionary Programming 5" should serve as a reference and forum for researchers investigating applications and theory of evolutionary programming and other related areas in evolutionary and natural computation. Chapters describe research in evolutionary programming, evolution strategies, genetic algorithms and genetic programming, artificial life, cultural algorithms, and other dynamic models that rely on evolutionary principles. Topics include the use of evolutionary simulations in optimization, neural network training and design, automatic control, image processing and other applications, as well as mathematical theory or empirical analysis providing insights into the behaviour of such algorithms. Of particular interest should be applications of simulated evolution to problems in biology and economics.

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