Introduction to the special issue: Trends in evolutionary methods for program induction
Evolutionary Computation
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From the Publisher: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 Chapters describe original, unpublished research in evolutionary programming, evolution strategies, genetic algorithms and genetic programming, artificial life, cultural algorithms, and other dynamic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