Introduction

Jong, Marianne de

doi:10.1080/02564718908529907

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1994

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“…Researchers have experimented with different types of representations, crossover and mutation operators, special-purpose operators, and approaches to reproduction and selection. However, all of these methods have a "family resemblance" in that they take some inspiration from biological evolution and from Holland's original GA. A new term, "Evolutionary Computation," has been introduced to cover these various members of the GA family, evolutionary programming, and evolution strategies [66].…”

Section: Go To Stepmentioning

confidence: 99%

Genetic Algorithms and Artificial Life

1994

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In Artificial Life, 1 (3), 267-289. AbstractGenetic algorithms are computational models of evolution that play a central role in many artificial-life models. We review the history and current scope of research on genetic algorithms in artificial life, using illustrative examples in which the genetic algorithm is used to study how learning and evolution interact, and to model ecosystems, immune system, cognitive systems, and social systems. We also outline a number of open questions and future directions for genetic algorithms in artificial-life research.

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confidence: 99%