Titlebook: Evolutionary Computing; AISB Workshop, Leeds Terence C. Fogarty Conference proceedings 1994 Springer-Verlag Berlin Heidelberg 1994 algorith

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靦腆

掃興

978-3-540-58483-4Springer-Verlag Berlin Heidelberg 1994

ARENA

山羊

https://doi.org/10.1007/3-540-58483-8algorithm; algorithms; artificial intelligence; evolution; evolutionary computation; genetic algorithm; ge

MENT

Formal memetic algorithms,-point crossover is defined together with representation-independentpatching and hill-climbing operators. The resulting formal algorithm is then constructed and tested empirically on the travelling sales-rep problem. Whereas the genetic algorithms tested were unable to make good progress on the prob

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A statistical mechanical formulation of the dynamics of genetic algorithms,. Rather than trying to predict what happens to each individual member of the population, methods of statistical mechanics are used to describe the evolution of statistical properties of the population. We present equations which predict these properties at one generation in terms of those at the pr

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SLUMP

Nonbinary transforms for genetic algorithm problems,ed ideas, Walsh and partition coefficients, and generalises them to the nonbinary case. These coefficients provide an efficient way of calculating the fitnesses of low order schemata and of writing the conditions that characterise deceptive functions. Functions can be analysed for deception or creat

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