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Statistical mechanics theory of genetic algorithms. (English) Zbl 1001.68185
Kallel, Leila (ed.) et al., Theoretical aspects of evolutionary computing. 2nd EvoNet Summer School, Middelheim campus, Univ. of Antwerp, Belgium, September 1999. Berlin: Springer. Natural Computing Series. 87-108 (2001).
Summary: This tutorial gives an introduction to the statistical mechanics method of analyzing Genetic Algorithm (GA) dynamics. The goals are to study GAs acting on specific problems which include realistic features such as: finite population effects, crossover, large search spaces, and realistic cost functions. Statistical mechanics allows one to derive deterministic equations of motion which describe average quantities of the population after selection, mutation, and crossover in terms of those before. The general ideas of this approach are described here, and some details given via consideration of a specific problem. Finally, a description of the literature is given.
For the entire collection see [Zbl 0962.00007].

68W05 Nonnumerical algorithms
68T05 Learning and adaptive systems in artificial intelligence
82B99 Equilibrium statistical mechanics