A statistical mechanics analysis of genetic algorithms for search and learning

Statistical mechanics can be used to derive a set of equations describing the evolution of a genetic algorithm involving crossover, mutation and selection. This paper gives an introduction to this work. It is shown how the method can be applied to to very simple problems, for which the dynamics of the genetic algorithm can be reduced to a set of nonlinear coupled difference equations. Good results are obtained when the equations are truncated to four variables.