cshalizi + genetic_algorithms   6

Suzuki : A Markov chain analysis of genetic algorithms: large deviation principle approach
"In this paper we prove that the stationary distribution of populations in genetic algorithms focuses on the uniform population with the highest fitness value as the selective pressure goes to ∞ and the mutation probability goes to 0. The obtained sufficient condition is based on the work of Albuquerque and Mazza (2000), who, following Cerf (1998), applied the large deviation principle approach (Freidlin-Wentzell theory) to the Markov chain of genetic algorithms. The sufficient condition is more general than that of Albuquerque and Mazza, and covers a set of parameters which were not found by Cerf."
large_deviations  markov_models  genetic_algorithms  evolution  re:bayes_as_evol  re:do-institutions-evolve 
january 2011 by cshalizi

Copy this bookmark:



description:


tags: