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Large scale empirical analysis of cooperative coevolution
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation - GECCO '11
We present a study of cooperative coevolution applied to moderately complex optimization problems in large-population environments. The study asks three questions. First: what collaboration methods perform best, and when? Second: how many subpopulations are desirable? Third: is it worthwhile to do more than one trial per fitness evaluation? We discovered that parallel methods tended to work better than sequential ones, that "shuffling" (a collaboration method) predominated in performance indoi:10.1145/2001858.2001943 dblp:conf/gecco/LukeSA11 fatcat:t3baykkonbfabosfnol4xh2jxq