Fate agent evolutionary algorithms with self-adaptive mutation

Arthur-Ervin Avrămiea, Giorgos Karafotias, Agoston Endre Eiben · 2014

Fate Agent EAs form a novel flavour or subclass in EC. The idea is to decompose the main loop of traditional evolutionary algorithms into three independently acting forces, implemented by the so-called Fate Agents, and create an evolutionary process by injecting these agents into a population of candidate solutions. This paper introduces an extension to the original concept, adding a mechanism to self-adapt the mutation of the Breeder Agents. The method improves the behaviour of the original Fate Agent EA on dynamically changing fitness landscapes.

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