Niching in Evolutionary Multi-agent Systems

Niching is a group of techniques used in evolutionary algorithms, useful inseveral types of problems, including multimodal or nonstationary optimiza-tion. This paper investigates the applicability of these methods to evolutionarymulti-agent systems (EMAS), a hybrid model combining the advantages of evo-lutionary algorithms and multi-agent systems. This could increase the efficiencyof this type of algorithms and allow to apply them to a wider class of prob-lems. As a starting point, a simple but flexible EMAS framework is proposed.Then, it is shown how to extend this framework in order to introduce niching,by adapting two classical niching methods. Finally, preliminary experimentalresults show the efficiency and the simultaneous discovery of multiple optimaby this modified EMAS.

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