Agent-Based Evolutionary and Immunological Optimization

Authors:
Aleksander Byrski;Marek Kisiel-Dorohinicki
Affiliations:
Department of Computer Science, AGH University of Science and Technology, Mickiewicz Avn. 30, 30-059 Cracow, Poland;Department of Computer Science, AGH University of Science and Technology, Mickiewicz Avn. 30, 30-059 Cracow, Poland
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part II
Year:
2007

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Abstract

An immunological selection mechanism for evolutionary multi-agent systems is discussed in the paper. It allows for reducing the number of fitness assignments required to get the solution of comparable quality as the classical resource-based selection in EMAS. Experimental studies aim at comparing the performance of immune-inspired selection, with resource-based one, and also with classical parallel evolutionary algorithms, based on typical multi-modal optimization benchmarks.