@selmarsmit

Agent Oriented Self-Adaptive Genetic Algorithm

, , and . Transactions of Information Processing Society of Japan, 44 (7): 61-68 (2003)

Abstract

Efficiency of Genetic Algorithms (GAs) depends largely on the parameters such as crossover rate and mutation rate. In general, however, it is difficult to adjust those parameters manually. Although there are a few researches about adaptive GAs for adjusting multiple parameters, they require extremely large computation costs. In this paper, we propose a new algorithm based on multi agent techniques which combines existing meta-GA techniques and GAs with distributed environment schemes. Through some simulations, we have confirmed that the proposed algorithm can adapt multiple parameters in reasonable computation costs.

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