Immune clonal strategy based on the adaptive mean mutation

Authors:
Ruochen Liu;Licheng Jiao
Affiliations:
Institute of Intelligent Information Processing, Xidian University, Xi'an, China;Institute of Intelligent Information Processing, Xidian University, Xi'an, China
Venue:
LSMS'07 Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications
Year:
2007

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Abstract

Based on the clonal selection theory, the main mechanisms of clone are analyzed in this paper. A novel strategy algorithm based on Artificial Immune System-Immune Clonal Strategy Algorithm base on the Adaptive Mean Mutation (ICSAMM), is presented, in which the Gauss mutation in the Classical Evolutionary Strategies algorithm (CES) is replaced by the Adaptive Mean one, and the size of algorithm step can be adjusted adaptively. Compared with CES, ICSAMM is shown to be an evolutionary strategy capable of avoiding prematurity, increasing the converging speed and keeping the variety of solution in the simulation. Using the theories of Markov Chain, its convergence is proved.