Co-Evolutionary Multi-Agent System with Sexual Selection Mechanism for Multi-Objective Optimization

Co-evolutionary techniques for evolutionary algorithms are aimed at overcoming their limited adaptive capabilities and allow for the application of such algorithms to problems for which it is difficult or even impossible to formulate explicit fitness function. Sexual selection resulting from sexual conflict and co-evolution of female mate choice and male displayed trait is considered to be one of the ecological interactions responsible for maintaining population diversity. In this paper the idea of co-evolutionary multi-agent system with sexual selection mechanism for multi-objective optimization is introduced. In presented system the Pareto frontier is located by the population of agents as a result of co-evolutionary interactions between sexes. Also, results from runs of presented system against test functions and comparison to classical multi-objective evolutionary algorithms are presented.