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Evolutionary Inheritance Mechanisms for Multi-criteriaDecision Making in Multi-agent Systems

In this paper we study the use of different evolutionary inheritance mechanisms for the adaptation of parameters in a multi-agent system where the agents have to solve tasks that are distributed within a dynamic environment. In the studied system the agents have to form teams to execute the tasks. Deciding which task to execute next is a multi-criteria decision problem for which the agents use different ranking schemes. Agents that have successfully executed several tasks can reproduce and pass the type of ranking scheme they have used and some corresponding parameter values to their successors. Three types of evolutionary mechanisms are compared: haploid, diploid, and haplo-diploid. The latter one is new for multi-agent systems. The focus of our simulation experiments is to study the influence of the different evolutionary mechanisms on the diversity of the agents and on the resulting efficiency of the multi-agent system for different dynamic environments.