Decision Support for Human Organizations by Multi-agent Based Evolutionary Computation

Abstract

A problem which arises in a human organization is often a multi-objective optimization problem or a single-objective one in which different fitness functions brought by humans coexist. In such cases, we need a two-stage process which consists of producing diverse solution candidates by computers and selecting a final solution from among the solution candidates by humans. Then, a method which unifies the two stages for efficient search is needed. In this study, we propose an evolutionary algorithm in the style of multi-agent system as one of the unified methods. In addition, we apply the proposed algorithm to the task in which a human group creates its representative avatar and show the basic usefulness of the algorithm.