An immune optimization inspired by biological immune cell-cooperation for division-and-labor problem

Abstract

The purposes of the paper are to propose and evaluate an immune optimization algorithm inspired by biological immune cell-cooperation, and this algorithm solves the division-of-labor problems in a multi-agent system (MAS). The proposed algorithm solves the problem through interactions between agents, and between agents and the environment. The interactions are performed by division-and-integration processing, inspired by immune cell-cooperation and a similar co-evolutionary approach. The division-and-integration processing optimizes the work domain, and the similar co-evolutionary approach performs equal divisions. To investigate the validity, this algorithm is applied to "N-th agent's Travelling Salesmen Problem" as a typical problem of MAS. The best property for solving via MAS is clarified with some simulations.