Autonomous role allocation in multi-agent systems with integrated ant division of labor models

This paper proposes a novel autonomous role allocation method for Multi-Agent Systems (MAS), inspired by the division of labor mechanisms observed in ant colonies. As MAS lack a centralized control architecture, global order must emerge through local interactions between autonomous agents and their environment. This inherent decentralized structure is expected to yield high robustness, flexibility, fault tolerance, and scalability. To address the challenge of autonomous coordination, we propose a role allocation framework incorporating three key components: the response threshold model, the response threshold variance model, and the response threshold specialization model. These models are derived directly from observed behaviors in ant colonies. Through computational simulations, we demonstrate the effectiveness of this approach in dynamic task allocation problems. Our results indicate that the proposed method enables agents to adaptively allocate roles in response to both internal and external system changes through local communication among agents.