Behavioral Diversity in Learning Robot Teams

Abstract

This work investigates the origins of behavioral diversity in learning robot teams. Behavioral diversity refers to the extent to which agents assume distinct behavioral roles in a group. Most research in multi-robot teams to date has centered on homogeneous systems, with work in heterogeneous groups focused primarily on mechanical and sensor differences between agents. In contrast, this work examines teams of mechanically identical robots. These systems are interesting because they may be homogeneous or heterogeneous depending only on behavior. Behavior is an extremely flexible dimension of heterogeneity in learning teams because the agents converge to hetero- or homogeneous solutions on their own. This research provides new tools for the investigation of behavioral diversity in multi-robot systems and a significant body of results using these tools in simulated and real mobile robot experiments. The experiments specifically investigate the relationship between the reinforcement function used for training and the diversity and performance of the resulting multi-robot teams.