Effects of Personality Distribution on Collective Behavior

摘要

Optimizing group success is challenging for multi-robot sys-tems, especially for large systems such as robot swarms where even simple individual interaction rules can lead to complex group behavior. Studies of natural systems have shown that heterogeneous groups can outperform homoge-neous groups, especially when individual differences lead to role or niche specialization. This happens even when the indi-viduals are seemingly identical. Although individuals within a group may appear physically identical, they can vary widely in their personality, which significantly affects their behavior. However, determining the most effective composition of per-sonalities in a group is particularly difficult in natural systems given the ambiguities of animal personalities and the physi-cal challenges of repeated evaluations. Using a biologically-based collective movement model, we evaluate different per-sonality distributions to determine their effect on the overall success of the group. Results show that although there are distributions that are clearly more effective than others, in many cases, there is a broad range of distributions that re-sults in high group success. Furthermore, experiments using variable, or adaptive, personalities demonstrate that success-ful distributions are stable equilibriums as initially extreme distributions converge to these successful distributions as per-sonalities change.