Ganging up: team-based aggression expands the population/performance envelope in a multi-robot system

We examine a team of robots with no centralized control performing a transportation task in which robots frequently interfere with each other, thus impairing overall team's performance. It has previously been shown that stereo-typed robot-robot competitions, inspired by aggressive displays in animals, can be used to effectively reduce interference and improve system performance for this task. We describe an extension to the previous best-performing 'aggression function' to dynamic teams of robots. Experimental results show that the new method provides the best performance yet seen. Further, we examine the effects of interference-reduction methods over a range of population sizes, and we compare the results to a previously suggested theoretical model

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