Abstract
In this paper we consider potential game theoretic attitude coordination. We especially focus on two ordered configurations: “synchronization” and “balanced circular formation”. We first show that both problems constitute potential games by employing some global and individual objective functions, and a learning algorithm called Restrictive Spatial Adaptive Play (RSAP) leads robots to the ordered configurations with high probability even in the presence of mobility constraints. We moreover show that the problem also constitutes a group-based potential game and convergence of distribution of actions to stationary one can be accelerated. Finally, the effectiveness of the schemes is demonstrated by simulation.
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