AAAI Publications, Workshops at the Twenty-Seventh AAAI Conference on Artificial Intelligence

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Minimizing Conflicts Between Moving Agents over a Set of Non-Homotopic Paths Through Regret Minimization
Andrew S. Kimmel, Kostas Bekris

Last modified: 2013-06-29


This paper considers a game-theoretic framework for motion coordination challenges. The focus of this work is to minimize the number of interactions agents have when moving through an environment. In particular, agents employ a replanning framework and regret minimization over a set of actions, which correspond to different homotopic paths. By associating a cost to each trajectory, a motion coordination game arises. Regret minimization is argued as an appropriate technique, as agents do not have any knowledge of other agents' cost functions. This work outlines a methodology for minimizing the regret of actions in a computationally efficient way. Initial simulation results involving pairs of mobile agents show indications that the proposed framework can improve the choice of non-colliding paths compared to a greedy choice by the agents, without increasing any information requirements.


Motion Planning; Multi-Agent; Decentralized; Coordination; Game Theory; Robotics

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