2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2022
DOI: 10.1109/iros47612.2022.9981416
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Factorization of Dynamic Games over Spatio-Temporal Resources

Abstract: Dynamic games feature a state-space complexity that scales superlinearly with the number of players. This makes this class of games often intractable even for a handful of players. We introduce the factorization process of dynamic games as a transformation leveraging the independence of players at equilibrium to build a leaner game graph. When applicable, it yields fewer nodes, fewer players per game node, hence much faster solutions. While for the general case checking for independence of players requires to … Show more

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Cited by 3 publications
(3 citation statements)
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References 40 publications
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“…For instance, safe, ethical, and robust motion planning algorithms are benchmarked using CommonRoad scenarios in [21]- [24]. The authors in [25]- [27] utilize CommonRoad tools to demonstrate the game-theoretic aspects of autonomous vehicles. Furthermore, CommonRoad paves the way to use advanced algorithms to facilitate motion planning, such as reinforcement learning [28], [29] and geometric deep learning [30].…”
Section: A Related Workmentioning
confidence: 99%
“…For instance, safe, ethical, and robust motion planning algorithms are benchmarked using CommonRoad scenarios in [21]- [24]. The authors in [25]- [27] utilize CommonRoad tools to demonstrate the game-theoretic aspects of autonomous vehicles. Furthermore, CommonRoad paves the way to use advanced algorithms to facilitate motion planning, such as reinforcement learning [28], [29] and geometric deep learning [30].…”
Section: A Related Workmentioning
confidence: 99%
“…In decision-making for autonomous mobile robots in environments consisting of many agents, modeling the interactions between the ego agent and surrounding agents is one of the most fundamental while challenging problems [1]- [3]. In such a case, the reward (as a measure of performance) received by each agent depends not only on the agent's own actions but also on the actions of others nearby [4].…”
Section: Introductionmentioning
confidence: 99%
“…(sbae@honda-ri.com) 3 Nan Li is with the Department of Aerospace Engineering, Auburn University, AL, USA (nzl0058@auburn.edu) aggressive chaser who has been dedicated to an overtaking maneuver and coming up from behind fast, an overtakingblocking behavior can be dangerous and result in a collision. Therefore, a prediction of the opponent's future trajectory is useful in order to react optimally [9].…”
Section: Introductionmentioning
confidence: 99%