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Decentralized multi-agent trajectory planning can survive bounded adversarial perturbations of neighboring controls without sacrificing the computational tractability of exact dynamic potential games.
Effective curling strategies can be learned entirely through self-supervision, matching expert heuristics without human-annotated data.
