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News/Mitigating Retaliatory Algorithmic Collusion in Repeated Games
arxiv
PublishedSeptember 18, 2026 at 4:00 AM

Mitigating Retaliatory Algorithmic Collusion in Repeated Games

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arXiv:2609.20548v1 Announce Type: cross Abstract: Reinforcement learning agents trained to maximize their own reward in repeated interactions can converge to supra-competitive outcomes resembling explicit collusion, without communication or shared design. Existing mitigation approaches are largely t

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