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  • title: Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning
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            Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning
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            Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning

            Dec 2, 2022

            Speakers

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            Anton Bakhtin

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            DXW

            David X. Wu

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            Adam Lerer

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            About

            No-press Diplomacy is a complex strategy game involving both cooperation and competition that has served as a benchmark for multi-agent AI research. While self-play reinforcement learning has resulted in numerous successes in purely adversarial games like chess, Go, and poker, self-play alone is insufficient for achieving optimal performance in domains involving cooperation with humans. We address this shortcoming by first introducing a planning algorithm we call DiL-piKL that regularizes a rewa…

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            NeurIPS 2022

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