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A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play, , , , , , , , , and 1 other author(s). Science, 362 (6419): 1140--1144 (2018)A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning, , , , , , , and . (2017)cite arxiv:1711.00832Comment: Camera-ready copy of NIPS 2017 paper, including appendix.Computing Approximate Nash Equilibria and Robust Best-Responses Using Sampling, , and . Journal of Artificial Intelligence Research, (2011)Hindsight and Sequential Rationality of Correlated Play., , , , , , and . AAAI, page 5584-5594. AAAI Press, (2021)Online Monte Carlo Counterfactual Regret Minimization for Search in Imperfect Information Games., , and . AAMAS, page 27-36. ACM, (2015)Neural Population Learning beyond Symmetric Zero-Sum Games., , , , , and . AAMAS, page 1247-1255. International Foundation for Autonomous Agents and Multiagent Systems / ACM, (2024)A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games., , , , , , , and . ICLR, OpenReview.net, (2023)Convergence of Monte Carlo Tree Search in Simultaneous Move Games., , , and . NIPS, page 2112-2120. (2013)Search-Improved Game-Theoretic Multiagent Reinforcement Learning in General and Negotiation Games., , , , , , , , , and . AAMAS, page 2445-2447. ACM, (2023)Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research., , , and . CoRR, (2019)