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Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning.

M. Johanson, E. Hughes, F. Timbers, and J. Leibo. CoRR, (2022)

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Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning.J. Pérolat, B. Vylder, D. Hennes, E. Tarassov, F. Strub, V. de Boer, P. Muller, J. Connor, N. Burch, T. Anthony and 24 other author(s). CoRR, (2022)Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning.M. Johanson, E. Hughes, F. Timbers, and J. Leibo. CoRR, (2022)Reward-respecting subtasks for model-based reinforcement learning.R. Sutton, M. Machado, G. Holland, D. Szepesvari, F. Timbers, B. Tanner, and A. White. Artif. Intell., (November 2023)Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent.E. Lockhart, M. Lanctot, J. Pérolat, J. Lespiau, D. Morrill, F. Timbers, and K. Tuyls. IJCAI, page 464-470. ijcai.org, (2019)OpenSpiel: A Framework for Reinforcement Learning in Games.M. Lanctot, E. Lockhart, J. Lespiau, V. Zambaldi, S. Upadhyay, J. Pérolat, S. Srinivasan, F. Timbers, K. Tuyls, S. Omidshafiei and 17 other author(s). CoRR, (2019)Player of Games.M. Schmid, M. Moravcik, N. Burch, R. Kadlec, J. Davidson, K. Waugh, N. Bard, F. Timbers, M. Lanctot, G. Holland and 3 other author(s). CoRR, (2021)The Advantage Regret-Matching Actor-Critic.A. Gruslys, M. Lanctot, R. Munos, F. Timbers, M. Schmid, J. Pérolat, D. Morrill, V. Zambaldi, J. Lespiau, J. Schultz and 3 other author(s). CoRR, (2020)Fast computation of Nash Equilibria in Imperfect Information Games.R. Munos, J. Pérolat, J. Lespiau, M. Rowland, B. Vylder, M. Lanctot, F. Timbers, D. Hennes, S. Omidshafiei, A. Gruslys and 3 other author(s). ICML, volume 119 of Proceedings of Machine Learning Research, page 7119-7129. PMLR, (2020)Reward-Respecting Subtasks for Model-Based Reinforcement Learning.R. Sutton, M. Machado, G. Holland, D. Szepesvari, F. Timbers, B. Tanner, and A. White. CoRR, (2022)Solving Common-Payoff Games with Approximate Policy Iteration.S. Sokota, E. Lockhart, F. Timbers, E. Davoodi, R. D'Orazio, N. Burch, M. Schmid, M. Bowling, and M. Lanctot. AAAI, page 9695-9703. AAAI Press, (2021)

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Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning.

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Disambiguation of "Timbers, Finbarr"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning.

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Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning.