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IBM Journal of Research and Development
A. L. Samuel, Some studies in machine learning using the game of checkers · 1959
Earlier work this paper cites.
The Annals of Mathematical Statistics
P. J. Huber, Robust Estimation of a Location Parameter · 1964
Earlier work this paper cites.
Artificial Intelligence
D. E. Knuth, R. W. Moore, An analysis of alpha-beta pruning · 1975
Earlier work this paper cites.
ACM Annual Conference
T. A. Marsland, M. Campbell, A survey of enhancements to the alpha-beta algorithm · 1981
Earlier work this paper cites.
Game of the year 1983: Scotland Yard, https://www.spiel-des-jahres.de/spiel-des-jahres-1983-scotland-yard/
1983
Earlier work this paper cites.
A. Elo, The Rating of Chessplayers, Past and Present
1986
Earlier work this paper cites.
Neural Comput
G. Tesauro, TD-Gammon, a self-teaching backgammon program, achieves master-level play · 1994
Earlier work this paper cites.
ACM Conference on Computer Science
J. Schaeffer, A. Plaat, New advances in alpha-beta searching · 1996
Earlier work this paper cites.
Econometrica
S. Hart, A. Mas-Colell, A simple adaptive procedure leading to correlated equilibrium · 2000
Earlier work this paper cites.
Artificial Intelligence
M. Campbell, A. J. Hoane, F.-h. Hsu, Deep blue · 2002
Earlier work this paper cites.
Proceedings of the Twenty-First Conference on Uncertaintyin Artificial Intelligence (UAI)
F. Southey, M. Bowling, B. Larson, C. Piccione, N. Burch, D. Billings, C. Rayner, Bayes’ bluff: Opponent modelling in poker · 2005
Earlier work this paper cites.
In: ECML-06. Number 4212 in LNCS
L. Kocsis, C. Szepesvári, Bandit based Monte-Carlo planning · 2006
Earlier work this paper cites.
Computers and Games
R. Coulom, Efficient selectivity and backup operators in Monte-Carlo tree search · 2007
Earlier work this paper cites.
Thirty-fourth Annual Conference on Neural Information Processing Systems
N. Brown, A. Bakhtin, A. Lerer, Q. Gong, Combining deep reinforcement learning and search for imperfect-information games · 2007
Earlier work this paper cites.
Advances in Neural Information Processing Systems 20
M. Zinkevich, M. Johanson, M. Bowling, C. Piccione, Regret minimization in games with incomplete information · 2008
Earlier work this paper cites.
Advances in Neural Information Processing Systems 22
M. Lanctot, K. Waugh, M. Zinkevich, M. Bowling, Monte Carlo sampling for regret minimization in extensive games · 2009
Earlier work this paper cites.
T. G. D. Team, Gnugo (2009). https://www.gnu.org/software/gnugo/
2009
Earlier work this paper cites.
S. J. Russell, P. Norvig, Artificial Intelligence: A Modern Approach
2010
Earlier work this paper cites.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence
J. Long, N. R. Sturtevant, M. Buro, T. Furtak, Understanding the success of perfect information Monte Carlo sampling in game tree search · 2010
Earlier work this paper cites.
CG’10: Proceedings of the 7th international conference on Computers and games
R. B. Segal, On the scalability of parallel UCT · 2010
Earlier work this paper cites.
Communications of the ACM
S. Gelly, L. Kocsis, M. Schoenauer, M. Sebag, D. Silver, C. Szepesvári, O. Teytaud, The grand challenge of computer Go: Monte Carlo tree search and extensions · 2012
Earlier work this paper cites.
IEEE Transactions on Computational Intelligence and AI in Games
C. B. Browne, E. Powley, D. Whitehouse, S. M. Lucas, P. I. Cowling, P. Rohlfshagen, S. Tavener, D. Perez, S. Samothrakis, S. Colton, A survey of monte carlo tree search methods · 2012
Earlier work this paper cites.
Proceedings of the Eleventh International Conference on Autonomous Agents and Multi-Agent Systems
M. Johanson, N. Bard, M. Lanctot, R. Gibson, M. Bowling, Efficient nash equilibrium approximation through Monte Carlo counterfactual regret minimization · 2012
Cited alongside, same era.
IEEE Transactions on Computational Intelligence and AI in Games
P. I. Cowling, E. J. Powley, D. Whitehouse, Information set Monte Carlo tree search · 2012
Cited alongside, same era.
IEEE Transactions on Computational Intelligence and AI in Games
J. Nijssen, M. Winands, Monte-Carlo tree search for the hide-and-seek game scotland yard · 2012
Cited alongside, same era.
J. Nijssen, Monte-carlo tree search for multi-player games, Ph.D. thesis, Maastricht University (2013)
2013
Cited alongside, same era.
M. Johanson, Measuring the size of large no-limit poker games (2013)
2013
Cited alongside, same era.
Proceedings of the Eighth International Conference on Learning Representations
H. Li, K. Hu, S. Zhang, Y. Qi, L. Song, Double neural counterfactual regret minimization · 2019
Later among the works it cites.
Proceedings of the 28th International Joint Conference on Artificial Intelligence
E. Lockhart, M. Lanctot, J. Pérolat, J.-B. Lespiau, D. Morrill, F. Timbers, K. Tuyls, Computing approximate equilibria in sequential adversarial games by exploitability descent · 2019
Later among the works it cites.
J. N. Foerster, F. Song, E. Hughes, N. Burch, I. Dunning, S. Whiteson, M. Botvinick, M. Bowling, Bayesian action decoder for deep multi-agent reinforcement learning (2019)
2019
Later among the works it cites.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems
M. Šustr, V. Kovařík, V. Lisỳ, Monte Carlo continual resolving for online strategy computation in imperfect information games · 2019
Later among the works it cites.
Artificial Intelligence
N. Bard, J. N. Foerster, S. Chandar, N. Burch, M. Lanctot, H. F. Song, E. Parisotto, V. Dumoulin, S. Moitra, E. Hughes, I. Dunning, S. Mourad, H. Larochelle, M. G. Bellemare, M. Bowling, The Hanabi challenge: A new frontier for AI research · 2020
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E. Jackson, Slumbot NL: Solving large games with counterfactual regret minimization using sampling and distributed processing · 2013
Cited alongside, same era.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI)
N. Burch, M. Johanson, M. Bowling, Solving imperfect information games using decomposition · 2014
Cited alongside, same era.
Proceedings of the 24th International Joint Conference on Artificial Intelligence
O. Tammelin, N. Burch, M. Johanson, M. Bowling, Solving heads-up limit Texas Hold’em · 2015
Cited alongside, same era.
Proceedings of the 24th International Joint Conference on Artificial Intelligence
J. Heinrich, D. Silver, Smooth UCT search in computer poker · 2015
Cited alongside, same era.
Proceedings of the Fourteenth International Conference on Autonomous Agents and Multi-Agent Systems
V. Lisý, M. Lanctot, M. Bowling, Online Monte Carlo counterfactual regret minimization for search in imperfect information games · 2015
Cited alongside, same era.
Proceedings of the 32nd International Conference on Machine Learning (ICML 2015)
J. Heinrich, M. Lanctot, D. Silver, Fictitious self-play in extensive-form games · 2015
Cited alongside, same era.
M. B. Johanson, Robust strategies and counter-strategies: From superhuman to optimal play, Ph.D. thesis, University of Alberta (2016). http://johanson.ca/publications/theses/2016-johanson-phd-thesis/2016-johanson-phd-thesis.pdf
2016
Cited alongside, same era.
Later among the works it cites.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence
A. Lerer, H. Hu, J. Foerster, N. Brown, Improving policies via search in cooperative partially observable games · 2020
Later among the works it cites.
Proceedings of the Cooperative AI Workshop at 34th Conference on Neural Information Processing Systems
E. Lockhart, N. Burch, N. Bard, S. Borgeaud, T. Eccles, L. Smaira, R. Smith, Human-agent cooperation in bridge bidding · 2020
Later among the works it cites.
Thirty-third Conference on Neural Information Processing Systems
T. W. Anthony, T. Eccles, A. Tacchetti, J. Kramár, I. M. Gemp, T. C. Hudson, N. Porcel, M. Lanctot, J. Pérolat, R. Everett, S. Singh, T. Graepel, Y. Bachrach, Learning to play no-press Diplomacy with best response policy iteration · 2020
Later among the works it cites.
In Proceedings of the International Conference on Learning Representations
J. Gray, A. Lerer, A. Bakhtin, N. Brown, Human-level performance in no-press Diplomacy via equilibrium search · 2020
Later among the works it cites.
Proceedings of the International Conference on Autonomous Agents and Multiagent Systems
M. Šustr, M. Schmid, M. Moravčík, N. Burch, M. Lanctot, M. Bowling, Sound search in imperfect information games · 2020
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E. Steinberger, A. Lerer, N. Brown, DREAM: Deep regret minimization with advantage baselines and model-free learning (2020)
2020
Later among the works it cites.
Proceedings of the International Conference on Autonomous Agents and Multiagent Systems
D. Hennes, D. Morrill, S. Omidshafiei, R. Munos, J. Perolat, M. Lanctot, A. Gruslys, J.-B. Lespiau, P. Parmas, E. Duenez-Guzman, K. Tuyls, Neural replicator dynamics · 2020
Later among the works it cites.
A. Gruslys, M. Lanctot, R. Munos, F. Timbers, M. Schmid, J. Perolat, D. Morrill, V. Zambaldi, J.-B. Lespiau, J. Schultz, M. G. Azar, M. Bowling, K. Tuyls, The advantage regret-matching actor-critic (2020)
2020
Later among the works it cites.
Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems
A. Bakhtin, D. Wu, A. Lerer, N. Brown, No-press Diplomacy from scratch · 2021
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2021
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Proceedings of the The Thirty-eighth International Conference on Machine Learning (ICML)
J. Perolat, R. Munos, J.-B. Lespiau, S. Omidshafiei, M. Rowland, P. Ortega, N. Burch, T. Anthony, D. Balduzzi, B. D. Vylder, G. Piliouras, M. Lanctot, K. Tuyls, From Poincaré recurrence to convergence in imperfect information games: Finding equilibrium via regularization · 2021
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Proceedings of the Thirty-fifth Conference on Neural Information Processing Systems
S. McAleer, J. Lanier, P. Baldi, R. Fox, Xdo: A double oracle algorithm for extensive-form games · 2021
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Proceedings of the Thirty-fifth Conference on Neural Information Processing Systems
X. Feng, O. Slumbers, Z. Wan, B. Liu, S. M. McAleer, Y. Wen, J. Wang, Y. Yang, Neural auto-curricula in two-player zero-sum games · 2021
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Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence
S. Sokota, E. Lockhart, F. Timbers, E. Davoodi, R. D’Orazio, N. Burch, M. Schmid, M. Bowling, M. Lanctot, Solving common-payoff games with approximate policy iteration · 2021
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Proceedings of the Thirty-fifth Conference on Neural Information Processing Systems
D. Strouse, K. R. McKee, M. Botvinick, E. Hughes, R. Everett, Collaborating with humans without human data · 2021
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T. S. D. Team, Stockfish: Open source chess engine (2021). https://stockfishchess.org/
2021
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Artificial Intelligence
V. Kovarík, M. Schmid, N. Burch, M. Bowling, V. Lisý, Rethinking formal models of partially observable multiagent decision making · 2022
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