Michael Bowling

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Manuela M. VelosoHerbert A. Simon University Professor of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Neil BurchDeepMind & Alberta Machine Intelligence Institute, University of AlbertaVerified email at ualberta.ca
Michael Bradley JohansonDeepMindVerified email at google.com
Marc LanctotResearch Scientist, Google DeepMindVerified email at google.com
Nolan BardUniversity of AlbertaVerified email at ualberta.ca
Joel VenessGoogle DeepMindVerified email at google.com
Marc G. BellemareGoogle BrainVerified email at google.com
Kevin WaughCarnegie Mellon UniversityVerified email at cs.cmu.edu
Martin SchmidGoogle DeepMindVerified email at kam.mff.cuni.cz
Dustin MorrillComputing Science PhD Candidate, University of Alberta and the Alberta Machine IntelligenceVerified email at ualberta.ca
Viliam LisýCzech Technical University in PragueVerified email at fel.cvut.cz
Marlos C. MachadoDeepMind, Amii, and University of AlbertaVerified email at google.com
Dale SchuurmansResearch Scientist, Google Brain / Professor, University of AlbertaVerified email at cs.ualberta.ca
Daniel LizotteAssociate Professor of Computer Science; Associate Professor of Epidemiology and BiostatisticsVerified email at uwo.ca
Trevor DavisPhD student, University of AlbertaVerified email at ualberta.ca
Brett BrowningNREC, RI, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Erin J. TalvitieAssociate Professor of Computer Science, Harvey Mudd CollegeVerified email at cs.hmc.edu
Duane SzafronProfessor of Computing Science, University of AlbertaVerified email at ualberta.ca
Richard S. SuttonDeepMind, Amii, and University of AlbertaVerified email at richsutton.com
Csaba SzepesvariDeepMind & University of AlbertaVerified email at cs.ualberta.ca

Michael Bowling

University of Alberta / DeepMind

Verified email at ualberta.ca - Homepage

Artificial Intelligence Machine Learning Game Theory Reinforcement Learning Computer Games


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The arcade learning environment: An evaluation platform for general agents MG Bellemare, Y Naddaf, J Veness, M Bowling Journal of Artificial Intelligence Research 47, 253-279, 2013	2613	2013
Multiagent learning using a variable learning rate M Bowling, M Veloso Artificial Intelligence 136 (2), 215-250, 2002	972	2002
Deepstack: Expert-level artificial intelligence in heads-up no-limit poker M Moravcík, M Schmid, N Burch, V Lisy, D Morrill, N Bard, T Davis, ... Science 356 (6337), 508-513, 2017	848	2017
Regret minimization in games with incomplete information M Zinkevich, M Johanson, M Bowling, C Piccione Advances in Neural Information Processing Systems 20, 1729-1736, 2008	728	2008
Heads-up limit hold’em poker is solved M Bowling, N Burch, M Johanson, O Tammelin Science 347 (6218), 145-149, 2015	478	2015
Rational and convergent learning in stochastic games M Bowling, M Veloso International Joint Conference on Artificial Intelligence 17 (1), 1021-1026, 2001	428	2001
Revisiting the arcade learning environment: Evaluation protocols and open problems for general agents MC Machado, MG Bellemare, E Talvitie, J Veness, M Hausknecht, ... Journal of Artificial Intelligence Research 61, 523-562, 2018	422	2018
Automatic gait optimization with gaussian process regression D Lizotte, T Wang, M Bowling, D Schuurmans Proc. of IJCAI, 944-949, 2007	336	2007
Convergence and no-regret in multiagent learning M Bowling Advances in neural information processing systems, 209-216, 2005	332	2005
Monte Carlo sampling for regret minimization in extensive games M Lanctot, K Waugh, M Zinkevich, M Bowling Advances in Neural Information Processing Systems 22, 1078-1086, 2009	287	2009
Bayes’ bluff: Opponent modelling in poker F Southey, M Bowling, B Larson, C Piccione, N Burch, D Billings, ... Proceedings of the 21st Annual Conference on Uncertainty in Artificial …, 2005	262*	2005
Apprenticeship learning using linear programming U Syed, M Bowling, RE Schapire Proceedings of the 25th international conference on Machine learning, 1032-1039, 2008	261	2008
STP: Skills, tactics, and plays for multi-robot control in adversarial environments B Browning, J Bruce, M Bowling, M Veloso Proceedings of the Institution of Mechanical Engineers, Part I: Journal of …, 2005	226	2005
A laplacian framework for option discovery in reinforcement learning MC Machado, MG Bellemare, M Bowling arXiv preprint arXiv:1703.00956, 2017	213	2017
The Hanabi challenge: A new frontier for AI research N Bard, JN Foerster, S Chandar, N Burch, M Lanctot, HF Song, E Parisotto, ... Artificial Intelligence 280, 103216, 2020	205	2020
Dyna-style planning with linear function approximation and prioritized sweeping RS Sutton, C Szepesvári, A Geramifard, MP Bowling arXiv preprint arXiv:1206.3285, 2012	196	2012
An analysis of stochastic game theory for multiagent reinforcement learning M Bowling, M Veloso Carnegie-Mellon Univ Pittsburgh Pa School of Computer Science, 2000	178	2000
Solving heads-up limit Texas Hold'em O Tammelin, N Burch, M Johanson, M Bowling Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015	152	2015
Bayesian sparse sampling for on-line reward optimization T Wang, D Lizotte, M Bowling, D Schuurmans Proceedings of the 22nd international conference on Machine learning, 956-963, 2005	140	2005
Plays as Effective Multiagent Plans Enabling Opponent-Adaptive Play Selection. MH Bowling, B Browning, MM Veloso ICAPS, 376-383, 2004	126	2004

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