Michael Bowling - Google Scholar

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	All	Since 2015
Citations	10360	6263
h-index	53	35
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Co-authors

Manuela M. VelosoHerbert A. Simon University Professor of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Neil BurchResearch scientist, DeepMindVerified email at ualberta.ca
Michael Bradley JohansonGoogle DeepMind, University of AlbertaVerified email at google.com
Joel VenessGoogle DeepMindVerified email at google.com
Marc G. BellemareGoogle BrainVerified email at google.com
Nolan BardUniversity of AlbertaVerified email at ualberta.ca
Kevin WaughCarnegie Mellon UniversityVerified email at cs.cmu.edu
Marc LanctotResearch Scientist, Google DeepMindVerified email at google.com
Brett BrowningNREC, RI, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Dale SchuurmansResearch Scientist, Google Brain / Professor, University of AlbertaVerified email at cs.ualberta.ca
Daniel LizotteAssistant Professor of Computer Science, University of Western OntarioVerified email at uwo.ca
Viliam LisýCzech Technical University in PragueVerified email at fel.cvut.cz
Marlos C. MachadoResearch Scientist, Google BrainVerified email at google.com
Martin SchmidCharles University in PragueVerified email at kam.mff.cuni.cz
Duane SzafronProfessor of Computing Science, University of AlbertaVerified email at ualberta.ca
Erin J. TalvitieAssociate Professor of Computer Science, Harvey Mudd CollegeVerified email at cs.hmc.edu
Trevor DavisPhD student, University of AlbertaVerified email at ualberta.ca
Csaba SzepesvariDeepMind & Department of Computing Science, University of AlbertaVerified email at cs.ualberta.ca
Peter StoneProfessor of Computer Science, The University of Texas at AustinVerified email at cs.utexas.edu
James R BruceGoogle ResearchVerified email at google.com

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	1479	2013
Multiagent learning using a variable learning rate M Bowling, M Veloso Artificial Intelligence 136 (2), 215-250, 2002	829	2002
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	489	2008
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	443	2017
Rational and convergent learning in stochastic games M Bowling, M Veloso International Joint Conference on Artificial Intelligence 17 (1), 1021-1026, 2001	365	2001
Heads-up limit hold’em poker is solved M Bowling, N Burch, M Johanson, O Tammelin Science 347 (6218), 145-149, 2015	331	2015
Convergence and no-regret in multiagent learning M Bowling Advances in neural information processing systems, 209-216, 2005	282	2005
Automatic gait optimization with gaussian process regression D Lizotte, T Wang, M Bowling, D Schuurmans Proc. of IJCAI, 944-949, 2007	252	2007
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	203	2005
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	199	2018
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	195	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	192*	2005
Apprenticeship learning using linear programming U Syed, M Bowling, RE Schapire Proceedings of the 25th international conference on Machine learning, 1032-1039, 2008	179	2008
An analysis of stochastic game theory for multiagent reinforcement learning M Bowling, M Veloso Carnegie-Mellon Univ Pittsburgh Pa School of Computer Science, 2000	151	2000
Dyna-style planning with linear function approximation and prioritized sweeping RS Sutton, C Szepesvári, A Geramifard, MP Bowling arXiv preprint arXiv:1206.3285, 2012	147	2012
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	128	2005
Plays as Effective Multiagent Plans Enabling Opponent-Adaptive Play Selection. MH Bowling, B Browning, MM Veloso ICAPS, 376-383, 2004	125	2004
A laplacian framework for option discovery in reinforcement learning MC Machado, MG Bellemare, M Bowling arXiv preprint arXiv:1703.00956, 2017	117	2017
Game-tree search with adaptation in stochastic imperfect-information games D Billings, A Davidson, T Schauenberg, N Burch, M Bowling, R Holte, ... International Conference on Computers and Games, 21-34, 2004	106	2004
Convergence problems of general-sum multiagent reinforcement learning M Bowling International Conference on Machine Learning, 89-94, 2000	105	2000

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