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 JohansonArtificial.AgencyVerified email at artificial.agency
Marc LanctotResearch Scientist, DeepMindVerified email at google.com
Nolan BardVerified 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
Marlos C. MachadoUniversity of AlbertaVerified email at ualberta.ca
Viliam LisýCzech Technical University in Prague & Gen DigitalVerified email at fel.cvut.cz
Trevor DavisPhD student, University of AlbertaVerified email at ualberta.ca
Dale SchuurmansUniversity of Alberta, GoogleVerified email at cs.ualberta.ca
Daniel LizotteAssociate Professor of Computer Science; Associate Professor of Epidemiology and BiostatisticsVerified email at uwo.ca
Erin J. TalvitieAssociate Professor of Computer Science, Harvey Mudd CollegeVerified email at cs.hmc.edu
Brett BrowningNREC, RI, Carnegie Mellon UniversityVerified email at cs.cmu.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
James R BruceThird Wave Automation IncVerified email at thirdwave.ai

Michael Bowling

University of Alberta

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	3141	2013
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	1037	2017
Multiagent learning using a variable learning rate M Bowling, M Veloso Artificial Intelligence 136 (2), 215-250, 2002	1027	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	852	2008
Heads-up limit hold’em poker is solved M Bowling, N Burch, M Johanson, O Tammelin Science 347 (6218), 145-149, 2015	540	2015
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	525	2018
Rational and convergent learning in stochastic games M Bowling, M Veloso International Joint Conference on Artificial Intelligence 17 (1), 1021-1026, 2001	456	2001
Automatic gait optimization with gaussian process regression D Lizotte, T Wang, M Bowling, D Schuurmans Proc. of IJCAI, 944-949, 2007	367	2007
Convergence and no-regret in multiagent learning M Bowling Advances in neural information processing systems, 209-216, 2005	352	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	328	2009
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	300	2020
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	295*	2005
Apprenticeship learning using linear programming U Syed, M Bowling, RE Schapire Proceedings of the 25th international conference on Machine learning, 1032-1039, 2008	289	2008
A laplacian framework for option discovery in reinforcement learning MC Machado, MG Bellemare, M Bowling International Conference on Machine Learning, 2295-2304, 2017	269	2017
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	233	2005
Dyna-style planning with linear function approximation and prioritized sweeping RS Sutton, C Szepesvári, A Geramifard, MP Bowling arXiv preprint arXiv:1206.3285, 2012	220	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	199	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	173	2015
Count-based exploration with the successor representation MC Machado, MG Bellemare, M Bowling Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5125-5133, 2020	158	2020
Generalization and Regularization in DQN J Farebrother, MC Machado, M Bowling arXiv preprint arXiv:1810.00123, 2018	153	2018

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