Michael Bowling

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Neil BurchSony AI & Alberta Machine Intelligence Institute, University of AlbertaVerified email at ualberta.ca
Manuela M. VelosoHerbert A. Simon University Professor of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Michael Bradley JohansonArtificial.AgencyVerified email at artificial.agency
Marc LanctotResearch Scientist, Google DeepMindVerified email at google.com
Nolan BardSenior Research Scientist, Sony AIVerified email at ualberta.ca
Joel VenessGoogle DeepMindVerified email at google.com
Marc G. BellemareReliant AIVerified email at reliant.ai
Martin SchmidGoogle DeepMindVerified email at kam.mff.cuni.cz
Kevin WaughCarnegie Mellon UniversityVerified email at cs.cmu.edu
Dustin MorrillSony AIVerified email at sony.com
Marlos C. MachadoUniversity of Alberta; AmiiVerified email at ualberta.ca
Viliam LisýCzech Technical University in PragueVerified email at fel.cvut.cz
Erin J. TalvitieAssociate Professor of Computer Science, Harvey Mudd CollegeVerified email at cs.hmc.edu
Dale SchuurmansUniversity of Alberta, Google DeepMindVerified 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
Duane SzafronProfessor of Computing Science, University of AlbertaVerified email at ualberta.ca
Richard S. SuttonKeen, Amii, and University of AlbertaVerified email at richsutton.com
James R BruceThird Wave Automation IncVerified email at thirdwave.ai

Michael Bowling

Amii, 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	3796	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	1247	2017
Multiagent learning using a variable learning rate M Bowling, M Veloso Artificial Intelligence 136 (2), 215-250, 2002	1089	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	1034	2008
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	670	2018
Heads-up limit hold’em poker is solved M Bowling, N Burch, M Johanson, O Tammelin Science 347 (6218), 145-149, 2015	620	2015
Rational and convergent learning in stochastic games M Bowling, M Veloso International Joint Conference on Artificial Intelligence 17 (1), 1021-1026, 2001	493	2001
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	450	2020
Automatic gait optimization with gaussian process regression D Lizotte, T Wang, M Bowling, D Schuurmans Proc. of IJCAI, 944-949, 2007	416	2007
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	396	2009
Convergence and no-regret in multiagent learning M Bowling Advances in neural information processing systems, 209-216, 2005	377	2005
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	345*	2005
Apprenticeship learning using linear programming U Syed, M Bowling, RE Schapire Proceedings of the 25th international conference on Machine learning, 1032-1039, 2008	333	2008
A laplacian framework for option discovery in reinforcement learning MC Machado, MG Bellemare, M Bowling International Conference on Machine Learning, 2295-2304, 2017	323	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	247	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	241	2012
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	226	2020
An analysis of stochastic game theory for multiagent reinforcement learning M Bowling, M Veloso School of Computer Science, Carnegie Mellon University, 2000	219	2000
Generalization and Regularization in DQN J Farebrother, MC Machado, M Bowling arXiv preprint arXiv:1810.00123, 2018	206	2018
Solving heads-up limit Texas Hold'em O Tammelin, N Burch, M Johanson, M Bowling Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015	202	2015

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