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Michael H. Bowling
Michael Bowling
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- affiliation: Department of Computing Science, University of Alberta
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2020 – today
- 2024
- [j18]Farzane Aminmansour, Taher Jafferjee, Ehsan Imani, Erin J. Talvitie, Michael Bowling, Martha White:
Mitigating Value Hallucination in Dyna-Style Planning via Multistep Predecessor Models. J. Artif. Intell. Res. 80: 441-473 (2024) - [c133]David Sychrovsky, Michal Sustr, Elnaz Davoodi, Michael Bowling, Marc Lanctot, Martin Schmid:
Learning Not to Regret. AAAI 2024: 15202-15210 - [c132]Simone Parisi, Montaser Mohammedalamen, Alireza Kazemipour, Matthew E. Taylor, Michael Bowling:
Monitored Markov Decision Processes. AAMAS 2024: 1549-1557 - [c131]Diego Gomez, Michael Bowling, Marlos C. Machado:
Proper Laplacian Representation Learning. ICLR 2024 - [i58]Simone Parisi, Montaser Mohammedalamen, Alireza Kazemipour, Matthew E. Taylor, Michael Bowling:
Monitored Markov Decision Processes. CoRR abs/2402.06819 (2024) - [i57]Simone Parisi, Alireza Kazemipour, Michael Bowling:
Beyond Optimism: Exploration With Partially Observable Rewards. CoRR abs/2406.13909 (2024) - [i56]Bradley Burega, John D. Martin, Luke Kapeluck, Michael Bowling:
Meta-Gradient Search Control: A Method for Improving the Efficiency of Dyna-style Planning. CoRR abs/2406.19561 (2024) - [i55]Esraa Elelimy, Adam White, Michael Bowling, Martha White:
Real-Time Recurrent Learning using Trace Units in Reinforcement Learning. CoRR abs/2409.01449 (2024) - 2023
- [j17]Marlos C. Machado
, André Barreto, Doina Precup, Michael Bowling:
Temporal Abstraction in Reinforcement Learning with the Successor Representation. J. Mach. Learn. Res. 24: 80:1-80:69 (2023) - [c130]Alexandre Trudeau, Michael Bowling:
Targeted Search Control in AlphaZero for Effective Policy Improvement. AAMAS 2023: 842-850 - [c129]Michael Bowling, John D. Martin, David Abel, Will Dabney:
Settling the Reward Hypothesis. ICML 2023: 3003-3020 - [c128]Vojtech Kovarík, Martin Schmid, Neil Burch, Michael Bowling, Viliam Lisý:
Rethinking Formal Models of Partially Observable Multiagent Decision Making (Extended Abstract). IJCAI 2023: 6920-6924 - [i54]Alexandre Trudeau, Michael Bowling:
Targeted Search Control in AlphaZero for Effective Policy Improvement. CoRR abs/2302.12359 (2023) - [i53]Zhe Wang, Petar Velickovic, Daniel Hennes, Nenad Tomasev, Laurel Prince, Michael Kaisers, Yoram Bachrach, Romuald Elie, Li Kevin Wenliang, Federico Piccinini, William Spearman, Ian Graham, Jerome T. Connor, Yi Yang, Adrià Recasens, Mina Khan, Nathalie Beauguerlange, Pablo Sprechmann, Pol Moreno, Nicolas Heess, Michael Bowling, Demis Hassabis, Karl Tuyls:
TacticAI: an AI assistant for football tactics. CoRR abs/2310.10553 (2023) - [i52]Diego Gomez, Michael Bowling, Marlos C. Machado:
Proper Laplacian Representation Learning. CoRR abs/2310.10833 (2023) - [i51]Zahra Bashir, Michael Bowling, Levi H. S. Lelis:
Assessing the Interpretability of Programmatic Policies with Large Language Models. CoRR abs/2311.06979 (2023) - 2022
- [j16]Vojtech Kovarík
Rethinking formal models of partially observable multiagent decision making. Artif. Intell. 303: 103645 (2022) - [j15]Paniz Behboudian, Yash Satsangi, Matthew E. Taylor, Anna Harutyunyan, Michael Bowling:
Policy invariant explicit shaping: an efficient alternative to reward shaping. Neural Comput. Appl. 34(3): 1673-1686 (2022) - [c127]Finbarr Timbers, Nolan Bard, Edward Lockhart, Marc Lanctot, Martin Schmid, Neil Burch, Julian Schrittwieser, Thomas Hubert, Michael Bowling:
Approximate Exploitability: Learning a Best Response. IJCAI 2022: 3487-3493 - [c126]Levi H. S. Lelis, João Gabriel Gama Vila Nova
Learning Curricula for Humans: An Empirical Study with Puzzles from The Witness. IJCAI 2022: 3877-3883 - [i50]Esra'a Saleh, John D. Martin, Anna Koop, Arash Pourzarabi, Michael Bowling:
Should Models Be Accurate? CoRR abs/2205.10736 (2022) - [i49]Dustin Morrill, Esra'a Saleh, Michael Bowling, Amy Greenwald
Interpolating Between Softmax Policy Gradient and Neural Replicator Dynamics with Capped Implicit Exploration. CoRR abs/2206.02036 (2022) - [i48]Richard S. Sutton, Michael H. Bowling, Patrick M. Pilarski
The Alberta Plan for AI Research. CoRR abs/2208.11173 (2022) - [i47]Aleksandra Kalinowska, Elnaz Davoodi, Florian Strub, Kory W. Mathewson, Ivana Kajic, Michael Bowling, Todd D. Murphey, Patrick M. Pilarski
Over-communicate no more: Situated RL agents learn concise communication protocols. CoRR abs/2211.01480 (2022) - [i46]Michael Bowling, John D. Martin, David Abel, Will Dabney:
Settling the Reward Hypothesis. CoRR abs/2212.10420 (2022) - 2021
- [j14]Cleyton R. Silva, Michael Bowling, Levi H. S. Lelis:
Teaching People by Justifying Tree Search Decisions: An Empirical Study in Curling. J. Artif. Intell. Res. 72: 1083-1102 (2021) - [c125]Dustin Morrill, Ryan D'Orazio, Reca Sarfati, Marc Lanctot, James R. Wright, Amy R. Greenwald, Michael Bowling:
Hindsight and Sequential Rationality of Correlated Play. AAAI 2021: 5584-5594 - [c124]Samuel Sokota, Edward Lockhart, Finbarr Timbers, Elnaz Davoodi, Ryan D'Orazio, Neil Burch, Martin Schmid, Michael Bowling, Marc Lanctot:
Solving Common-Payoff Games with Approximate Policy Iteration. AAAI 2021: 9695-9703 - [c123]Michal Sustr, Martin Schmid, Matej Moravcík, Neil Burch, Marc Lanctot, Michael Bowling:
Sound Algorithms in Imperfect Information Games. AAMAS 2021: 1674-1676 - [c122]Chris Alvin
Toward a Competitive Agent Framework for Magic: The Gathering. FLAIRS 2021 - [c121]Dustin Morrill, Ryan D'Orazio, Marc Lanctot, James R. Wright, Michael Bowling, Amy R. Greenwald:
Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games. ICML 2021: 7818-7828 - [i45]Samuel Sokota, Edward Lockhart, Finbarr Timbers, Elnaz Davoodi, Ryan D'Orazio, Neil Burch, Martin Schmid, Michael Bowling, Marc Lanctot:
Solving Common-Payoff Games with Approximate Policy Iteration. CoRR abs/2101.04237 (2021) - [i44]Dustin Morrill, Ryan D'Orazio, Marc Lanctot, James R. Wright, Michael Bowling, Amy Greenwald:
Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games. CoRR abs/2102.06973 (2021) - [i43]Montaser Mohammedalamen, Dustin Morrill, Alexander Sieusahai, Yash Satsangi, Michael Bowling:
Learning to Be Cautious. CoRR abs/2110.15907 (2021) - [i42]Dustin Morrill, Amy R. Greenwald, Michael Bowling:
The Partially Observable History Process. CoRR abs/2111.08102 (2021) - [i41]Martin Schmid, Matej Moravcik, Neil Burch, Rudolf Kadlec, Joshua Davidson, Kevin Waugh, Nolan Bard, Finbarr Timbers, Marc Lanctot, G. Zacharias Holland, Elnaz Davoodi, Alden Christianson, Michael Bowling:
Player of Games. CoRR abs/2112.03178 (2021) - 2020
- [j13]Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling:
The Hanabi challenge: A new frontier for AI research. Artif. Intell. 280: 103216 (2020) - [c120]Marlos C. Machado, Marc G. Bellemare, Michael Bowling:
Count-Based Exploration with the Successor Representation. AAAI 2020: 5125-5133 - [c119]Ryan D'Orazio, Dustin Morrill, James R. Wright, Michael Bowling:
Alternative Function Approximation Parameterizations for Solving Games: An Analysis of ƒ-Regression Counterfactual Regret Minimization. AAMAS 2020: 339-347 - [c118]Trevor Davis, Martin Schmid, Michael Bowling:
Low-Variance and Zero-Variance Baselines for Extensive-Form Games. ICML 2020: 2392-2401 - [c117]Zaheen Farraz Ahmad, Levi Lelis, Michael Bowling:
Marginal Utility for Planning in Continuous or Large Discrete Action Spaces. NeurIPS 2020 - [i40]Finbarr Timbers, Edward Lockhart, Martin Schmid, Marc Lanctot, Michael Bowling:
Approximate exploitability: Learning a best response in large games. CoRR abs/2004.09677 (2020) - [i39]Katya Kudashkina, Valliappa Chockalingam, Graham W. Taylor, Michael Bowling:
Sample-Efficient Model-based Actor-Critic for an Interactive Dialogue Task. CoRR abs/2004.13657 (2020) - [i38]Taher Jafferjee, Ehsan Imani, Erin Talvitie, Martha White, Michael Bowling:
Hallucinating Value: A Pitfall of Dyna-style Planning with Imperfect Environment Models. CoRR abs/2006.04363 (2020) - [i37]Zaheen Farraz Ahmad, Levi H. S. Lelis, Michael Bowling:
Marginal Utility for Planning in Continuous or Large Discrete Action Spaces. CoRR abs/2006.06054 (2020) - [i36]Michal Sustr, Martin Schmid, Matej Moravcík, Neil Burch, Marc Lanctot, Michael Bowling:
Sound Search in Imperfect Information Games. CoRR abs/2006.08740 (2020) - [i35]Audrunas Gruslys, Marc Lanctot, Rémi Munos, Finbarr Timbers, Martin Schmid, Julien Pérolat, Dustin Morrill, Vinícius Flores Zambaldi, Jean-Baptiste Lespiau, John Schultz, Mohammad Gheshlaghi Azar, Michael Bowling, Karl Tuyls:
The Advantage Regret-Matching Actor-Critic. CoRR abs/2008.12234 (2020) - [i34]Paniz Behboudian, Yash Satsangi, Matthew E. Taylor, Anna Harutyunyan, Michael Bowling:
Useful Policy Invariant Shaping from Arbitrary Advice. CoRR abs/2011.01297 (2020) - [i33]Dustin Morrill, Ryan D'Orazio, Reca Sarfati, Marc Lanctot, James R. Wright, Amy Greenwald, Michael Bowling:
Hindsight and Sequential Rationality of Correlated Play. CoRR abs/2012.05874 (2020)
2010 – 2019
- 2019
- [c116]Trevor Davis, Kevin Waugh, Michael Bowling:
Solving Large Extensive-Form Games with Strategy Constraints. AAAI 2019: 1861-1868 - [c115]Martin Schmid, Neil Burch, Marc Lanctot, Matej Moravcik, Rudolf Kadlec, Michael Bowling:
Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games Using Baselines. AAAI 2019: 2157-2164 - [c114]Jakob N. Foerster, H. Francis Song, Edward Hughes, Neil Burch, Iain Dunning, Shimon Whiteson, Matthew M. Botvinick, Michael Bowling:
Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning. ICML 2019: 1942-1951 - [c113]Fushan Li, Michael Bowling:
Ease-of-Teaching and Language Structure from Emergent Communication. NeurIPS 2019: 15825-15835 - [i32]Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling:
The Hanabi Challenge: A New Frontier for AI Research. CoRR abs/1902.00506 (2019) - [i31]Fushan Li, Michael Bowling:
Ease-of-Teaching and Language Structure from Emergent Communication. CoRR abs/1906.02403 (2019) - [i30]Vojtech Kovarík, Martin Schmid, Neil Burch, Michael Bowling, Viliam Lisý:
Rethinking Formal Models of Partially Observable Multiagent Decision Making. CoRR abs/1906.11110 (2019) - [i29]Trevor Davis, Martin Schmid, Michael Bowling:
Low-Variance and Zero-Variance Baselines for Extensive-Form Games. CoRR abs/1907.09633 (2019) - [i28]Ryan D'Orazio, Dustin Morrill, James R. Wright, Michael Bowling:
Alternative Function Approximation Parameterizations for Solving Games: An Analysis of f-Regression Counterfactual Regret Minimization. CoRR abs/1912.02967 (2019) - 2018
- [j12]Marlos C. Machado
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents. J. Artif. Intell. Res. 61: 523-562 (2018) - [c112]Neil Burch, Martin Schmid, Matej Moravcik, Dustin Morrill, Michael Bowling:
AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games. AAAI 2018: 949-956 - [c111]Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling:
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents (Extended Abstract). IJCAI 2018: 5573-5577 - [c110]Sriram Srinivasan, Marc Lanctot, Vinícius Flores Zambaldi, Julien Pérolat, Karl Tuyls, Rémi Munos, Michael Bowling:
Actor-Critic Policy Optimization in Partially Observable Multiagent Environments. NeurIPS 2018: 3426-3439 - [i27]G. Zacharias Holland, Erik Talvitie, Michael Bowling:
The Effect of Planning Shape on Dyna-style Planning in High-dimensional State Spaces. CoRR abs/1806.01825 (2018) - [i26]Marlos C. Machado, Marc G. Bellemare, Michael Bowling:
Count-Based Exploration with the Successor Representation. CoRR abs/1807.11622 (2018) - [i25]Martin Schmid, Neil Burch, Marc Lanctot, Matej Moravcik, Rudolf Kadlec, Michael Bowling:
Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games using Baselines. CoRR abs/1809.03057 (2018) - [i24]Trevor Davis, Kevin Waugh, Michael Bowling:
Solving Large Extensive-Form Games with Strategy Constraints. CoRR abs/1809.07893 (2018) - [i23]Jesse Farebrother, Marlos C. Machado, Michael Bowling:
Generalization and Regularization in DQN. CoRR abs/1810.00123 (2018) - [i22]Sriram Srinivasan, Marc Lanctot, Vinícius Flores Zambaldi, Julien Pérolat, Karl Tuyls, Rémi Munos, Michael Bowling:
Actor-Critic Policy Optimization in Partially Observable Multiagent Environments. CoRR abs/1810.09026 (2018) - [i21]Jakob N. Foerster, H. Francis Song, Edward Hughes, Neil Burch, Iain Dunning, Shimon Whiteson, Matthew M. Botvinick, Michael Bowling:
Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning. CoRR abs/1811.01458 (2018) - 2017
- [j11]Michael Bowling, Neil Burch, Michael Johanson, Oskari Tammelin:
Heads-up limit hold'em poker is solved. Commun. ACM 60(11): 81-88 (2017) - [c109]Neil Burch, Martin Schmid, Matej Moravcik, Michael Bowling:
AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games. AAAI Workshops 2017 - [c108]Viliam Lisý, Michael Bowling:
Eqilibrium Approximation Quality of Current No-Limit Poker Bots. AAAI Workshops 2017 - [c107]Marlos C. Machado
A Laplacian Framework for Option Discovery in Reinforcement Learning. ICML 2017: 2295-2304 - [i20]Matej Moravcík, Martin Schmid, Neil Burch, Viliam Lisý, Dustin Morrill, Nolan Bard, Trevor Davis, Kevin Waugh, Michael Johanson, Michael H. Bowling:
DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker. CoRR abs/1701.01724 (2017) - [i19]Marlos C. Machado, Marc G. Bellemare, Michael H. Bowling:
A Laplacian Framework for Option Discovery in Reinforcement Learning. CoRR abs/1703.00956 (2017) - [i18]Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling:
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents. CoRR abs/1709.06009 (2017) - 2016
- [c106]Viliam Lisý, Trevor Davis, Michael H. Bowling:
Counterfactual Regret Minimization in Sequential Security Games. AAAI 2016: 544-550 - [c105]Yitao Liang, Marlos C. Machado
State of the Art Control of Atari Games Using Shallow Reinforcement Learning. AAMAS 2016: 485-493 - [c104]Zaheen Farraz Ahmad, Robert C. Holte, Michael Bowling:
Action Selection for Hammer Shots in Curling. IJCAI 2016: 561-567 - [c103]Timothy Yee, Viliam Lisý, Michael H. Bowling:
Monte Carlo Tree Search in Continuous Action Spaces with Execution Uncertainty. IJCAI 2016: 690-697 - [c102]Kieran Milan, Joel Veness, James Kirkpatrick, Michael H. Bowling, Anna Koop, Demis Hassabis:
The Forget-me-not Process. NIPS 2016: 3702-3710 - [i17]Marlos C. Machado, Michael H. Bowling:
Learning Purposeful Behaviour in the Absence of Rewards. CoRR abs/1605.07700 (2016) - [i16]Neil Burch, Martin Schmid, Matej Moravcik, Michael H. Bowling:
AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games. CoRR abs/1612.06915 (2016) - [i15]Viliam Lisý, Michael H. Bowling:
Eqilibrium Approximation Quality of Current No-Limit Poker Bots. CoRR abs/1612.07547 (2016) - 2015
- [c101]Nolan Bard, Deon Nicholas, Csaba Szepesvári, Michael Bowling:
Decision-Theoretic Clustering of Strategies. AAAI Workshop: Computer Poker and Imperfect Information 2015 - [c100]Ujjwal Das Gupta, Erik Talvitie, Michael Bowling:
Policy Tree: Adaptive Representation for Policy Gradient. AAAI 2015: 2547-2553 - [c99]Marlos C. Machado, Sriram Srinivasan, Michael H. Bowling:
Domain-Independent Optimistic Initialization for Reinforcement Learning. AAAI Workshop: Learning for General Competency in Video Games 2015 - [c98]Erik Talvitie, Michael H. Bowling:
Pairwise Relative Offset Features for Atari 2600 Games. AAAI Workshop: Learning for General Competency in Video Games 2015 - [c97]Kevin Waugh, Dustin Morrill, James Andrew Bagnell, Michael H. Bowling:
Solving Games with Functional Regret Estimation. AAAI 2015: 2138-2145 - [c96]Kevin Waugh, Dustin Morrill, James Andrew Bagnell, Michael Bowling:
Solving Games with Functional Regret Estimation. AAAI Workshop: Computer Poker and Imperfect Information 2015 - [c95]Martha White, Junfeng Wen, Michael Bowling, Dale Schuurmans:
Optimal Estimation of Multivariate ARMA Models. AAAI 2015: 3080-3086 - [c94]Pascal Poupart, Aarti Malhotra, Pei Pei, Kee-Eung Kim, Bongseok Goh, Michael Bowling:
Approximate Linear Programming for Constrained Partially Observable Markov Decision Processes. AAAI 2015: 3342-3348 - [c93]Sriram Srinivasan, Erik Talvitie, Michael H. Bowling:
Improving Exploration in UCT Using Local Manifolds. AAAI 2015: 3386-3392 - [c92]James Neufeld, Dale Schuurmans, Michael H. Bowling:
Variance Reduction via Antithetic Markov Chains. AISTATS 2015 - [c91]Nolan Bard, Deon Nicholas, Csaba Szepesvári, Michael H. Bowling:
Decision-theoretic Clustering of Strategies. AAMAS 2015: 17-25 - [c90]Viliam Lisý, Marc Lanctot, Michael H. Bowling:
Online Monte Carlo Counterfactual Regret Minimization for Search in Imperfect Information Games. AAMAS 2015: 27-36 - [c89]Oskari Tammelin, Neil Burch, Michael Johanson, Michael Bowling:
Solving Heads-Up Limit Texas Hold'em. IJCAI 2015: 645-652 - [c88]Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling:
The Arcade Learning Environment: An Evaluation Platform for General Agents (Extended Abstract). IJCAI 2015: 4148-4152 - [e1]Michael Bowling, Marc G. Bellemare, Erik Talvitie, Joel Veness, Marlos C. Machado:
Learning for General Competency in Video Games, Papers from the 2015 AAAI Workshop, Austin, Texas, USA, January 26, 2015. AAAI Technical Report WS-15-10, AAAI Press 2015, ISBN 978-1-57735-721-6 [contents] - [i14]Yitao Liang, Marlos C. Machado, Erik Talvitie, Michael H. Bowling:
State of the Art Control of Atari Games Using Shallow Reinforcement Learning. CoRR abs/1512.01563 (2015) - 2014
- [j10]T. L. MacKay, Nolan Bard, Michael Bowling, David C. Hodgins
Do pokers players know how good they are? Accuracy of poker skill estimation in online and offline players. Comput. Hum. Behav. 31: 419-424 (2014) - [c87]Neil Burch, Michael Johanson, Michael Bowling:
Solving Imperfect Information Games Using Decomposition. AAAI 2014: 602-608 - [c86]Trevor Davis, Neil Burch, Michael Bowling:
Using Response Functions to Measure Strategy Strength. AAAI 2014: 630-636 - [c85]Nolan Bard, Michael Johanson, Michael H. Bowling:
Asymmetric abstractions for adversarial settings. AAMAS 2014: 501-508 - [i13]Marlos C. Machado, Sriram Srinivasan, Michael Bowling:
Domain-Independent Optimistic Initialization for Reinforcement Learning. CoRR abs/1410.4604 (2014) - [i12]Kevin Waugh, Dustin Morrill, J. Andrew Bagnell, Michael Bowling:
Solving Games with Functional Regret Estimation. CoRR abs/1411.7974 (2014) - 2013
- [j9]Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling:
The Arcade Learning Environment: An Evaluation Platform for General Agents. J. Artif. Intell. Res. 47: 253-279 (2013) - [j8]Arash Afkanpour, Csaba Szepesvári, Michael Bowling:
Alignment based kernel learning with a continuous set of base kernels. Mach. Learn. 91(3): 305-324 (2013) - [c84]Parisa Mazrooei, Christopher Archibald, Michael Bowling:
Automating Collusion Detection in Sequential Games. AAAI 2013: 675-682 - [c83]Daniel J. Lizotte, Michael Bowling, Susan A. Murphy:
Linear Fitted-Q Iteration with Multiple Reward Functions. ICAPS 2013 - [c82]Nolan Bard, Michael Johanson, Neil Burch, Michael Bowling:
Online implicit agent modelling. AAMAS 2013: 255-262 - [c81]Michael Johanson, Neil Burch, Richard Anthony Valenzano, Michael Bowling:
Evaluating state-space abstractions in extensive-form games. AAMAS 2013: 271-278 - [c80]Joshua Davidson, Christopher Archibald, Michael Bowling:
Baseline: practical control variates for agent evaluation in zero-sum domains. AAMAS 2013: 1005-1012 - [c79]Christopher Archibald, Neil Burch, Michael Bowling, Matthew J. Rutherford:
Rating players in games with real-valued outcomes. AAMAS 2013: 1307-1308 - [c78]Joel Veness, Martha White, Michael Bowling, András György
Partition Tree Weighting. DCC 2013: 321-330 - [c77]Arash Afkanpour, András György, Csaba Szepesvári, Michael Bowling:
A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning. ICML (1) 2013: 374-382 - [c76]Marc G. Bellemare, Joel Veness, Michael Bowling:
Bayesian Learning of Recursively Factored Environments. ICML (3) 2013: 1211-1219 - [c75]D. Chris Rayner, Nathan R. Sturtevant, Michael Bowling:
Subset Selection of Search Heuristics. IJCAI 2013: 637-643 - [i11]Neil Burch, Michael Bowling:
CFR-D: Solving Imperfect Information Games Using Decomposition. CoRR abs/1303.4441 (2013) - 2012
- [j7]Daniel J. Lizotte, Michael Bowling, Susan A. Murphy:
Linear fitted-Q iteration with multiple reward functions. J. Mach. Learn. Res. 13: 3253-3295 (2012) - [c74]Marc G. Bellemare, Joel Veness, Michael Bowling:
Investigating Contingency Awareness Using Atari 2600 Games. AAAI 2012: 864-871 - [c73]Richard G. Gibson, Marc Lanctot, Neil Burch, Duane Szafron, Michael Bowling:
Generalized Sampling and Variance in Counterfactual Regret Minimization. AAAI 2012: 1355-1361 - [c72]Michael Johanson, Nolan Bard, Neil Burch, Michael Bowling:
Finding Optimal Abstract Strategies in Extensive-Form Games. AAAI 2012: 1371-1379 - [c71]Michael Johanson, Nolan Bard, Marc Lanctot, Richard G. Gibson, Michael Bowling:
Efficient Nash equilibrium approximation through Monte Carlo counterfactual regret minimization. AAMAS 2012: 837-846 - [c70]Jeff Orkin, Gillian Smith, Michael Bowling:
Keynotes [abstracts of three keynote presentations]. CIG 2012 - [c69]Joel Veness, Kee Siong Ng
Context Tree Switching. DCC 2012: 327-336 - [c68]Michael Bowling, Martin Zinkevich:
On Local Regret. ICML 2012 - [c67]Marc Lanctot, Richard G. Gibson, Neil Burch, Michael Bowling:
No-Regret Learning in Extensive-Form Games with Imperfect Recall. ICML 2012 - [c66]Katherine Chen, Michael Bowling:
Tractable Objectives for Robust Policy Optimization. NIPS 2012: 2078-2086 - [c65]Marc G. Bellemare, Joel Veness, Michael Bowling:
Sketch-Based Linear Value Function Approximation. NIPS 2012: 2222-2230 - [i10]Arash Afkanpour, András György, Csaba Szepesvári, Michael H. Bowling:
A Randomized Strategy for Learning to Combine Many Features. CoRR abs/1205.0288 (2012) - [i9]Marc Lanctot, Richard G. Gibson, Neil Burch, Martin Zinkevich, Michael H. Bowling:
No-Regret Learning in Extensive-Form Games with Imperfect Recall. CoRR abs/1205.0622 (2012) - [i8]Richard S. Sutton, Csaba Szepesvári, Alborz Geramifard, Michael Bowling:
Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping. CoRR abs/1206.3285 (2012) - [i7]Michael Bowling, Martin Zinkevich:
On Local Regret. CoRR abs/1206.3318 (2012) - [i6]Finnegan Southey, Michael Bowling, Bryce Larson, Carmelo Piccione, Neil Burch, Darse Billings, D. Chris Rayner:
Bayes' Bluff: Opponent Modelling in Poker. CoRR abs/1207.1411 (2012) - [i5]Marc G. Bellemare, Yavar Naddaf, Joel Veness, Michael Bowling:
The Arcade Learning Environment: An Evaluation Platform for General Agents. CoRR abs/1207.4708 (2012) - [i4]Joel Veness, Martha White, Michael Bowling, András György:
Partition Tree Weighting. CoRR abs/1211.0587 (2012) - 2011
- [j6]Martin Zinkevich, Michael H. Bowling, Michael Wunder:
The lemonade stand game competition: solving unsolvable games. SIGecom Exch. 10(1): 35-38 (2011) - [c64]D. Chris Rayner, Michael H. Bowling, Nathan R. Sturtevant:
Euclidean Heuristic Optimization. AAAI 2011: 81-86 - [c63]Michael Johanson, Kevin Waugh, Michael H. Bowling, Martin Zinkevich:
Accelerating Best Response Calculation in Large Extensive Games. IJCAI 2011: 258-265 - [c62]Joel Veness, Marc Lanctot, Michael H. Bowling:
Variance Reduction in Monte-Carlo Tree Search. NIPS 2011: 1836-1844 - [i3]Michael H. Bowling, Manuela M. Veloso:
Existence of Multiagent Equilibria with Limited Agents. CoRR abs/1107.0033 (2011) - [i2]Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling:
Context Tree Switching. CoRR abs/1111.3182 (2011) - [i1]Arash Afkanpour, Csaba Szepesvári, Michael H. Bowling:
Alignment Based Kernel Learning with a Continuous Set of Base Kernels. CoRR abs/1112.4607 (2011) - 2010
- [c61]Daniel J. Lizotte, Michael H. Bowling, Susan A. Murphy:
Efficient Reinforcement Learning with Multiple Reward Functions for Randomized Controlled Trial Analysis. ICML 2010: 695-702
2000 – 2009
- 2009
- [c60]Kevin Waugh, David Schnizlein, Michael H. Bowling, Duane Szafron:
Abstraction pathologies in extensive games. AAMAS (2) 2009: 781-788 - [c59]Michael H. Bowling, Nicholas Abou Risk, Nolan Bard, Darse Billings, Neil Burch, Joshua Davidson, John Alexander Hawkin, Robert Holte, Michael Johanson, Morgan Kan, Bryce Paradis, Jonathan Schaeffer, David Schnizlein, Duane Szafron, Kevin Waugh, Martin Zinkevich:
A demonstration of the Polaris poker system. AAMAS (2) 2009: 1391-1392 - [c58]David Schnizlein, Michael H. Bowling, Duane Szafron:
Probabilistic State Translation in Extensive Games with Large Action Sets. IJCAI 2009: 278-284 - [c57]Martha White, Michael H. Bowling:
Learning a Value Analysis Tool for Agent Evaluation. IJCAI 2009: 1976-1981 - [c56]Marc Lanctot, Kevin Waugh, Martin Zinkevich, Michael H. Bowling:
Monte Carlo Sampling for Regret Minimization in Extensive Games. NIPS 2009: 1078-1086 - [c55]Kevin Waugh, Nolan Bard, Michael H. Bowling:
Strategy Grafting in Extensive Games. NIPS 2009: 2026-2034 - [c54]Kevin Waugh, Martin Zinkevich, Michael Johanson, Morgan Kan, David Schnizlein, Michael H. Bowling:
A Practical Use of Imperfect Recall. SARA 2009 - [c53]Michael Johanson, Michael H. Bowling:
Data Biased Robust Counter Strategies. AISTATS 2009: 264-271 - 2008
- [c52]Maria Cutumisu, Duane Szafron, Michael H. Bowling, Richard S. Sutton:
Agent Learning using Action-Dependent Learning Rates in Computer Role-Playing Games. AIIDE 2008 - [c51]James Neufeld, Michael Sokolsky, Jason Roberts, Adam Milstein, Stephen Walsh, Michael H. Bowling:
Autonomous geocaching: navigation and goal finding in outdoor domains. AAMAS (1) 2008: 47-54 - [c50]Michael H. Bowling, Alborz Geramifard, David Wingate:
Sigma point policy iteration. AAMAS (1) 2008: 379-386 - [c49]Michael H. Bowling, Michael Johanson, Neil Burch, Duane Szafron:
Strategy evaluation in extensive games with importance sampling. ICML 2008: 72-79 - [c48]Umar Syed, Michael H. Bowling, Robert E. Schapire:
Apprenticeship learning using linear programming. ICML 2008: 1032-1039 - [c47]Michael Biggs, Ali Ghodsi, Dana F. Wilkinson, Michael H. Bowling:
Scalable Action Respecting Embedding. ISAIM 2008 - [c46]Nathan R. Sturtevant, H. James Hoover, Jonathan Schaeffer, Sean Gouglas, Michael H. Bowling, Finnegan Southey, Matthew Bouchard, Ghassan Zabaneh:
Multidisciplinary students and instructors: a second-year games course. SIGCSE 2008: 383-387 - [c45]Richard S. Sutton, Csaba Szepesvári, Alborz Geramifard, Michael H. Bowling:
Dyna-Style Planning with Linear Function Approximation and Prioritized Sweeping. UAI 2008: 528-536 - 2007
- [c44]Nolan Bard, Michael H. Bowling:
Particle Filtering for Dynamic Agent Modelling in Simplified Poker. AAAI 2007: 515-521 - [c43]Martin Zinkevich, Michael H. Bowling, Neil Burch:
A New Algorithm for Generating Equilibria in Massive Zero-Sum Games. AAAI 2007: 788-794 - [c42]Daniel J. Lizotte, Tao Wang, Michael H. Bowling, Dale Schuurmans:
Automatic Gait Optimization with Gaussian Process Regression. IJCAI 2007: 944-949 - [c41]Michael Johanson, Martin Zinkevich, Michael H. Bowling:
Computing Robust Counter-Strategies. NIPS 2007: 721-728 - [c40]Tao Wang, Daniel J. Lizotte, Michael H. Bowling, Dale Schuurmans:
Stable Dual Dynamic Programming. NIPS 2007: 1569-1576 - [c39]Martin Zinkevich, Michael Johanson, Michael H. Bowling, Carmelo Piccione:
Regret Minimization in Games with Incomplete Information. NIPS 2007: 1729-1736 - 2006
- [j5]Michael H. Bowling, Johannes Fürnkranz
Machine learning and games. Mach. Learn. 63(3): 211-215 (2006) - [c38]Alborz Geramifard, Michael H. Bowling, Richard S. Sutton:
Incremental Least-Squares Temporal Difference Learning. AAAI 2006: 356-361 - [c37]Achim Rettinger, Martin Zinkevich, Michael H. Bowling:
Boosting Expert Ensembles for Rapid Concept Recall. AAAI 2006: 464-469 - [c36]Martin Zinkevich, Michael H. Bowling, Nolan Bard, Morgan Kan, Darse Billings:
Optimal Unbiased Estimators for Evaluating Agent Performance. AAAI 2006: 573-579 - [c35]Armita Kaboli, Michael H. Bowling, Petr Musílek:
Bayesian Calibration for Monte Carlo Localization. AAAI 2006: 964-969 - [c34]Nathan R. Sturtevant, Martin Zinkevich, Michael H. Bowling:
Prob-Maxn: Playing N-Player Games with Opponent Models. AAAI 2006: 1057-1063 - [c33]Tao Wang, Pascal Poupart, Michael H. Bowling, Dale Schuurmans:
Compact, Convex Upper Bound Iteration for Approximate POMDP Planning. AAAI 2006: 1245-1252 - [c32]Michael H. Bowling, Dana F. Wilkinson, Ali Ghodsi:
Subjective Mapping. AAAI 2006: 1569-1572 - [c31]Nathan R. Sturtevant, Michael H. Bowling:
Robust game play against unknown opponents. AAMAS 2006: 713-719 - [c30]Michael H. Bowling, Peter McCracken, Michael James, James Neufeld, Dana F. Wilkinson:
Learning predictive state representations using non-blind policies. ICML 2006: 129-136 - [c29]Alborz Geramifard, Michael H. Bowling, Martin Zinkevich, Richard S. Sutton:
iLSTD: Eligibility Traces and Convergence Analysis. NIPS 2006: 441-448 - 2005
- [c28]Michael H. Bowling, Peter McCracken:
Coordination and Adaptation in Impromptu Teams. AAAI 2005: 53-58 - [c27]Michael H. Bowling, Ali Ghodsi, Dana F. Wilkinson:
Action respecting embedding. ICML 2005: 65-72 - [c26]Tao Wang, Daniel J. Lizotte
Bayesian sparse sampling for on-line reward optimization. ICML 2005: 956-963 - [c25]Dana F. Wilkinson, Michael H. Bowling, Ali Ghodsi:
Learning Subjective Representations for Planning. IJCAI 2005: 889-894 - [c24]Michael H. Bowling, Dana F. Wilkinson, Ali Ghodsi, Adam Milstein:
Subjective Localization with Action Respecting Embedding. ISRR 2005: 190-202 - [c23]Peter McCracken, Michael H. Bowling:
Online Discovery and Learning of Predictive State Representations. NIPS 2005: 875-882 - [c22]Finnegan Southey, Michael H. Bowling, Bryce Larson, Carmelo Piccione, Neil Burch, Darse Billings, D. Chris Rayner:
Bayes? Bluff: Opponent Modelling in Poker. UAI 2005: 550-558 - 2004
- [j4]Michael H. Bowling, Manuela M. Veloso:
Existence of Multiagent Equilibria with Limited Agents. J. Artif. Intell. Res. 22: 353-384 (2004) - [c21]Peter McCracken, Michael Bowling:
Safe Strategies for Agent Modelling in Games. AAAI Technical Report (2) 2004: 103-110 - [c20]Michael H. Bowling, Brett Browning, Manuela M. Veloso:
Plays as Effective Multiagent Plans Enabling Opponent-Adaptive Play Selection. ICAPS 2004: 376-383 - [c19]Darse Billings, Aaron Davidson, Terence Schauenberg, Neil Burch, Michael H. Bowling, Robert C. Holte, Jonathan Schaeffer, Duane Szafron:
Game-Tree Search with Adaptation in Stochastic Imperfect-Information Games. Computers and Games 2004: 21-34 - [c18]Michael H. Bowling:
Convergence and No-Regret in Multiagent Learning. NIPS 2004: 209-216 - 2003
- [c17]James Bruce, Michael H. Bowling, Brett Browning, Manuela M. Veloso:
Multi-robot team response to a multi-robot opponent team. ICRA 2003: 2281-2286 - [c16]Michael H. Bowling, Manuela M. Veloso:
Simultaneous Adversarial Multi-Robot Learning. IJCAI 2003: 699-704 - [c15]Michael H. Bowling, Rune Møller Jensen, Manuela M. Veloso:
A Formalization of Equilibria for Multiagent Planning. IJCAI 2003: 1460-1462 - [c14]Michael H. Bowling, Brett Browning, Allen Chang, Manuela M. Veloso:
Plays as Team Plans for Coordination and Adaptation. RoboCup 2003: 686-693 - 2002
- [j3]Michael H. Bowling, Manuela M. Veloso:
Multiagent learning using a variable learning rate. Artif. Intell. 136(2): 215-250 (2002) - [c13]Gal A. Kaminka, Michael H. Bowling:
Towards robust teams with many agents. AAMAS 2002: 729-736 - [c12]Brett Browning, Michael H. Bowling, Manuela M. Veloso:
Improbability Filtering for Rejecting False Positives. ICRA 2002: 3038-3043 - [c11]Michael H. Bowling:
Approximation Techniques in Multiagent Learning. SARA 2002: 328-329 - 2001
- [c10]Michael H. Bowling, Manuela M. Veloso:
Convergence of Gradient Dynamics with a Variable Learning Rate. ICML 2001: 27-34 - [c9]Michael H. Bowling, Manuela M. Veloso:
Rational and Convergent Learning in Stochastic Games. IJCAI 2001: 1021-1026 - [c8]Brett Browning, Michael H. Bowling, James Bruce, Ravi Balasubramanian, Manuela M. Veloso:
CM-Dragons'01 - Vision-Based Motion Tracking and Heteregenous Robots. RoboCup 2001: 567-570 - 2000
- [j2]Manuela M. Veloso, Michael H. Bowling, Sorin Achim, Kwun Han, Peter Stone:
CMUNITED-98: RoboCup-98 Small-Robot World Champion Team. AI Mag. 21(1): 29-36 (2000) - [c7]Michael H. Bowling:
Convergence Problems of General-Sum Multiagent Reinforcement Learning. ICML 2000: 89-94
1990 – 1999
- 1999
- [c6]Manuela M. Veloso, Michael H. Bowling, Sorin Achim, Kwun Han, Peter Stone:
CMUnited-98: A Team of Robotic Soccer Agents. AAAI/IAAI 1999: 891-896 - [c5]Michael Bowling, Manuela M. Veloso:
Motion control in dynamic multi-robot environments. CIRA 1999: 168-173 - [c4]Michael H. Bowling, Manuela M. Veloso:
Bounding the Suboptimality of Reusing Subproblem. IJCAI 1999: 1340-1347 - [c3]Michael H. Bowling, Manuela M. Veloso:
Motion Control in Dynamic Multi-Robot Environments. RoboCup 1999: 222-230 - [c2]Manuela M. Veloso, Michael H. Bowling, Sorin Achim:
CMUnited-99: Small-Size Robot Team. RoboCup 1999: 661-662 - 1998
- [j1]Manuela M. Veloso, Michael H. Bowling, Peter Stone:
The CMUnited-98 champion small-robot team. Adv. Robotics 13(8): 753-766 (1998) - [c1]Manuela M. Veloso, Michael H. Bowling, Sorin Achim, Kwun Han, Peter Stone:
The CMUnited-98 Small-Robot Team. RoboCup 1998: 77-92
Coauthor Index
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