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Marc G. Bellemare

Metrics and continuity in reinforcement learning


Feb 02, 2021
Charline Le Lan, Marc G. Bellemare, Pablo Samuel Castro

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* Accepted at AAAI 2021 
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Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning


Jan 13, 2021
Rishabh Agarwal, Marlos C. Machado, Pablo Samuel Castro, Marc G. Bellemare

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* Accepted at ICLR 2021 (Spotlight). Website: https://agarwl.github.io/pse 
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The Importance of Pessimism in Fixed-Dataset Policy Optimization


Oct 04, 2020
Jacob Buckman, Carles Gelada, Marc G. Bellemare

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Representations for Stable Off-Policy Reinforcement Learning


Jul 10, 2020
Dibya Ghosh, Marc G. Bellemare

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* ICML 2020 
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The Value-Improvement Path: Towards Better Representations for Reinforcement Learning


Jun 03, 2020
Will Dabney, André Barreto, Mark Rowland, Robert Dadashi, John Quan, Marc G. Bellemare, David Silver

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A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms


Mar 27, 2020
Philip Amortila, Doina Precup, Prakash Panangaden, Marc G. Bellemare

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* AISTATS 2020 
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Zooming for Efficient Model-Free Reinforcement Learning in Metric Spaces


Mar 09, 2020
Ahmed Touati, Adrien Ali Taiga, Marc G. Bellemare

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On Catastrophic Interference in Atari 2600 Games


Feb 28, 2020
William Fedus, Dibya Ghosh, John D. Martin, Marc G. Bellemare, Yoshua Bengio, Hugo Larochelle

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* First two authors contributed equally. Code available to reproduce experiments at https://github.com/google-research/google-research/tree/master/memento 
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Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction


Nov 28, 2019
Vishal Jain, William Fedus, Hugo Larochelle, Doina Precup, Marc G. Bellemare

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* To appear in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20). Accepted for Oral presentation 
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Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment


Aug 06, 2019
Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron Courville, Marc G. Bellemare

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* Accepted at the second Exploration in Reinforcement Learning Workshop at the 36th International Conference on Machine Learning, Long Beach, California 
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DeepMDP: Learning Continuous Latent Space Models for Representation Learning


Jun 06, 2019
Carles Gelada, Saurabh Kumar, Jacob Buckman, Ofir Nachum, Marc G. Bellemare

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* 13 pages main text, 16 pages appendix. ICML 2019 
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Hyperbolic Discounting and Learning over Multiple Horizons


Feb 28, 2019
William Fedus, Carles Gelada, Yoshua Bengio, Marc G. Bellemare, Hugo Larochelle

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Statistics and Samples in Distributional Reinforcement Learning


Feb 21, 2019
Mark Rowland, Robert Dadashi, Saurabh Kumar, Rémi Munos, Marc G. Bellemare, Will Dabney

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A Comparative Analysis of Expected and Distributional Reinforcement Learning


Feb 21, 2019
Clare Lyle, Pablo Samuel Castro, Marc G. Bellemare

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* To appear in the Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence 
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The Value Function Polytope in Reinforcement Learning


Feb 15, 2019
Robert Dadashi, Adrien Ali Taïga, Nicolas Le Roux, Dale Schuurmans, Marc G. Bellemare

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Distributional reinforcement learning with linear function approximation


Feb 08, 2019
Marc G. Bellemare, Nicolas Le Roux, Pablo Samuel Castro, Subhodeep Moitra

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* Proceedings of AISTATS 2019 
 * To appear 
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The Hanabi Challenge: A New Frontier for AI Research


Feb 01, 2019
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

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* 37 pages, 5 figures, submitted to Artificial Intelligence 
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A Geometric Perspective on Optimal Representations for Reinforcement Learning


Jan 31, 2019
Marc G. Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taiga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle

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Shaping the Narrative Arc: An Information-Theoretic Approach to Collaborative Dialogue


Jan 31, 2019
Kory W. Mathewson, Pablo Samuel Castro, Colin Cherry, George Foster, Marc G. Bellemare

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* 20 pages, 9 figures 
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Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift


Jan 27, 2019
Carles Gelada, Marc G. Bellemare

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* AAAI 2019 
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Dopamine: A Research Framework for Deep Reinforcement Learning


Dec 14, 2018
Pablo Samuel Castro, Subhodeep Moitra, Carles Gelada, Saurabh Kumar, Marc G. Bellemare

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An Introduction to Deep Reinforcement Learning


Dec 03, 2018
Vincent Francois-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau

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* Foundations and Trends in Machine Learning: Vol. 11, No. 3-4, 2018 
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Approximate Exploration through State Abstraction


Aug 29, 2018
Adrien Ali Taïga, Aaron Courville, Marc G. Bellemare

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Count-Based Exploration with the Successor Representation


Aug 14, 2018
Marlos C. Machado, Marc G. Bellemare, Michael Bowling

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An Analysis of Categorical Distributional Reinforcement Learning


Feb 22, 2018
Mark Rowland, Marc G. Bellemare, Will Dabney, Rémi Munos, Yee Whye Teh

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Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents


Dec 01, 2017
Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew Hausknecht, Michael Bowling

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