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POMRL: No-Regret Learning-to-Plan with Increasing Horizons


Dec 30, 2022
Khimya Khetarpal, Claire Vernade, Brendan O'Donoghue, Satinder Singh, Tom Zahavy

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* 24 pages, 6 figures 

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The Paradox of Choice: Using Attention in Hierarchical Reinforcement Learning


Jan 24, 2022
Andrei Nica, Khimya Khetarpal, Doina Precup

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* 20 pages, 15 figures 

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Temporally Abstract Partial Models


Aug 06, 2021
Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, Doina Precup

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* 34 pages, 5 figures 

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Sequoia: A Software Framework to Unify Continual Learning Research


Aug 03, 2021
Fabrice Normandin, Florian Golemo, Oleksiy Ostapenko, Pau Rodriguez, Matthew D Riemer, Julio Hurtado, Khimya Khetarpal, Dominic Zhao, Ryan Lindeborg, Timothée Lesort, Laurent Charlin, Irina Rish, Massimo Caccia

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Variance Penalized On-Policy and Off-Policy Actor-Critic


Feb 03, 2021
Arushi Jain, Gandharv Patil, Ayush Jain, Khimya Khetarpal, Doina Precup

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* Accepted to the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 2021 

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Towards Continual Reinforcement Learning: A Review and Perspectives


Dec 25, 2020
Khimya Khetarpal, Matthew Riemer, Irina Rish, Doina Precup

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* Preprint, 52 pages, 8 figures 

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Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP


Jul 28, 2020
Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau

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* Accepted at the ICML 2020 Workshop on Theoretical Foundations of Reinforcement Learning. 21 pages, 12 figures 

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What can I do here? A Theory of Affordances in Reinforcement Learning


Jun 26, 2020
Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, David Abel, Doina Precup

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* Thirty-seventh International Conference on Machine Learning (ICML 2020) 

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Options of Interest: Temporal Abstraction with Interest Functions


Jan 01, 2020
Khimya Khetarpal, Martin Klissarov, Maxime Chevalier-Boisvert, Pierre-Luc Bacon, Doina Precup

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* To appear in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) 

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