| The option-critic architecture PL Bacon, J Harb, D Precup Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 576 | 2017 |
| Conditional computation in neural networks for faster models E Bengio, PL Bacon, J Pineau, D Precup arXiv preprint arXiv:1511.06297, 2015 | 177 | 2015 |
| When waiting is not an option: Learning options with a deliberation cost J Harb, PL Bacon, M Klissarov, D Precup Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 72 | 2018 |
| Optiongan: Learning joint reward-policy options using generative adversarial inverse reinforcement learning P Henderson, WD Chang, PL Bacon, D Meger, J Pineau, D Precup Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 38 | 2018 |
| Convergent TREE BACKUP and RETRACE with function approximation A Touati, PL Bacon, D Precup, P Vincent International Conference on Machine Learning, 4955-4964, 2018 | 26 | 2018 |
| Learning robust options D Mankowitz, T Mann, PL Bacon, D Precup, S Mannor Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 25 | 2018 |
| Learnings options end-to-end for continuous action tasks M Klissarov, PL Bacon, J Harb, D Precup arXiv preprint arXiv:1712.00004, 2017 | 23 | 2017 |
| Learning with options that terminate off-policy A Harutyunyan, P Vrancx, PL Bacon, D Precup, A Nowe Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 15 | 2018 |
| Temporal Representation Learning PL Bacon McGill University Libraries, 2018 | 13 | 2018 |
| Understanding the curse of horizon in off-policy evaluation via conditional importance sampling Y Liu, PL Bacon, E Brunskill International Conference on Machine Learning, 6184-6193, 2020 | 10 | 2020 |
| Options of interest: Temporal abstraction with interest functions K Khetarpal, M Klissarov, M Chevalier-Boisvert, PL Bacon, D Precup Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4444-4451, 2020 | 10 | 2020 |
| Learning with options: Just deliberate and relax PL Bacon, D Precup NIPS Bounded Optimality and Rational Metareasoning Workshop, 2015 | 10 | 2015 |
| On the bottleneck concept for options discovery: Theoretical underpinnings and extension in continuous state spaces PL Bacon | 8 | 2014 |
| On the bottleneck concept for options discovery PL Bacon Ph. D. dissertation, Masters thesis, 2013 | 6 | 2013 |
| The barbados 2018 list of open issues in continual learning T Schaul, H van Hasselt, J Modayil, M White, A White, PL Bacon, J Harb, ... arXiv preprint arXiv:1811.07004, 2018 | 5 | 2018 |
| Conditional computation in neural networks using a decision-theoretic approach PL Bacon, E Bengio, J Pineau, D Precup Proceedings of the 2nd Multidisciplinary Conference on Reinforcement …, 2015 | 5 | 2015 |
| Using label propagation for learning temporally abstract actions in reinforcement learning PL Bacon, D Precup Proceedings of the Workshop on Multiagent Interaction Networks, 1-7, 2013 | 5 | 2013 |
| Xlvin: executed latent value iteration nets A Deac, P Veličković, O Milinković, PL Bacon, J Tang, M Nikolić arXiv preprint arXiv:2010.13146, 2020 | 4 | 2020 |
| Policy evaluation networks J Harb, T Schaul, D Precup, PL Bacon arXiv preprint arXiv:2002.11833, 2020 | 4 | 2020 |
| Entropy regularization with discounted future state distribution in policy gradient methods R Islam, R Seraj, PL Bacon, D Precup arXiv preprint arXiv:1912.05104, 2019 | 4 | 2019 |
Doina PrecupDeepMind and McGill UniversityVerified email at cs.mcgill.ca
