Multi-step reinforcement learning: A unifying algorithm K De Asis, J Hernandez-Garcia, G Holland, R Sutton Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 145 | 2018 |
Predicting motor sequence learning in individuals with chronic stroke KP Wadden, K De Asis, CS Mang, JL Neva, S Peters, B Lakhani, LA Boyd Neurorehabilitation and Neural Repair 31 (1), 95-104, 2017 | 44 | 2017 |
Fixed-horizon temporal difference methods for stable reinforcement learning K De Asis, A Chan, S Pitis, R Sutton, D Graves Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3741-3748, 2020 | 36 | 2020 |
Individualized challenge point practice as a method to aid motor sequence learning KP Wadden, NJ Hodges, K De Asis, JL Neva, LA Boyd Journal of Motor Behavior, 2018 | 27 | 2018 |
Per-decision multi-step temporal difference learning with control variates K De Asis, RS Sutton arXiv preprint arXiv:1807.01830, 2018 | 16 | 2018 |
Predicting Periodicity with Temporal Difference Learning K De Asis, B Bennett, RS Sutton arXiv preprint arXiv:1809.07435, 2018 | 2 | 2018 |
An Idiosyncrasy of Time-discretization in Reinforcement Learning K De Asis, RS Sutton arXiv preprint arXiv:2406.14951, 2024 | 1 | 2024 |
Value-aware Importance Weighting for Off-policy Reinforcement Learning K De Asis, E Graves, RS Sutton Conference on Lifelong Learning Agents, 745-763, 2023 | 1 | 2023 |
Inverse Policy Evaluation for Value-based Decision Making A Chan, K De Asis, RS Sutton | 1* | 2021 |
A Unified View of Multi-step Temporal Difference Learning K De Asis University of Alberta, 2018 | 1 | 2018 |
Explorations in the Foundations of Value-based Reinforcement Learning K De Asis | | 2024 |