| Horde: A scalable real-time architecture for learning knowledge from unsupervised sensorimotor interaction RS Sutton, J Modayil, M Delp, T Degris, PM Pilarski, A White, D Precup The 10th International Conference on Autonomous Agents and Multiagent …, 2011 | 677 | 2011 |
| RL-Glue: Language-independent software for reinforcement-learning experiments B Tanner, A White The Journal of Machine Learning Research 10, 2133-2136, 2009 | 171 | 2009 |
| Loss of plasticity in continual deep reinforcement learning Z Abbas, R Zhao, J Modayil, A White, MC Machado Conference on lifelong learning agents, 620-636, 2023 | 155 | 2023 |
| Multi-timescale nexting in a reinforcement learning robot J Modayil, A White, RS Sutton Adaptive Behavior 22 (2), 146-160, 2014 | 155 | 2014 |
| Feature construction for reinforcement learning in hearts NR Sturtevant, AM White International Conference on Computers and Games, 122-134, 2006 | 87 | 2006 |
| Developing a predictive approach to knowledge A White University of Alberta, 2015 | 85 | 2015 |
| Empirical design in reinforcement learning A Patterson, S Neumann, M White, A White Journal of Machine Learning Research 25 (318), 1-63, 2024 | 78 | 2024 |
| Adapting behavior via intrinsic reward: A survey and empirical study C Linke, NM Ady, M White, T Degris, A White Journal of artificial intelligence research 69, 1287-1332, 2020 | 62 | 2020 |
| Gradient temporal-difference learning with regularized corrections S Ghiassian, A Patterson, S Garg, D Gupta, A White, M White International Conference on Machine Learning, 3524-3534, 2020 | 62 | 2020 |
| Organizing experience: a deeper look at replay mechanisms for sample-based planning in continuous state domains Y Pan, M Zaheer, A White, A Patterson, M White arXiv preprint arXiv:1806.04624, 2018 | 62 | 2018 |
| Report on the 2008 reinforcement learning competition S Whiteson, B Tanner, A White AI Magazine 31 (2), 81-81, 2010 | 60 | 2010 |
| A greedy approach to adapting the trace parameter for temporal difference learning M White, A White arXiv preprint arXiv:1607.00446, 2016 | 54 | 2016 |
| The in-sample softmax for offline reinforcement learning C Xiao, H Wang, Y Pan, A White, M White arXiv preprint arXiv:2302.14372, 2023 | 53 | 2023 |
| Improving performance in reinforcement learning by breaking generalization in neural networks S Ghiassian, B Rafiee, YL Lo, A White arXiv preprint arXiv:2003.07417, 2020 | 49 | 2020 |
| Investigating practical linear temporal difference learning A White, M White arXiv preprint arXiv:1602.08771, 2016 | 49 | 2016 |
| General value function networks M Schlegel, A Jacobsen, Z Abbas, A Patterson, A White, M White Journal of Artificial Intelligence Research 70, 497-543, 2021 | 46 | 2021 |
| Investigating the properties of neural network representations in reinforcement learning H Wang, E Miahi, M White, MC Machado, Z Abbas, R Kumaraswamy, ... Artificial Intelligence 330, 104100, 2024 | 44 | 2024 |
| Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains M White, A White Advances in Neural Information Processing Systems, 2010 | 42 | 2010 |
| Accelerated gradient temporal difference learning Y Pan, A White, M White Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 40 | 2017 |
| Surprise and curiosity for big data robotics A White, J Modayil, RS Sutton Workshops at the Twenty-Eighth AAAI Conference on Artificial Intelligence 7, 2014 | 40 | 2014 |
Martha WhiteUniversity of AlbertaVerified email at ualberta.ca
