| Minatar: An atari-inspired testbed for thorough and reproducible reinforcement learning experiments K Young, T Tian arXiv preprint arXiv:1903.03176, 2019 | 112* | 2019 |
| Comparing Direct and Indirect Temporal-Difference Methods for Estimating the Variance of the Return. C Sherstan, DR Ashley, B Bennett, K Young, A White, M White, RS Sutton UAI, 63-72, 2018 | 34* | 2018 |
| Neurohex: A deep q-learning hex agent K Young, G Vasan, R Hayward Workshop on Computer Games, 3-18, 2016 | 32 | 2016 |
| Metatrace Actor-Critic: Online Step-Size Tuning by Meta-gradient Descent for Reinforcement Learning Control K Young, B Wang, ME Taylor International Joint Conference on Artificial Intelligence, 4185--4191, 2019 | 26* | 2019 |
| The Benefits of Model-Based Generalization in Reinforcement Learning K Young, A Ramesh, L Kirsch, J Schmidhuber Proceedings of the 40th International Conference on Machine Learning, 40254 …, 2023 | 12 | 2023 |
| Integrating episodic memory into a reinforcement learning agent using reservoir sampling KJ Young, RS Sutton, S Yang arXiv preprint arXiv:1806.00540, 2018 | 9 | 2018 |
| Understanding the pathologies of approximate policy evaluation when combined with greedification in reinforcement learning K Young, RS Sutton arXiv preprint arXiv:2010.15268, 2020 | 6 | 2020 |
| Variance Reduced Advantage Estimation with Hindsight Credit Assignment K Young arXiv preprint arXiv:1911.08362, 2019 | 4 | 2019 |
| A Reverse Hex Solver K Young, RB Hayward International Conference on Computers and Games, 137-148, 2016 | 4 | 2016 |
| Hindsight Network Credit Assignment: Efficient Credit Assignment in Networks of Discrete Stochastic Units K Young Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8919-8926, 2022 | 2 | 2022 |
| MoHex wins Hex 11× 11 and 13× 13 tournament RB Hayward, N Weninger, K Young, K Takada, T Zhang ICGA J.(2017, To appear), 0 | 2 | |
| Doubly-Asynchronous Value Iteration: Making Value Iteration Asynchronous in Actions T Tian, K Young, RS Sutton Advances in Neural Information Processing Systems (NeurIPS), 2022 | 1 | 2022 |
| Iterative Option Discovery for Planning, by Planning K Young, RS Sutton arXiv preprint arXiv:2310.01569, 2023 | | 2023 |
| Learning What to Remember with Online Policy Gradient Over a Reservoir K Young, RS Sutton | | |
| MOHEX WINS 2016 HEX 11X11 AND 13X13 TOURNAMENTS R Hayward, N Weninger, K Young, K Takada, T Zhang | | |
Richard S. SuttonKeen, Amii, and University of AlbertaVerified email at richsutton.com
