Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ... arXiv preprint arXiv:2312.11805, 2023 | 568 | 2023 |
Organizing experience: a deeper look at replay mechanisms for sample-based planning in continuous state domains Y Pan, Z Abbas, A White, A Patterson, M White IJCAI'18, 2018 | 53 | 2018 |
General value function networks M Schlegel, A Jacobsen, Z Abbas, A Patterson, A White, M White arXiv preprint arXiv:1807.06763, 2018 | 41 | 2018 |
Selective Dyna-style Planning Under Limited Model Capacity Z Abbas, S Sokota, EJ Talvitie, M White ICML'20, 2020 | 33 | 2020 |
Loss of Plasticity in Continual Deep Reinforcement Learning Z Abbas, R Zhao, J Modayil, A White, MC Machado arXiv preprint arXiv:2303.07507, 2023 | 32 | 2023 |
Planning with expectation models Y Wan, Z Abbas, A White, M White, RS Sutton IJCAI'19, 2019 | 25 | 2019 |
Investigating the Properties of Neural Network Representations in Reinforcement Learning H Wang, E Miahi, M White, MC Machado, Z Abbas, R Kumaraswamy, ... arXiv preprint arXiv:2203.15955, 2022 | 15 | 2022 |
From Eye-blinks to State Construction: Diagnostic Benchmarks for Online Representation Learning B Rafiee, Z Abbas, S Ghiassian, R Kumaraswamy, R Sutton, E Ludvig, ... arXiv preprint arXiv:2011.04590, 2020 | 8 | 2020 |
Model-based reinforcement learning with non-linear expectation models and stochastic environments Y Wan, Z Abbas, M White, RS Sutton FAIM Workshop on Prediction and Generative Modeling in Reinforcement …, 2018 | 6 | 2018 |
Selective Dyna-style Planning Using Neural Network Models with Limited Capacity Z Abbas | 2* | 2020 |
Incrementally Learning Functions of the Return B Bennett, W Chung, Z Abbas, V Liu arXiv preprint arXiv:1907.04651, 2019 | 1 | 2019 |
Towards model-free RL algorithms that scale well with unstructured data J Modayil, Z Abbas arXiv preprint arXiv:2311.02215, 2023 | | 2023 |