Integrated task and motion planning CR Garrett, R Chitnis, R Holladay, B Kim, T Silver, LP Kaelbling, ... Annual review of control, robotics, and autonomous systems 4 (1), 265-293, 2021 | 428 | 2021 |
Schema networks: Zero-shot transfer with a generative causal model of intuitive physics K Kansky, T Silver, DA Mély, M Eldawy, M Lázaro-Gredilla, X Lou, ... International conference on machine learning, 1809-1818, 2017 | 275 | 2017 |
Residual policy learning T Silver, K Allen, J Tenenbaum, L Kaelbling arXiv preprint arXiv:1812.06298, 2018 | 171 | 2018 |
Online bayesian goal inference for boundedly rational planning agents T Zhi-Xuan, J Mann, T Silver, J Tenenbaum, V Mansinghka Advances in neural information processing systems 33, 19238-19250, 2020 | 94 | 2020 |
Transforming clinical data into actionable prognosis models: machine-learning framework and field-deployable app to predict outcome of Ebola patients A Colubri, T Silver, T Fradet, K Retzepi, B Fry, P Sabeti PLoS neglected tropical diseases 10 (3), e0004549, 2016 | 80 | 2016 |
Planning with learned object importance in large problem instances using graph neural networks T Silver, R Chitnis, A Curtis, JB Tenenbaum, T Lozano-Pérez, ... Proceedings of the AAAI conference on artificial intelligence 35 (13), 11962 …, 2021 | 76 | 2021 |
Learning symbolic operators for task and motion planning T Silver, R Chitnis, J Tenenbaum, LP Kaelbling, T Lozano-Pérez 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 74 | 2021 |
PDDL planning with pretrained large language models T Silver, V Hariprasad, RS Shuttleworth, N Kumar, T Lozano-Pérez, ... NeurIPS 2022 foundation models for decision making workshop, 2022 | 69 | 2022 |
PDDLGym: Gym environments from PDDL problems T Silver, R Chitnis arXiv preprint arXiv:2002.06432, 2020 | 65 | 2020 |
Learning neuro-symbolic skills for bilevel planning T Silver, A Athalye, JB Tenenbaum, T Lozano-Pérez, LP Kaelbling arXiv preprint arXiv:2206.10680, 2022 | 56 | 2022 |
Generalized planning in pddl domains with pretrained large language models T Silver, S Dan, K Srinivas, JB Tenenbaum, L Kaelbling, M Katz Proceedings of the AAAI Conference on Artificial Intelligence 38 (18), 20256 …, 2024 | 54 | 2024 |
Few-Shot Bayesian Imitation Learning with Logical Program Policies T Silver, KR Allen, AK Lew, L Kaelbling, J Tenenbaum Thirty-Fourth AAAI Conference on Artificial Intelligence, 0 | 45* | |
Predicate invention for bilevel planning T Silver, R Chitnis, N Kumar, W McClinton, T Lozano-Pérez, L Kaelbling, ... Proceedings of the AAAI Conference on Artificial Intelligence 37 (10), 12120 …, 2023 | 44* | 2023 |
Learning neuro-symbolic relational transition models for bilevel planning R Chitnis, T Silver, JB Tenenbaum, T Lozano-Perez, LP Kaelbling 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022 | 44 | 2022 |
Reinforcement learning for classical planning: Viewing heuristics as dense reward generators C Gehring, M Asai, R Chitnis, T Silver, L Kaelbling, S Sohrabi, M Katz Proceedings of the International Conference on Automated Planning and …, 2022 | 36 | 2022 |
Glib: Efficient exploration for relational model-based reinforcement learning via goal-literal babbling R Chitnis, T Silver, JB Tenenbaum, LP Kaelbling, T Lozano-Pérez Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 11782 …, 2021 | 36* | 2021 |
Camps: Learning context-specific abstractions for efficient planning in factored mdps R Chitnis, T Silver, B Kim, L Kaelbling, T Lozano-Perez Conference on robot learning, 64-79, 2021 | 31 | 2021 |
Learning sparse relational transition models V Xia, W Zi, K Allen, T Silver, LP Kaelbling International Conference on Learning Representations (ICLR), 2019 | 29 | 2019 |
Discovering state and action abstractions for generalized task and motion planning A Curtis, T Silver, JB Tenenbaum, T Lozano-Pérez, L Kaelbling Proceedings of the AAAI conference on artificial intelligence 36 (5), 5377-5384, 2022 | 25 | 2022 |
Behavior is everything: Towards representing concepts with sensorimotor contingencies N Hay, M Stark, A Schlegel, C Wendelken, D Park, E Purdy, T Silver, ... Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 25 | 2018 |