| Appl: Adaptive planner parameter learning X Xiao, Z Wang, Z Xu, B Liu, G Warnell, G Dhamankar, A Nair, P Stone Robotics and Autonomous Systems 154, 104132, 2022 | 62 | 2022 |
| Applr: Adaptive planner parameter learning from reinforcement Z Xu, G Dhamankar, A Nair, X Xiao, G Warnell, B Liu, Z Wang, P Stone 2021 IEEE international conference on robotics and automation (ICRA), 6086-6092, 2021 | 59 | 2021 |
| Appli: Adaptive planner parameter learning from interventions Z Wang, X Xiao, B Liu, G Warnell, P Stone 2021 IEEE international conference on robotics and automation (ICRA), 6079-6085, 2021 | 54 | 2021 |
| Apple: Adaptive planner parameter learning from evaluative feedback Z Wang, X Xiao, G Warnell, P Stone IEEE Robotics and Automation Letters 6 (4), 7744-7749, 2021 | 48 | 2021 |
| Causal dynamics learning for task-independent state abstraction Z Wang, X Xiao, Z Xu, Y Zhu, P Stone arXiv preprint arXiv:2206.13452, 2022 | 43 | 2022 |
| From agile ground to aerial navigation: Learning from learned hallucination Z Wang, X Xiao, AJ Nettekoven, K Umasankar, A Singh, S Bommakanti, ... arXiv preprint arXiv:2108.09793, 2021 | 40 | 2021 |
| Accelerated Robot Learning via Human Brain Signals I Akinola, Z Wang, J Shi, X He, P Lapborisuth, J Xu, D Watkins-Valls, ... IEEE International Conference on Robotics and Automation, 2020, 2019 | 24 | 2019 |
| Variational objectives for Markovian dynamics with backward simulation A Khalil Moretti, Z Wang, L Wu, I Drori, I Pe’er ECAI 2020, 1371-1378, 2020 | 16 | 2020 |
| Smoothing nonlinear variational objectives with sequential Monte Carlo A Moretti, Z Wang, L Wu, I Pe'er | 14 | 2019 |
| Particle smoothing variational objectives AK Moretti, Z Wang, L Wu, I Drori, I Pe'er arXiv preprint arXiv:1909.09734, 2019 | 13 | 2019 |
| Task-independent causal state abstraction Z Wang, X Xiao, Y Zhu, P Stone Proceedings of the 35th International Conference on Neural Information …, 2021 | 11 | 2021 |
| Maximizing BCI human feedback using active learning Z Wang, J Shi, I Akinola, P Allen 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 7 | 2020 |
| Learning to correct mistakes: Backjumping in long-horizon task and motion planning Y Sung, Z Wang, P Stone Conference on Robot Learning, 2115-2124, 2023 | 6 | 2023 |
| Building minimal and reusable causal state abstractions for reinforcement learning Z Wang, C Wang, X Xiao, Y Zhu, P Stone Proceedings of the AAAI Conference on Artificial Intelligence 38 (14), 15778 …, 2024 | 5 | 2024 |
| ELDEN: exploration via local dependencies Z Wang, J Hu, P Stone, R Martín-Martín Advances in Neural Information Processing Systems 36, 2024 | 3 | 2024 |
| Clamgen: Closed-loop arm motion generation via multi-view vision-based rl I Akinola, Z Wang, P Allen 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 3 | 2021 |
| Disentangled unsupervised skill discovery for efficient hierarchical reinforcement learning J Hu, Z Wang, P Stone, R Martín-Martín arXiv preprint arXiv:2410.11251, 2024 | 2 | 2024 |
| SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions Z Wang, J Hu, C Chuck, S Chen, R Martín-Martín, A Zhang, S Niekum, ... arXiv preprint arXiv:2410.18416, 2024 | | 2024 |
| Adaptive Planner Parameter Learning for Mobile Robot Navigation in the Wild X Xiao, B Liu, G Warnell, Z Wang, Z Xu, G Dhamankar, A Nair, P Stone | | 2021 |
Peter StoneProfessor of Computer Science, The University of Texas at AustinΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα cs.utexas.edu
