Provably Efficient Multi-Agent Reinforcement Learning with Fully Decentralized Communication J Lidard, U Madhushani, NE Leonard 2022 American Control Conference (ACC), 3311-3316, 2022 | 5 | 2022 |
Feedback Control and Parameter Estimation for Lift Maximization of a Pitching Airfoil JM Lidard, D Goswami, D Snyder, G Sedky, AR Jones, DA Paley Journal of Guidance, Control, and Dynamics 44 (3), 587-594, 2021 | 4* | 2021 |
Blending Data-Driven Priors in Dynamic Games J Lidard, H Hu, A Hancock, Z Zhang, AG Contreras, V Modi, J DeCastro, ... arXiv preprint arXiv:2402.14174, 2024 | 2 | 2024 |
Risk-Calibrated Human-Robot Interaction via Set-Valued Intent Prediction J Lidard, H Pham, A Bachman, B Boateng, A Majumdar arXiv preprint arXiv:2403.15959, 2024 | | 2024 |
NashFormer: Leveraging Local Nash Equilibria for Semantically Diverse Trajectory Prediction J Lidard, O So, Y Zhang, J DeCastro, X Cui, X Huang, YL Kuo, J Leonard, ... arXiv preprint arXiv:2305.17600, 2023 | | 2023 |