| Implicit learning dynamics in stackelberg games: Equilibria characterization, convergence analysis, and empirical study T Fiez, B Chasnov, L Ratliff International Conference on Machine Learning, 3133-3144, 2020 | 109 | 2020 |
| Convergence of learning dynamics in stackelberg games T Fiez, B Chasnov, LJ Ratliff arXiv preprint arXiv:1906.01217, 2019 | 94 | 2019 |
| Stackelberg actor-critic: Game-theoretic reinforcement learning algorithms L Zheng, T Fiez, Z Alumbaugh, B Chasnov, LJ Ratliff Proceedings of the AAAI conference on artificial intelligence 36 (8), 9217-9224, 2022 | 36 | 2022 |
| Convergence analysis of gradient-based learning in continuous games B Chasnov, L Ratliff, E Mazumdar, S Burden Uncertainty in artificial intelligence, 935-944, 2020 | 32 | 2020 |
| Stackelberg policy gradient: evaluating the performance of leaders and followers QL Vu, Z Alumbaugh, R Ching, Q Ding, A Mahajan, B Chasnov, S Burden, ... ICLR 2022 Workshop on Gamification and Multiagent Solutions, 2022 | 11 | 2022 |
| Convergence analysis of gradient-based learning with non-uniform learning rates in non-cooperative multi-agent settings B Chasnov, LJ Ratliff, E Mazumdar, SA Burden arXiv preprint arXiv:1906.00731, 2019 | 11 | 2019 |
| Stackelberg actor-critic: A game-theoretic perspective L Zheng, T Fiez, Z Alumbaugh, B Chasnov, LJ Ratliff AAAI Workshop on Reinforcement Learning and Games, 2021 | 7 | 2021 |
| Convergence of learning dynamics in Stackelberg games (2019) T Fiez, B Chasnov, LJ Ratliff arXiv preprint arXiv:1906.01217 12, 1906 | 6 | 1906 |
| Opponent Anticipation via Conjectural Variations B Chasnov, T Fiez, L Ratliff | 4 | 2019 |
| Stability of gradient learning dynamics in continuous games: Scalar action spaces BJ Chasnov, D Calderone, B Açıkmeşe, SA Burden, LJ Ratliff 2020 59th IEEE Conference on Decision and Control (CDC), 3543-3548, 2020 | 3 | 2020 |
| Stability of Gradient Learning Dynamics in Continuous Games: Scalar Action Spaces BJ Chasnov, D Calderone, B Acikmese, SA Burden, LJ Ratliff IEEE Conference on Decision and Control, 2020 | 3 | 2020 |
| Experiments with sensorimotor games in dynamic human/machine interaction B Chasnov, M Yamagami, B Parsa, LJ Ratliff, SA Burden Micro-and Nanotechnology Sensors, Systems, and Applications XI 10982, 344-352, 2019 | 3 | 2019 |
| Consistent Conjectural Variations Equilibria: Characterization & Stability for a Class of Continuous Games DJ Calderone, BJ Chasnov, SA Burden, LJ Ratliff IEEE Control Systems Letters, 2023 | 1 | 2023 |
| Human adaptation to adaptive machines converges to game-theoretic equilibria BJ Chasnov, LJ Ratliff, SA Burden arXiv preprint arXiv:2305.01124, 2023 | 1 | 2023 |
| Visual Modeling System for Optimization-Based Real-Time Trajectory Planning for Autonomous Aerial Drones S Mceowen, D Sullivan, D Calderone, M Szmuk, O Sheridan, B Açıkmeşe, ... 2022 IEEE Aerospace Conference (AERO), 1-9, 2022 | 1 | 2022 |
| Characterizing equilibria in stackelberg games T Fiez, B Chasnov, LJ Ratliff Smooth Games Optimization and Machine Learning Workshop at NeurIPS 2019 …, 2019 | 1 | 2019 |
| Gradient Conjectures for Strategic Multi-Agent Learning B Chasnov, T Fiez, LJ Ratliff | 1 | 2019 |
| Co-adaptation improves performance in a dynamic human-machine interface M Yamagami, M Madduri, BJ Chasnov, AHY Chou, LN Peterson, ... bioRxiv, 2023.07. 14.549053, 2023 | | 2023 |
| Stability of Gradient Learning Dynamics in Continuous Games: Vector Action Spaces BJ Chasnov, D Calderone, B Açıkmeşe, SA Burden, LJ Ratliff arXiv preprint arXiv:2011.05562, 2020 | | 2020 |
| Finite-Time Convergence of Gradient-Based Learning in Continuous Games B Chasnov, LJ Ratliff, D Calderone, E Mazumdar, SA Burden | | 2019 |
Lillian J. RatliffAssociate Professor, University of WashingtonVerified email at uw.edu
