| 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 | 140 | 2020 |
| Convergence of learning dynamics in stackelberg games T Fiez, B Chasnov, LJ Ratliff arXiv preprint arXiv:1906.01217, 2019 | 99 | 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 | 52 | 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 | 40 | 2020 |
| 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 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 | 9 | 2022 |
| 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 |
| Opponent Anticipation via Conjectural Variations B Chasnov, T Fiez, L Ratliff | 6 | 2019 |
| Convergence of learning dynamics in Stackelberg games (2019) T Fiez, B Chasnov, LJ Ratliff arXiv preprint arXiv:1906.01217 12, 1906 | 6 | 1906 |
| Human adaptation to adaptive machines converges to game-theoretic equilibria BJ Chasnov, LJ Ratliff, SA Burden arXiv preprint arXiv:2305.01124, 2023 | 5 | 2023 |
| 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 | 4 | 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 | 4 | 2019 |
| Consistent conjectural variations equilibria: Characterization and stability for a class of continuous games DJ Calderone, BJ Chasnov, SA Burden, LJ Ratliff IEEE Control Systems Letters 7, 2743-2748, 2023 | 3 | 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 | 3 | 2022 |
| Effect of Adaptation Rate and Cost Display in a Human-AI Interaction Game JT Isa, B Wu, Q Wang, Y Zhang, SA Burden, LJ Ratliff, BJ Chasnov arXiv preprint arXiv:2408.14640, 2024 | 1 | 2024 |
| 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 | 1 | 2020 |
| 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 |
| Finite-Time Convergence of Gradient-Based Learning in Continuous Games B Chasnov, LJ Ratliff, D Calderone, E Mazumdar, SA Burden Mimeo, 2019 | 1 | 2019 |
| Dynamics of Multi-Agent Learning Under Bounded Rationality: Theory and Empirical Evidence BJ Chasnov University of Washington, 2024 | | 2024 |
Lillian J. RatliffAssociate Professor, University of WashingtonVerified email at uw.edu
