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Multiplayer Performative Prediction: Learning in Decision-Dependent Games

Jan 10, 2022
Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff

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Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms

Sep 25, 2021
Liyuan Zheng, Tanner Fiez, Zane Alumbaugh, Benjamin Chasnov, Lillian J. Ratliff

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Which Echo Chamber? Regions of Attraction in Learning with Decision-Dependent Distributions

Jun 30, 2021
Roy Dong, Lillian J. Ratliff

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Zeroth-Order Methods for Convex-Concave Minmax Problems: Applications to Decision-Dependent Risk Minimization

Jun 16, 2021
Chinmay Maheshwari, Chih-Yuan Chiu, Eric Mazumdar, S. Shankar Sastry, Lillian J. Ratliff

* 32 pages, 5 figures 

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Minimax Optimization with Smooth Algorithmic Adversaries

Jun 02, 2021
Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff

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Function Design for Improved Competitive Ratio in Online Resource Allocation with Procurement Costs

Dec 23, 2020
Mitas Ray, Omid Sadeghi, Lillian J. Ratliff, Maryam Fazel

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Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks

Mar 20, 2020
Liyuan Zheng, Yuanyuan Shi, Lillian J. Ratliff, Baosen Zhang

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Constrained Upper Confidence Reinforcement Learning

Jan 26, 2020
Liyuan Zheng, Lillian J. Ratliff

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Policy-Gradient Algorithms Have No Guarantees of Convergence in Continuous Action and State Multi-Agent Settings

Jul 08, 2019
Eric Mazumdar, Lillian J. Ratliff, Michael I. Jordan, S. Shankar Sastry

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Convergence of Learning Dynamics in Stackelberg Games

Jun 04, 2019
Tanner Fiez, Benjamin Chasnov, Lillian J. Ratliff

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Convergence Analysis of Gradient-Based Learning with Non-Uniform Learning Rates in Non-Cooperative Multi-Agent Settings

May 30, 2019
Benjamin Chasnov, Lillian J. Ratliff, Eric Mazumdar, Samuel A. Burden

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Competitive Statistical Estimation with Strategic Data Sources

Apr 29, 2019
Tyler Westenbroek, Roy Dong, Lillian J. Ratliff, S. Shankar Sastry

* accepted in the IEEE Transactions on Automatic Control 

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On the Convergence of Gradient-Based Learning in Continuous Games

Sep 27, 2018
Eric Mazumdar, Lillian J. Ratliff

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Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences

Jul 06, 2018
Tanner Fiez, Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff

* Published as a conference paper in Conference on Uncertainty in Artificial Intelligence (UAI) 2018 

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Incentives in the Dark: Multi-armed Bandits for Evolving Users with Unknown Type

Mar 11, 2018
Lillian J. Ratliff, Shreyas Sekar, Liyuan Zheng, Tanner Fiez

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Inverse Risk-Sensitive Reinforcement Learning

Nov 21, 2017
Lillian J. Ratliff, Eric Mazumdar

* v3 (comments regarding updates): We significantly extended the theory (Theorem 2, 3, 5 and Proposition 3). We also correct some minor typos throughout the document; v2 (comments regarding updates): We corrected some notational typos and made clarifications in the proof. We also added clarifying remarks regarding reference points and acceptance levels which were previously conflated 

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