Provably Efficient Algorithms for Multi-Objective Competitive RL

5 February 2021

Papers citing "Provably Efficient Algorithms for Multi-Objective Competitive RL"

9 / 9 papers shown

Title
Pseudonorm Approachability and Applications to Regret Minimization Christoph Dann Yishay Mansour M. Mohri Jon Schneider Balasubramanian Sivan 34 5 0 03 Feb 2023
A Near-Optimal Primal-Dual Method for Off-Policy Learning in CMDP Fan Chen Junyu Zhang Zaiwen Wen OffRL 39 8 0 13 Jul 2022
Near-Optimal Sample Complexity Bounds for Constrained MDPs Sharan Vaswani Lin F. Yang Csaba Szepesvári 32 32 0 13 Jun 2022
Policy Optimization for Markov Games: Unified Framework and Faster Convergence Runyu Zhang Qinghua Liu Haiquan Wang Caiming Xiong Na Li Yu Bai 27 26 0 06 Jun 2022
Challenging Common Assumptions in Convex Reinforcement Learning Mirco Mutti Ric De Santi Piersilvio De Bartolomeis Marcello Restelli OffRL 32 21 0 03 Feb 2022
Concave Utility Reinforcement Learning with Zero-Constraint Violations Mridul Agarwal Qinbo Bai Vaneet Aggarwal 36 12 0 12 Sep 2021
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces Chi Jin Qinghua Liu Tiancheng Yu 26 50 0 07 Jun 2021
Reward-Free Exploration for Reinforcement Learning Chi Jin A. Krishnamurthy Max Simchowitz Tiancheng Yu OffRL 112 194 0 07 Feb 2020
Blackwell Approachability and Low-Regret Learning are Equivalent Jacob D. Abernethy Peter L. Bartlett Elad Hazan 78 114 0 08 Nov 2010