A Simple Reward-free Approach to Constrained Reinforcement Learning

12 July 2021

Papers citing "A Simple Reward-free Approach to Constrained Reinforcement Learning"

9 / 9 papers shown

Title
Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More Fanchen Bu Hyeonsoo Jo Soo Yong Lee Sungsoo Ahn Kijung Shin 22 3 0 14 May 2024
Bayesian Constraint Inference from User Demonstrations Based on Margin-Respecting Preference Models Dimitris Papadimitriou Daniel S. Brown 48 1 0 04 Mar 2024
Reinforcement Learning by Guided Safe Exploration Qisong Yang T. D. Simão N. Jansen Simon Tindemans M. Spaan OffRL OnRL 34 5 0 26 Jul 2023
Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs Yuan Cheng Ruiquan Huang J. Yang Yitao Liang OffRL 41 8 0 20 Mar 2023
Pseudonorm Approachability and Applications to Regret Minimization Christoph Dann Yishay Mansour M. Mohri Jon Schneider Balasubramanian Sivan 34 5 0 03 Feb 2023
Near-Optimal Sample Complexity Bounds for Constrained MDPs Sharan Vaswani Lin F. Yang Csaba Szepesvári 32 32 0 13 Jun 2022
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 122 166 0 06 Jan 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