Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning

25 November 2020

Papers citing "Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning"

6 / 6 papers shown

Title
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
Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning Ruida Zhou Tao-Wen Liu D. Kalathil P. R. Kumar Chao Tian 45 13 0 10 Jun 2022
Gap-Dependent Unsupervised Exploration for Reinforcement Learning Jingfeng Wu Vladimir Braverman Lin F. Yang 33 12 0 11 Aug 2021
A Simple Reward-free Approach to Constrained Reinforcement Learning Sobhan Miryoosefi Chi Jin 16 29 0 12 Jul 2021
Provably Efficient Algorithms for Multi-Objective Competitive RL Tiancheng Yu Yi Tian J.N. Zhang S. Sra 32 20 0 05 Feb 2021
Reward-Free Exploration for Reinforcement Learning Chi Jin A. Krishnamurthy Max Simchowitz Tiancheng Yu OffRL 112 194 0 07 Feb 2020