Regret Bounds for Risk-sensitive Reinforcement Learning with Lipschitz Dynamic Risk Measures

4 June 2023

Papers citing "Regret Bounds for Risk-sensitive Reinforcement Learning with Lipschitz Dynamic Risk Measures"

7 / 7 papers shown

Title
Policy Gradient Methods for Risk-Sensitive Distributional Reinforcement Learning with Provable Convergence Minheng Xiao Xian Yu Lei Ying 42 2 0 23 May 2024
Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation Yu Chen Xiangcheng Zhang Siwei Wang Longbo Huang 42 3 0 28 Feb 2024
Provably Efficient Partially Observable Risk-Sensitive Reinforcement Learning with Hindsight Observation Tonghe Zhang Yu Chen Longbo Huang 44 0 0 28 Feb 2024
A Distribution Optimization Framework for Confidence Bounds of Risk Measures Hao Liang Zhimin Luo 22 3 0 12 Jun 2023
Conditionally Elicitable Dynamic Risk Measures for Deep Reinforcement Learning Anthony Coache S. Jaimungal Á. Cartea 28 13 0 29 Jun 2022
Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning Yingjie Fei Zhuoran Yang Yudong Chen Zhaoran Wang 51 46 0 06 Nov 2021
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach Yinlam Chow Aviv Tamar Shie Mannor Marco Pavone 73 314 0 06 Jun 2015