Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret

22 June 2020

Papers citing "Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret"

27 / 27 papers shown

Title
Risk-sensitive Reinforcement Learning Based on Convex Scoring Functions Shanyu Han Yang Liu Xiang Yu 75 0 0 07 May 2025
Policy Gradient Methods for Risk-Sensitive Distributional Reinforcement Learning with Provable Convergence Minheng Xiao Xian Yu Lei Ying 82 2 0 23 May 2024
Towards Efficient Risk-Sensitive Policy Gradient: An Iteration Complexity Analysis Rui Liu Erfaun Noorani Pratap Tokekar John S. Baras 72 1 0 13 Mar 2024
Exploration-Exploitation in Constrained MDPs Yonathan Efroni Shie Mannor Matteo Pirotta 110 179 0 04 Mar 2020
Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss Shuang Qiu Xiaohan Wei Zhuoran Yang Jieping Ye Zhaoran Wang 125 49 0 02 Mar 2020
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization Dongsheng Ding Xiaohan Wei Zhuoran Yang Zhaoran Wang M. Jovanović 68 165 0 01 Mar 2020
Provable Self-Play Algorithms for Competitive Reinforcement Learning Yu Bai Chi Jin SSL 137 149 0 10 Feb 2020
Constrained Upper Confidence Reinforcement Learning Liyuan Zheng Lillian J. Ratliff 77 68 0 26 Jan 2020
$Policy Optimization for $\mathcal{H}_2$ Linear Control with $\mathcal{H}_\infty$ Robustness Guarantee: Implicit Regularization and Global Convergence$ Policy Optimization for $\mathcal{H}_2$ Linear Control with $\mathcal{H}_\infty$ Robustness Guarantee: Implicit Regularization and Global Convergence Kai Zhang Bin Hu Tamer Basar 53 121 0 21 Oct 2019
Provably Efficient Reinforcement Learning with Linear Function Approximation Chi Jin Zhuoran Yang Zhaoran Wang Michael I. Jordan 86 557 0 11 Jul 2019
Epistemic Risk-Sensitive Reinforcement Learning Hannes Eriksson Christos Dimitrakakis 111 29 0 14 Jun 2019
Estimating Risk and Uncertainty in Deep Reinforcement Learning W. Clements B. V. Delft Benoît-Marie Robaglia Reda Bahi Slaoui Sébastien Toth 58 97 0 23 May 2019
Lyapunov-based Safe Policy Optimization for Continuous Control Yinlam Chow Ofir Nachum Aleksandra Faust Edgar A. Duénez-Guzmán Mohammad Ghavamzadeh 70 246 0 28 Jan 2019
Model and Reinforcement Learning for Markov Games with Risk Preferences Wenjie Huang P. V. Hai W. Haskell 33 4 0 15 Jan 2019
A Block Coordinate Ascent Algorithm for Mean-Variance Optimization Bo Liu Tengyang Xie Yangyang Xu Mohammad Ghavamzadeh Yinlam Chow Daoming Lyu Daesub Yoon 53 30 0 07 Sep 2018
Is Q-learning Provably Efficient? Chi Jin Zeyuan Allen-Zhu Sébastien Bubeck Michael I. Jordan OffRL 65 806 0 10 Jul 2018
Constrained Policy Optimization Joshua Achiam David Held Aviv Tamar Pieter Abbeel 110 1,322 0 30 May 2017
Minimax Regret Bounds for Reinforcement Learning M. G. Azar Ian Osband Rémi Munos 83 774 0 16 Mar 2017
Risk-Averse Multi-Armed Bandit Problems under Mean-Variance Measure Sattar Vakili Qing Zhao 37 88 0 18 Apr 2016
Risk-Constrained Reinforcement Learning with Percentile Risk Criteria Yinlam Chow Mohammad Ghavamzadeh Lucas Janson Marco Pavone 70 512 0 05 Dec 2015
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach Yinlam Chow Aviv Tamar Shie Mannor Marco Pavone 121 317 0 06 Jun 2015
Policy Gradient for Coherent Risk Measures Aviv Tamar Yinlam Chow Mohammad Ghavamzadeh Shie Mannor 60 117 0 13 Feb 2015
Algorithms for CVaR Optimization in MDPs Yinlam Chow Mohammad Ghavamzadeh 73 198 0 12 Jun 2014
Generalized Risk-Aversion in Stochastic Multi-Armed Bandits Alexander Zimin Rasmus Ibsen-Jensen K. Chatterjee 46 38 0 05 May 2014
Generalization and Exploration via Randomized Value Functions Ian Osband Benjamin Van Roy Zheng Wen 77 314 0 04 Feb 2014
Risk-sensitive Reinforcement Learning Yun Shen Michael J. Tobia T. Sommer Klaus Obermayer 88 320 0 08 Nov 2013
Risk-sensitive Markov control processes Yun Shen W. Stannat Klaus Obermayer 76 90 0 28 Oct 2011