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DOPE: Doubly Optimistic and Pessimistic Exploration for Safe Reinforcement Learning
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DOPE: Doubly Optimistic and Pessimistic Exploration for Safe Reinforcement Learning

Archana Bura
Aria HasanzadeZonuzy
D. Kalathil
S. Shakkottai
J. Chamberland
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Papers citing "DOPE: Doubly Optimistic and Pessimistic Exploration for Safe Reinforcement Learning"

5 / 5 papers shown
Title
Ensuring Safety in an Uncertain Environment: Constrained MDPs via Stochastic Thresholds
Ensuring Safety in an Uncertain Environment: Constrained MDPs via Stochastic Thresholds
Qian Zuo
Fengxiang He
102
0
0
07 Apr 2025
Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form
Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form
Toshinori Kitamura
Tadashi Kozuno
Wataru Kumagai
Kenta Hoshino
Y. Hosoe
Kazumi Kasaura
Masashi Hamaya
Paavo Parmas
Yutaka Matsuo
163
2
0
29 Aug 2024
A safe exploration approach to constrained Markov decision processes
A safe exploration approach to constrained Markov decision processes
Tingting Ni
Maryam Kamgarpour
113
3
0
01 Dec 2023
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs
Dongsheng Ding
Chen-Yu Wei
Jianchao Tan
Alejandro Ribeiro
125
22
0
20 Jun 2023
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain
Jianye Hao
Tianpei Yang
Hongyao Tang
Chenjia Bai
Jinyi Liu
Zhaopeng Meng
Peng Liu
Zhen Wang
OffRL
86
103
0
14 Sep 2021