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What can online reinforcement learning with function approximation benefit from general coverage conditions?

What can online reinforcement learning with function approximation benefit from general coverage conditions?

Fanghui Liu
Luca Viano
V. Cevher
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Papers citing "What can online reinforcement learning with function approximation benefit from general coverage conditions?"

4 / 4 papers shown
Title
A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
Zixiang Chen
C. J. Li
An Yuan
Quanquan Gu
Michael I. Jordan
OffRL
108
26
0
30 Sep 2022
Understanding Deep Neural Function Approximation in Reinforcement Learning via $ε$-Greedy Exploration
Understanding Deep Neural Function Approximation in Reinforcement Learning via εε-Greedy Exploration
Fanghui Liu
Luca Viano
V. Cevher
29
16
0
15 Sep 2022
Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage
Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage
Masatoshi Uehara
Wen Sun
OffRL
93
144
0
13 Jul 2021
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Sergey Levine
Aviral Kumar
George Tucker
Justin Fu
OffRL
GP
334
1,951
0
04 May 2020