Provably Efficient Offline Reinforcement Learning With Trajectory-Wise Reward-Reference-Cited by-同舟云学术

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Provably Efficient Offline Reinforcement Learning With Trajectory-Wise Reward

Published:2024-09 Issue:9 Volume:70 Page:6481-6518
ISSN:0018-9448
Container-title:IEEE Transactions on Information Theory
language:
Short-container-title:IEEE Trans. Inform. Theory

Author:

Xu Tengyu¹,Wang Yue²,Zou Shaofeng³^ORCID,Liang Yingbin¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH, USA

2. Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA

3. Department of Electrical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, USA

Funder

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/18/10642977/10596317-aam.pdf

Reference81 articles.

1. Human-level control through deep reinforcement learning

2. End-to-end training of deep visuomotor policies;Levine;J. Mach. Learn. Res.,2016

3. Mastering the game of Go without human knowledge

4. Improved protein structure prediction using potentials from deep learning

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