Offline RL with discrete proxy representations for generalizability in POMDPs

Offline Reinforcement Learning (RL) has demonstrated promising results in various applications by learning policies from previously collected datasets, reducing the need for online exploration and interactions. However, real-world scenarios usually involve partial observability, which brings crucial...

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Bibliographic Details
Main Authors: GU, Pengjie, CAI, Xinyu, XING, Dong, WANG, Xinrun, ZHAO, Mengchen, AN, Bo
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2023
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Online Access:https://ink.library.smu.edu.sg/sis_research/9048
https://ink.library.smu.edu.sg/context/sis_research/article/10051/viewcontent/Offline_rl_with_discrete_proxy_av.pdf
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Institution: Singapore Management University
Language: English
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