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Filtering by: Creator Fu, Zuyue Subject Computer science Subject Industrial engineering

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Description:: In this dissertation, we aim to develop algorithms that achieve optimality with provable complexity guarantees under various settings in reinforcement learning (RL). Specifically, in Markov decision processes (MDPs), we study single-agent and multi-agent online RL, respectively, and offline RL under the presence of unobserved confounders. Single-agent online RL. We design...
Subject:: Industrial engineering and Computer science
Creator:: Fu, Zuyue
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 09/22/2022
Date Created:: 2022-01-01
Resource Type:: Dissertation
Alternate Identifier:: etdadmin_upload_927346 and http://dissertations.umi.com/northwestern:16223

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