Action selection for composable modular deep reinforcement learning

In modular reinforcement learning (MRL), a complex decision making problem is decomposed into multiple simpler subproblems each solved by a separate module. Often, these subproblems have conflicting goals, and incomparable reward scales. A composable decision making architecture requires that even t...

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Bibliographic Details
Main Authors: GUPTA, Vaibhav, ANAND, Daksh, PARACHURI, Praveen, KUMAR, Akshat
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2021
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Online Access:https://ink.library.smu.edu.sg/sis_research/6179
https://ink.library.smu.edu.sg/context/sis_research/article/7182/viewcontent/AAMAS_2021.pdf
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Institution: Singapore Management University
Language: English
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