Learning the continuous-time optimal decision law from discrete-time rewards

The concept of reward is fundamental in reinforcement learning with a wide range of applications in natural and social sciences. Seeking an interpretable reward for decision-making that largely shapes the system's behavior has always been a challenge in reinforcement learning. In this work, we...

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Bibliographic Details
Main Authors: Chen Ci, Xie Lihua, Xie Kan, Lewis Frank Leroy, Liu Yilu, Xie Shengli
Format: Article
Language:English
Published: Science Press 2024-03-01
Series:National Science Open
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Online Access:https://www.sciengine.com/doi/10.1360/nso/20230054
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