Combining PSR theory with distributional reinforcement learning

Combining PSR theory with distributional reinforcement learning

This work focuses on using Distributional Reinforcement Learning (DRL) in a partially observable environment that is modelled via Predictive State Representation Theory (PSR). We aim to integrate the beneﬁts of DRL and PSR to obtain a model-based reinforcement learning method that is capable of prov...

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書目詳細資料
主要作者:	Zhou, Jingzhe
其他作者:	Zinovi Rabinovich
格式:	Thesis-Master by Research
語言:	English
出版:	Nanyang Technological University 2020
主題:	Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
在線閱讀:	https://hdl.handle.net/10356/139946
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Nanyang Technological University
語言:	English

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