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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Bibliographic Details
Main Author: Zhou, Jingzhe
Other Authors: Zinovi Rabinovich
Format: Thesis-Master by Research
Language:English
Published: Nanyang Technological University 2020
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Online Access:https://hdl.handle.net/10356/139946

Internet

https://hdl.handle.net/10356/139946

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