A Deep Hierarchical Reinforcement Learning Algorithm in Partially Observable Markov Decision Processes

A Deep Hierarchical Reinforcement Learning Algorithm in Partially Observable Markov Decision Processes

In recent years, reinforcement learning (RL) has achieved remarkable success due to the growing adoption of deep learning techniques and the rapid growth of computing power. Nevertheless, it is well-known that flat reinforcement learning algorithms are often have trouble learning and are even data-e...

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Bibliographic Details
Main Authors: Tuyen P. Le, Ngo Anh Vien, TaeChoong Chung
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Hierarchical deep reinforcement learning
partially observable MDP (POMDP)
semi-MDP
partially observable semi-MDP (POSMDP)
Online Access:https://ieeexplore.ieee.org/document/8421749/

Internet

https://ieeexplore.ieee.org/document/8421749/

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