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A Reward Optimization Method Based on Action Subrewards in Hierarchical Reinforcement Learning
Joint Authors
Liu, Quan
Fu, Yuchen
Ling, Xionghong
Cui, Zhiming
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-28
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Reinforcement learning (RL) is one kind of interactive learning methods.
Its main characteristics are “trial and error” and “related reward.” A hierarchical reinforcement learning method based on action subrewards is proposed to solve the problem of “curse of dimensionality,” which means that the states space will grow exponentially in the number of features and low convergence speed.
The method can reduce state spaces greatly and choose actions with favorable purpose and efficiency so as to optimize reward function and enhance convergence speed.
Apply it to the online learning in Tetris game, and the experiment result shows that the convergence speed of this algorithm can be enhanced evidently based on the new method which combines hierarchical reinforcement learning algorithm and action subrewards.
The “curse of dimensionality” problem is also solved to a certain extent with hierarchical method.
All the performance with different parameters is compared and analyzed as well.
American Psychological Association (APA)
Fu, Yuchen& Liu, Quan& Ling, Xionghong& Cui, Zhiming. 2014. A Reward Optimization Method Based on Action Subrewards in Hierarchical Reinforcement Learning. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-1048351
Modern Language Association (MLA)
Fu, Yuchen…[et al.]. A Reward Optimization Method Based on Action Subrewards in Hierarchical Reinforcement Learning. The Scientific World Journal No. 2014 (2014), pp.1-6.
https://search.emarefa.net/detail/BIM-1048351
American Medical Association (AMA)
Fu, Yuchen& Liu, Quan& Ling, Xionghong& Cui, Zhiming. A Reward Optimization Method Based on Action Subrewards in Hierarchical Reinforcement Learning. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-1048351
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048351