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NSYSU

1. Lee, Chih-wen. Adaptive Exploration Strategies for Reinforcement Learning.

Degree: Master, Electrical Engineering, 2016, NSYSU

Reinforcement learning through an agent to learn policy use trial and error method to achieve the goal, but when we want to apply it in a real environment, how to dividing state space becomes difficult to decide, another problem in reinforcement learning, agent takes an action in the learning process according to the policy, we will encounter how to balance exploitation and exploration, to explore a new areas in order to gain experience, or to get the maximum reward on existing knowledge. To solve problems, we proposed the decision tree-based adaptive state space segmentation algorithm and then use decreasing Tabu search and adaptive exploration strategies to solve the problem of exploitation and exploration on this method. Decreasing Tabu search will put the action into the Tabu list, after agent take an action. If the Tabu list is full, release the action, but the size of Tabu list will decreasing according to the number of successful reaching goals. Adaptive exploration strategy is based on information entropy, not tuning exploration rate by manually. Finally, a maze environment simulation is used to validate the proposed method, further to decrease the learning time. Advisors/Committee Members: Yu-Jen Chen (chair), Ming-Yi Ju (chair), Kao-Shing Huang (committee member).

Subjects/Keywords: Reinforce learning; Tabu search; State aggregation; trade-off between Exploration and Exploitation; decision tree; ε-greedy

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lee, C. (2016). Adaptive Exploration Strategies for Reinforcement Learning. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0025116-130314

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lee, Chih-wen. “Adaptive Exploration Strategies for Reinforcement Learning.” 2016. Thesis, NSYSU. Accessed October 18, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0025116-130314.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lee, Chih-wen. “Adaptive Exploration Strategies for Reinforcement Learning.” 2016. Web. 18 Oct 2019.

Vancouver:

Lee C. Adaptive Exploration Strategies for Reinforcement Learning. [Internet] [Thesis]. NSYSU; 2016. [cited 2019 Oct 18]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0025116-130314.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lee C. Adaptive Exploration Strategies for Reinforcement Learning. [Thesis]. NSYSU; 2016. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0025116-130314

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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