Title page for etd-0727115-130716


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URN etd-0727115-130716
Author Yi-Chia Tseng
Author's Email Address No Public.
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Department Electrical Engineering
Year 2015
Semester 1
Degree Master
Type of Document
Language English
Title An Unified Approach to Inverse Reinforcement Learning by Oppositive Demonstrations
Date of Defense 2015-08-25
Page Count 45
Keyword
  • Apprenticeship Learning
  • Feature weight
  • Inverse Reinforcement learning
  • Reward function
  • Reinforcement learning
  • Abstract Reinforcement learning (RL) techniques use a reward function to correct a learning agent to solve sequential decision making problems through interactions with a dynamic environment, but it is hard to design the reward function in complex problems. Its design difficulties promote the inverse reinforcement learning (IRL) by deriving from an expert’s demonstrations. It is assumed that the demonstrations are meaningful and reproducible. In this thesis, demonstrations of failure are not entirely useless. An unified method of combining oppositive demonstrations is proposed to teach the robot by showing inappropriate demonstrations or trying to exhibit unrelated behaviors, so as to the agent can deliberately avoid such bad situations and speed up the learning. According to the result of simulations, it is obvious that the performance of algorithm combined with demonstrations of failure is better than that has only good demonstrations. It is not only convenient to operate but also save a lot of learning time.
    Advisory Committee
  • Tzuu-Hseng S. Li - chair
  • Ming-Yi Ju - co-chair
  • Yu-Jen Chen - co-chair
  • Kao-Shing Huang - advisor
  • Files
  • etd-0727115-130716.pdf
  • indicate access worldwide
    Date of Submission 2015-08-27

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