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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yamaguchi, A. Takamatsu, J. Ogasawara, T. |
| Copyright Year | 2009 |
| Description | Author affiliation: Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5, Takayama, Ikoma, 630-0192, JAPAN (Yamaguchi, A.; Takamatsu, J.; Ogasawara, T.) |
| Abstract | This paper presents a new continuous action space for reinforcement learning (RL) with the wire-fitting [1]. The wire-fitting has a desirable feature to be used with action value function based RL algorithms. However, the wire-fitting becomes unstable caused by changing the parameters of actions. Furthermore, the acquired behavior highly depend on the initial values of the parameters. The proposed action space is expanded from the DCOB, proposed by Yamaguchi et al. [2], where the discrete action set is generated from given basis functions. Based on the DCOB, we apply some constraints to the parameters in order to obtain stability. Furthermore, we also describe a proper way to initialize the parameters. The simulation results demonstrate that the proposed method outperforms the wire-fitting. On the other hand, the resulting performance of the proposed method is the same as, or inferior to the DCOB. This paper also discuss about this result. |
| Starting Page | 401 |
| Ending Page | 407 |
| File Size | 507392 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781424450817 |
| ISSN | 19449445 |
| DOI | 10.1109/ROMAN.2009.5326234 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-09-27 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Learning Space technology Orbital robotics Stability Humanoid robots Human robot interaction Information science Legged locomotion Robot control jumping Reinforcement learning continuous action space motion learning crawling |
| Content Type | Text |
| Resource Type | Article |
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