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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Kurashige, Kentarou Nikaido, Kaoru |
| Copyright Year | 2014 |
| Description | Author affiliation: Dept. of Information and Electronic Engineering Muroran Institute of Technology, Hokkaido, Japan, 050-8585 (Kurashige, Kentarou; Nikaido, Kaoru) |
| Abstract | Various studies related to machine learning have been performed. In this study, we focus on reinforcement learning, one of the methods used in machine learning. In conventional reinforcement leaning, the design of the reward function is difficult, because it is a complex and laborious task and requires expert knowledge. In previous studies, the robot learned from external sources, not autonomously. To solve this problem, we propose a method of robot learning through interactions with humans using sensor input. The reward is also generated through interactions with humans. However, the method does not require additional tasks that must be performed by the human. Therefore, the user does not need expert knowledge, and anyone can teach the robot. Our experiment confirmed that robot learning is possible through the proposed method. |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 601738 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479944644 |
| DOI | 10.1109/RIISS.2014.7009176 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-12-09 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Pain Learning (artificial intelligence) Biological systems Writing Robot sensing systems Trajectory Robot-human interaction reward generation pleasure and pain reinforcement learning |
| Content Type | Text |
| Resource Type | Article |
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