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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhang, W. Kalyana-Kumar, K. Li, A.L. Nguyen, V.D. Simon, W.E. |
| Copyright Year | 1996 |
| Description | Author affiliation: Lamar Univ., Beaumont, TX, USA (Zhang, W.) |
| Abstract | Kgroo, a simulated 3-link folding legged uniped robot is presented and locomotion training of Kgroo with fuzzy-neural control is discussed. It is observed that for the uniped locomotion problem, global training of a fuzzy or neural controller is subject to failure. It is shown that, starting with a single jump example, a multiagent cerebellum model (MAC-J) can enable Kgroo to learn different jumps with a geometrical learning rate based on a learning-tuning-brainstorming theory. Technically, this work introduces effective means for decomposing the high-dimensional locomotion control problem into kernel spaces; theoretically, incremental learning and coordinated cerebellar agent discovery provide a natural explanation to certain explosive learning behaviors in human and animal locomotion control. |
| Starting Page | 239 |
| Ending Page | 245 |
| File Size | 757767 |
| Page Count | 7 |
| File Format | |
| ISBN | 0780336453 |
| DOI | 10.1109/FUZZY.1996.551748 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1996-09-11 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Legged locomotion Animals Equations Springs Fuzzy control Brain modeling Motion control Robots Computer science Mechanical engineering |
| Content Type | Text |
| Resource Type | Article |
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