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http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6972Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.creator | Aboaf, Eric W. | - |
| dc.date | 2004-10-20T20:11:45Z | - |
| dc.date | 2004-10-20T20:11:45Z | - |
| dc.date | 1988-08-01 | - |
| dc.date.accessioned | 2013-10-09T02:48:00Z | - |
| dc.date.available | 2013-10-09T02:48:00Z | - |
| dc.date.issued | 2013-10-09 | - |
| dc.identifier | AITR-1079 | - |
| dc.identifier | http://hdl.handle.net/1721.1/6972 | - |
| dc.identifier.uri | http://koha.mediu.edu.my:8181/xmlui/handle/1721 | - |
| dc.description | We are investigating how to program robots so that they learn from experience. Our goal is to develop principled methods of learning that can improve a robot's performance of a wide range of dynamic tasks. We have developed task-level learning that successfully improves a robot's performance of two complex tasks, ball-throwing and juggling. With task- level learning, a robot practices a task, monitors its own performance, and uses that experience to adjust its task-level commands. This learning method serves to complement other approaches, such as model calibration, for improving robot performance. | - |
| dc.format | 9997518 bytes | - |
| dc.format | 3880924 bytes | - |
| dc.format | application/postscript | - |
| dc.format | application/pdf | - |
| dc.language | en_US | - |
| dc.relation | AITR-1079 | - |
| dc.title | Task-Level Robot Learning | - |
| Appears in Collections: | MIT Items | |
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