Control and Learning by the State Space Model: Experimental Findings

dc.creator	Raibert, Marc
dc.date	2004-10-04T14:48:13Z
dc.date	2004-10-04T14:48:13Z
dc.date	1977-04-01
dc.date.accessioned	2013-10-09T02:44:35Z
dc.date.available	2013-10-09T02:44:35Z
dc.date.issued	2013-10-09
dc.identifier	AIM-412
dc.identifier	http://hdl.handle.net/1721.1/6273
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description	This is the second of a two part presentation of a model for motor control and learning. The model was implemented using a small computer and the MIT -Scheinman manipulator. Experiments were conducted which demonstrate the controller's ability to learn new movements, adapt to mechanical changes caused by inertial and elastic loading, and generalize its behavior among similar movements. A second generation model, based on improvements suggested by these experiments is suggested.
dc.format	12327356 bytes
dc.format	9840929 bytes
dc.format	application/postscript
dc.format	application/pdf
dc.language	en_US
dc.relation	AIM-412
dc.title	Control and Learning by the State Space Model: Experimental Findings

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