JPL Technical Report Server

Control of a simulated arm using a novel combination of Cerebellar learning mechanisms

Show simple item record

dc.contributor.author Assad, C. en_US
dc.contributor.author Hartmann, M. en_US
dc.contributor.author Paulin, M. G. en_US
dc.date.accessioned 2004-09-22T21:33:05Z
dc.date.available 2004-09-22T21:33:05Z
dc.date.issued 2001-06-30 en_US
dc.identifier.citation Tenth Annual Computational Neuroscience Meeting en_US
dc.identifier.citation San Francisco, CA, USA en_US
dc.identifier.clearanceno 02-0243 en_US
dc.identifier.uri http://hdl.handle.net/2014/11678
dc.description.abstract We present a model of cerebellar cortex that combines two types of learning: feedforward predicitve association based on local Hebbian-type learning between granule cell ascending branch and parallel fiber inputs, and reinforcement learning with feedback error correction based on climbing fiber activity. en_US
dc.format.extent 2960995 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.subject.other cerebellum cerebellar learning dynamic state estimation sensorimotor control en_US
dc.title Control of a simulated arm using a novel combination of Cerebellar learning mechanisms en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search


Browse

My Account