title: A biologically inspired computational model of the Block Copying Task
creator: Lan, Tian
creator: Arnold, Michael
creator: Sejnowski, Terrence
creator: Jabri, Marwan
subject: Machine Learning
subject: Neural Nets
description: We present in this paper a biologically inspired model of the Basal Ganglia which deals with Block Copying as a sequence learning task. By breaking a relatively complex task into simpler operations with well-defined skills, an approach which is termed as a skill-based machine design is used in the device of computational models to complete such tasks. Basal Ganglia are critically involved in sensorimotor control. From the learning aspects, Actor-Critic architectures have been proposed to model the Basal Ganglia and Temporal difference has been proposed as a learning algorithm. The model is implemented and simulation results are presented to show the capability of our model to successfully complete the task.
publisher: Lund University Cognitive Studies
contributor: Prince, Christopher G.
contributor: Berthouze, Luc
contributor: Kozima, Hideki
contributor: Bullock, Daniel
contributor: Stojanov, Georgi
contributor: Balkenius, Christian
date: 2003
type: Conference Poster
type: PeerReviewed
format: application/pdf
identifier: http://cogprints.org/3350/1/Lan.pdf
identifier:   Lan, Tian and Arnold, Michael and Sejnowski, Terrence and Jabri, Marwan  (2003) A biologically inspired computational model of the Block Copying Task.  [Conference Poster]     
relation: http://cogprints.org/3350/