PhD thesis anouncement

[Michael Kositsky]

Dear Connectionists,

My PhD thesis on motor learning and 
skill acquisition is now available at

http://www-anw.cs.umass.edu/~kositsky/phdThesis/phdThesis.html

Title:

Motor Learning and Skill Acquisition
by Sequences of Elementary Actions

Abstract:

The work presents a computational model for motor 
learning and memory. The basic approach of the model 
is to treat complex activities as sequences of elementary 
actions. The model implements two major functions.
First, the combination of elementary actions into sequences 
to produce desired complex activities, which is achieved by 
a search procedure involving multiscale task analysis and 
stochastic descent processing. Second, the utilization of 
past motor experience by effective memorization and retrieval, 
and generalizing sequences. New tasks are accomplished by 
combining past sequences intended for similar tasks. 
The generalization is based upon the clustering property 
of motor experience data. Specifically, the clustering property 
results in concentrating the data points within compact regions, 
allowing fast and accurate generalization of the elementary 
actions and consequently, enabling a robust performance of 
familiar tasks. A motor memory architecture is proposed that 
uses the clusters as the basic memory units. 

The computational work is accompanied by a set of psychophysical 
studies aimed at examining the possible use of a cluster 
representation by the human motor system. The experiment examines 
the entire motor learning process, starting from untrained 
movements up to the formation of highly skilled actions.


Michael Kositsky

Senior Postdoctoral Researcher
Department of Computer Science
University of Massachusetts, Amherst

email: kositsky at cs.umass.edu
web:   http://www-anw.cs.umass.edu/~kositsky