Acquisition and Improvement of Human Motor Skills:
	      Learning through Observation and Practice

			      Wayne Iba
		    Doctoral Dissertation Abstract
				 1991

Skilled movement is an integral part of the human existence.  This is
exemplified in a range of behaviors from concert violin performance,
to picking up and drinking a glass of milk.  A better understanding of
motor skills and their development is a prerequisite to the
construction of truly flexible intelligent agents.  Existing
computational models have mostly focused on low-level issues of
controlling manipulators rather than on capturing skilled movements as
conceptual units.  The psychological literature provides very
high-level abstract theories or low-level analysis of specific
movement phenomena.  Furthermore, the acquisition of skills is largely
ignored in both bodies of work.  In response to these issues, we
present MEANDER, a computational model of human motor behavior, that
uniformly addresses both the acquisition of skills through observation
and the improvement of skills through practice.

Meander consists of a sensory-effector interface, a memory of
movements, and a set of performance and learning mechanisms that let
it recognize and generate motor skills.  The system initially acquires
such skills by observing movements performed by another agent and
constructing a concept hierarchy.  Observed movements are parsed and
stored internally as motor schemas.  Two subsystems of MEANDER
interact to allow observed movements to be recognized and stored
skills to be executed.  The OXBOW module is responsible for
constructing and modifying the skill hierarchy according to the
observed experiences.  Given a stored motor skill in memory, the
MAGGIE component will take the motor schema and cause some effector to
behave appropriately.  Errors in execution can be corrected through a
closed-loop feedback control mechanism.  All learning involves
changing the hierarchical memory of skill concepts to more closely
correspond to either observed experience or to desired behaviors.

One can evaluate the effectiveness of a model in a number of ways.  We
evaluate MEANDER empirically with respect to how well it acquires and
improves both artificial movement types and handwritten script letters
from the alphabet.  We also evaluate MEANDER as a psychological model
by comparing its behavior to robust phenomena in humans and by
considering the richness of the predictions it makes.