  The biomechanics of the human body allow humans a range of possible ways of
executing movements to attain specific goals. Nevertheless, humans exhibit
significant patterns in how they execute movements. We propose that the
observed patterns of human movement arise because subjects select those ways to
execute movements that are, in a rigorous sense, optimal. In this project, we
show how this proposition can guide the development of computational models of
movement selection and thereby account for human movement patterns. We proceed
by first developing a movement utility formalism that operationalizes the
concept of a best or optimal way of executing a movement using a utility
function so that the problem of movement selection becomes the problem of
finding the movement that maximizes the utility function. Since the movement
utility formalism includes a contribution of the metabolic energy of the
movement (maximum utility movements try to minimize metabolic energy), we also
develop a metabolic energy formalism that we can use to construct estimators of
the metabolic energies of particular movements. We then show how we can
construct an estimator for the metabolic energies of normal walking gaits and
we use that estimator to construct a movement utility model of the selection of
normal walking gaits and show that the relationship between avg. walking speed
and avg. step length predicted by this model agrees with observation. We
conclude by proposing a physical mechanism that a subject might use to estimate
the metabolic energy of a movement in practice.
