S., & Gräser O. (2006)
Imitation Learning and Response Facilitation in Embodied Agents
In J. Gratch et al.
(Eds.), Intelligent Virtual Agents 2006, LNAI 4133
Imitation is supposedly a fundamental mechanism for humans to learn
new actions and to gain knowledge about another’s intentions.
The basis of this behavior seems to be a direct influencing of the motor
system by the perceptual system, affording fast, selective enhancement
of a motor response already in the repertoire (response facilitation)
as well as learning and delayed reproduction of new actions (true
imitation). In this paper, we present an approach to attain these
capabilities in virtual embodied agents. Building upon a computational
motor control model, our approach connects visual representations of
observed hand and arm movements to graph-based representations of motor
commands. Forward and inverse models are employed to allow for both
fast mimicking responses as well as imitation learning.