Embodied Gesture Processing: Motor-Based Integration of Perception and Action in Social Artificial Agents
A close coupling of perception and action processes is assumed to play an important role in basic capabilities of social interaction, such as guiding attention and observation of others behavior, coordinating the form and functions of behavior, or grounding the understanding of others behavior in ones own experiences. In the attempt to endow artificial embodied agents with similar abilities, we present a probabilistic model for the integration of perception and generation of hand-arm gestures via a hierarchy of shared motor representations, allowing for combined bottom-up and top-down processing. Results from human-agent interactions are reported demonstrating the models performance in learning, observation, imitation, and generation of gestures.
gestures computational model interactive artificial agents nonverbal communication perception-action links