Imitation as a first step to social learning in synthetic characters: a graph-based approach

The processes and representations used to generate the behavior of expressive virtual characters are a valuable and largely untapped resource for helping those characters make sense of the world around them. In this paper, we present Max T. Mouse, an anthropomorphic animated mouse character who uses his own motor and behavior representations to interpret the behaviors he sees his friend Morris Mouse performing. Specifically, by using his own motor and action systems as models for the behavioral capabilities of others (a process known as Simulation Theory in the cognitive literature), Max can begin to identify simple goals and motivations for Morris's behavior, an important step towards developing socially intelligent animated characters. Additionally, Max uses a novel motion graph-based movement recognition process in order to accurately parse and imitate Morris's movements and behaviors in real-time and without prior examples, even when provided with limited synthetic visual input. Key contributions of this paper include demonstrating that using the same mechanisms for movement and behavior perception and production allows for an elegant conservation of representation, and that the innate structure of motion graphs can be used to facilitate both movement parsing and movement recognition.