Integrated dynamical intelligence for interactive embodied agents

Abstract

For embodied agents that interact with people in time-sensitive applications, such as robot assistants or autonomous characters in video games, effectiveness can depend on responsive and adaptive behavior in dynamic environments. To support such behavior, agents' cognitive and physical systems can be modeled in a single, shared language of dynamical systems, an integrated design that supports performance with mechanisms not readily available in other modeling approaches. In this paper, we discuss these general ideas and describe how hybrid dynamical cognitive agents (HDCAs) employ such integrated modeling, resulting in dynamically sensitive user interaction, task sequencing, and adaptive behavior. We also present results of the first user-interactive applications of HDCAs: As demonstrations of this integrated cognitive-physical intelligence, we implemented our HDCAs as autonomous players in an interactive animated Tag game; resulting HDCA behavior included dynamic task re-sequencing, interesting and sensible unscripted behavior, and learning of a multi-faceted user-specified strategy for improving game play.

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