Multispace Behavioral Model for Face-Based Affective Social Agents

This paper describes a behavioral model for affective social agents based on three independent but interacting parameter spaces:
knowledge, personality, andmood. These spaces control a lower-level geometry space that provides parameters at the facial feature
level. Personality and mood use findings in behavioral psychology to relate the perception of personality types and emotional
states to the facial actions and expressions through two-dimensional models for personality and emotion. Knowledge encapsulates
the tasks to be performed and the decision-making process using a specially designed XML-based language. While the geometry
space provides an MPEG-4 compatible set of parameters for low-level control, the behavioral extensions available through the
triple spaces provide flexible means of designing complicated personality types, facial expression, and dynamic interactive scenarios.