Explanatory Style for Socially Interactive Agents

Abstract

Recent years have seen an explosion of interest in computational models of socio-emotional processes, both as a mean to deepen understanding of human behavior and as a mechanism to drive a variety of training and entertainment applications. In contrast with work on emotion, where research groups have developed detailed models of emotional processes, models of personality have emphasized shallow surface behavior. Here, we build on computational appraisal models of emotion to better characterize dispositional differences in how people come to understand social situations. Known as explanatory style, this dispositional factor plays a key role in social interactions and certain socio-emotional disorders, such as depression. Building on appraisal and attribution theories, we model key conceptual variables underlying the explanatory style, and enable agents to exhibit different explanatory tendencies according to their personalities. We describe an interactive virtual environment that uses the model to allow participants to explore individual differences in the explanation of social events, with the goal of encouraging the development of perspective taking and emotion-regulatory skills.

This research was supported in part by the UCN Project, the MIC 21C Frontier R&D Program in Korea, and in part by the U.S. Army Research, Development, and Engineering Command (RDECOM).