Predicting User Psychological Characteristics from Interactions with Empathetic Virtual Agents

Enabling virtual agents to quickly and accurately infer users' psychological characteristics such as their personality could support a broad range of applications in education, training, and entertainment. With a focus on narrative-centered learning environments, this paper presents an inductive framework for inferring users' psychological characteristics from observations of their interactions with virtual agents. Trained on traces of users' interactions with virtual agents in the environment, psychological user models are induced from the interactions to accurately infer different aspects of a user's personality. Further, analyses of timing data suggest that these induced models are also able to converge on correct predictions after a relatively small number of interactions with virtual agents.

[1]  C. L. Rusting,et al.  Personality, mood, and cognitive processing of emotional information: three conceptual frameworks. , 1998, Psychological bulletin.

[2]  Hannes Högni Vilhjálmsson,et al.  Social Perception and Steering for Online Avatars , 2008, IVA.

[3]  Stacy Marsella,et al.  Thespian: Modeling Socially Normative Behavior in a Decision-Theoretic Framework , 2006, IVA.

[4]  Ning Wang,et al.  Creating Rapport with Virtual Agents , 2007, IVA.

[5]  James C. Lester,et al.  Modeling parallel and reactive empathy in virtual agents: an inductive approach , 2008, AAMAS.

[6]  Timothy W. Bickmore,et al.  Establishing and maintaining long-term human-computer relationships , 2005, TCHI.

[7]  A Social-Cognitive Framework for PALs , 2006 .

[8]  W. Lewis Johnson,et al.  Serious Use of a Serious Game for Language Learning , 2007, AIED.

[9]  Wenji Mao,et al.  Modeling social inference in virtual agents , 2009, AI & SOCIETY.

[10]  Clifford Nass,et al.  The media equation - how people treat computers, television, and new media like real people and places , 1996 .

[11]  Ning Wang,et al.  Agreeable People Like Agreeable Virtual Humans , 2008, IVA.

[12]  Paul T. Costa,et al.  Personality in Adulthood: A Five-Factor Theory Perspective , 2005 .

[13]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques, 3rd Edition , 1999 .

[14]  Ian H. Witten,et al.  Data mining - practical machine learning tools and techniques, Second Edition , 2005, The Morgan Kaufmann series in data management systems.

[15]  Ian Witten,et al.  Data Mining , 2000 .

[16]  James C. Lester,et al.  Affective Transitions in Narrative-Centered Learning Environments , 2008, J. Educ. Technol. Soc..

[17]  Andrew Stern,et al.  Structuring Content in the Façade Interactive Drama Architecture , 2005, AIIDE.

[18]  J. Uleman.  A framework for thinking intentionally about unintended thoughts , 1989 .

[19]  James C. Lester,et al.  U-director: a decision-theoretic narrative planning architecture for storytelling environments , 2006, AAMAS '06.

[20]  Jonathan P. Rowe,et al.  The effects of empathetic virtual characters on presence in narrative-centered learning environments , 2008, CHI.

[21]  Clifford Nass,et al.  Consistency of personality in interactive characters: verbal cues, non-verbal cues, and user characteristics , 2000, Int. J. Hum. Comput. Stud..