Publication
Designing Emotions - An Empirical Approach to Realistic Affect Simulation
Michael Kipp; Thomas Dackweiler; Patrick Gebhard
In: KI - Künstliche Intelligenz, German Journal on Artificial Intelligence - Organ des Fachbereiches "Künstliche Intelligenz" der Gesellschaft für Informatik e.V. (KI), Vol. 25 - Special Issue on Emotion and Computing, No. 3, Pages 205-211, Springer, 8/2011.
Abstract
While current virtual characters may look photorealistic they often lack behavioral complexity. Emotion may be the key ingredient to create behavioral variety, social adaptivity and thus believability. While various models of emotion have been suggested, the concrete parametrization must often be designed by the implementer. We propose to enhance an implemented affect simulator called ALMA (A Layered Model of Affect) by learning the parametrization of the underlying OCC model through user studies. Users are asked to rate emotional intensity in a variety of described situations. We then use regression analysis to recreate these reactions in the OCC model. We present a tool called EMIMOTO (EMotion Intensity MOdeling TOol) in conjunction with the ALMA simulation tool. Our approach is a first step toward empirically parametrized emotion models that try to reflect user expectations.