The Affective Tigger reacts to his playmate with a display of emotion, based on his perception of the mood of play. This would be aimed at learning situations where the agent acts as a kind of mentor, occasionally supporting the user in his or her otherwise self-propelled exploration. It also provides an opportunity for learning about the role of human emotions expressed during a learning situation. Behavioral results showed the agent was significantly more effective than the control conditions in helping relieve frustration levels. We have begun an effort to outfit a car and driver with various sensors and pattern recognition that aims to recognize important affective states of the driver such as anger or stress.
Experimental results are forthcoming.
A study in pattern recognition correlation of biosignals from an actor's body during the actor's self-induced emotional states. Includes a new online-emotion recognition algorithm. We conduct basic research in Bayesian learning theory, pattern recognition, and other aspects of modeling that form the crucial underpinnings of our efforts to build robust, flexible, and adaptive systems. Details on the learning algorithm development are in Minka's 1996 master's thesis, An Image Database Browser that Learns from User Interaction . User Modeling of Physiology.