Ji, Gray, Guhe, & Schoelles (2004)

Ji, Q., Gray, W. D., Guhe, M., & Schoelles, M. J. (2004). Towards an integrated cognitive architecture for modeling and recognizing user affect. Paper presented at the AAAI Spring Symposium on Emotion Modeling and Recognition, Stanford, CA..


We outline the cognitive model CASS (Cognitive–Affective State System). As the name suggests it is a cognitive model that also takes human affect into account. CASS combines Dynamic Bayesian Networks (DBNs) and an ACT-R model. The DBN model (R-BARS, the Rensselaer Bayesian Affect Recognition System) determines the user’s most likely affective states using both current and stored sensory data. The affective–cognitive model integrates R-BARS with ACT-R to play two roles: (1) the use of model tracing to determine the impact of affective state on cognitive proc-essing, and (2) linking changes in affective state to changes in the value of ACT-R’s parameters so as to directly generate (i.e., predict) the influence of affect on cognition. The cognitive implications of the user’s affective state are determined by analyzing the deviation of user behavior from the optimal path determined by the model.


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