Towards an Integrated Cognitive Architecture for Modeling and Recognizing User Affect

Architectures for Modeling Emotion: Cross-Disciplinary Foundations

Volume

Papers from the 2004 AAAI Spring Symposium

Contents

We outline the cognitive model CASS (Cognitive CAffective 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 de-termine the impact of affective state on cognitive process-ing, 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 cog-nitive implications of the user’s affective state are determined by analyzing the deviation of user behavior from the optimal path determined by the model.