Affective state can influence users ’ cognitive processing capabilities and hence their productivity (Picard 1997). The first goal of our research is to develop methods to timely and efficiently recognize negative user affective states, model their influence on cognition and behavior, and provide the most appropriate intervention in a timely manner to return the user to his/her productive state. The second, more distal, goal is to develop an integrated architecture of affect and cognition. There are four challenges facing this initiative. (1) Users ’ affect develops over time, and its expressions vary significantly with individual and context. (2) Affective state observations from a given sensory source are ambiguous, uncertain, and incomplete. (3) The influence of cognition on affective state and vice versa is not well understood. (4) Interventions to improve user performance mus
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