Affect plays an important role in the way humans respond to situations. The affective processes may, from the perspective of a reasoning system, be viewed as a heuristic mechanism for efficiently assessing one's circumstances and acting upon them [Oatley1987]. An important, but often ignored component of the simulation of such processes is the intensities of the affective states (e.g. moods, emotions) that arise.
In this article we discuss an approach to reasoning about emotion intensity within the context of the Affective Reasoner [Elliott1992] (hereafter, AR) a computer simulation that reasons about emotions in a multi-agent system. The AR is designed around the constraining hypothesis that there are twenty-four distinct categories of emotion, each based on a different set of eliciting conditions (c.f., [Ortony et al. 1988]). In this context we have postulated the existence of functions that map interpretations of simulated situations into scalar intensity ratings for emotion instances within those categories. Working abductively from descriptions of emotion-generating situations, we used emotion intensity variables to explain the ways in which changes in various aspects of the simulation might cause changes in emotion intensity. These variables, which represent both situations external to the agent, and dispositions and moods internal to the agent, together with some preliminary functions that illustrate their use in computing emotion intensities, are described in this paper.