The Logic of Mood: An Integration of Mood and Emotion in a Logical Model

Abstract

Over the years we have seen an increasing amount of intelligent agent models with emotions. However, another affective state that is equally important, and which closely interacts with emotions, is often overlooked: mood. In this thesis, we aim to integrate the affect mood in models of agents with emotions. To gain a deeper understanding of the affective phenomena emotion and mood, we have explored theories of emotion and mood from different fields of study, mainly from psychology and artificial intelligence. The logical model of Steunebrink (2010) and the computational model ALMA are the foundations for a new structure of the process of emotion. This new structure allows for easy incorporation of mood. Upon closer inspection we find that there are discrepancies between the logical and the computational model. These models are both inspired by psychological theories. Therefore we investigate these underlying psychological theories of the models, and use the information from these theories to integrate mood with emotion. In the end we propose a new structure for the emotion elicitation process which combines factors from the original psychological theories and from the logical and computational models, and which eliminates discrepancies that occurred in the integration of mood and emotion.