Abstract We study the interplay of moods, emotions, and trust in decisionmaking contexts characterized by commitments among agents. We develop a general approach representing the relationships among these concepts via a Bayesian network model. Our approach incorporates insights from the literature and provides a computational methodology for identifying improved Bayesian models. Based on observations from an empirical study, we motivate a refined Bayesian model involving the above-mentioned concepts that goes beyond the relationships known in the literature. Our findings include (1) the violation of a commitment affects trust more than its satisfaction; (2) goal satisfaction affects mood and emotion more than commitment satisfaction, but the outcome of a commitment affects trust more than the outcome of a goal; and (3) an agent's prior mood and trust affect whether it satisfies its commitments
