Previous active inference accounts of emotion translate fluctuations in free energy to a sense of emotion, sometimes focusing exclusively on valence. However, in affective science, emotions are often represented as multidimensional. In this paper, we adapt a Circumplex Model of emotion to the Active Inference framework by demonstrating a mapping of free energy into valence and arousal, relating valence to utility less expected utility and arousal to the entropy of posterior beliefs. Under this formulation, we simulate artificial agents engaged in a search task and assign emotional states to them. We show that experimental manipulation of priors and object presence results in commonsense variability in these assignments.