Free Energy in a Circumplex Model of Emotion

TL;DR

This paper extends active inference models of emotion by integrating a Circumplex Model, representing emotions as valence and arousal, and demonstrates how expected free energy can generate these emotional signals in simulated agents.

Contribution

It introduces a novel mapping of free energy to a two-dimensional emotion space using the Circumplex Model, enhancing the understanding of emotion representation in active inference.

Findings

Expected free energy can be mapped to valence and arousal signals.

Manipulating priors and object presence affects simulated emotional states.

The model reproduces variability in emotions consistent with affective science.

Abstract

Previous active inference accounts of emotion translate fluctuations in free energy to a sense of emotion, mainly focusing on valence. However, in affective science, emotions are often represented as multi-dimensional. In this paper, we propose to adopt a Circumplex Model of emotion by mapping emotions into a two-dimensional spectrum of valence and arousal. We show how one can derive a valence and arousal signal from an agent's expected free energy, relating arousal to the entropy of posterior beliefs and valence to utility less expected utility. Under this formulation, we simulate artificial agents engaged in a search task. We show that the manipulation of priors and object presence results in commonsense variability in emotional states.