Mateus Joffily, Giorgio Coricelli, Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne (GATE Lyon Saint-Étienne), École normale supérieure de Lyon (ENS de Lyon)-Université Lumière - Lyon 2 (UL2)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS), Groupe d'analyse et de théorie économique (GATE Lyon Saint-Étienne), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-École normale supérieure - Lyon (ENS Lyon), Center for Mind/Brain Sciences, Università degli Studi di Trento (UNITN), Department of Economics, University of Southern California, University of Southern California (USC), and Dao, Taï
The free-energy principle has recently been proposed as a unified Bayesian account of perception, learning and action. Despite the inextricable link between emotion and cognition, emotion has not yet been formulated under this framework. A core concept that permeates many perspectives on emotion is valence, which broadly refers to the positive and negative character of emotion or some of its aspects. In the present paper, we propose a definition of emotional valence in terms of the negative rate of change of free-energy over time. If the second time-derivative of free-energy is taken into account, the dynamics of basic forms of emotion such as happiness, unhappiness, hope, fear, disappointment and relief can be explained. In this formulation, an important function of emotional valence turns out to regulate the learning rate of the causes of sensory inputs. When sensations increasingly violate the agent's expectations, valence is negative and increases the learning rate. Conversely, when sensations increasingly fulfil the agent's expectations, valence is positive and decreases the learning rate. This dynamic interaction between emotional valence and learning rate highlights the crucial role played by emotions in biological agents' adaptation to unexpected changes in their world., Author Summary Emotion plays a crucial role in the adaptation of humans and other animals to changes in their world. Nevertheless, emotion has been neglected in Bayesian models of learning in non-stationary environments. The free-energy principle has recently been proposed as a unified account of learning, perception and action in biological agents. In this paper, we propose a formal definition of emotional valence (i.e., the positive and negative character of emotion) in terms of the rate of change of free-energy or, under some simplifying assumptions, of prediction error over time. This formalization leads to a straightforward and simple meta-learning scheme that accounts for the complex and reciprocal interaction between cognition and emotion. We instantiate this scheme with an emotional agent who is able to dynamically assign emotional valence to every new state of the world that is visited and to experience basic forms of emotion. Crucially, our hypothetical agent uses emotional valence to dynamically adapt to unexpected changes in the world. The proposed scheme is very general in the sense that it is not tied to any particular generative model of sensory inputs.