A tale of two densities: active inference is enactive inference

The aim of this article is to clarify how best to interpret some of the central constructs that underwrite the free-energy principle (FEP) - and its corollary, active inference - in theoretical neuroscience and biology: namely, the role that generative models and variational densities play in this theory. We argue that these constructs have been systematically misrepresented in the literature, because of the conflation between the FEP and active inference, on the one hand, and distinct (albeit closely related) Bayesian formulations, centred on the brain - variously known as predictive processing, predictive coding or the prediction error minimisation framework. More specifically, we examine two contrasting interpretations of these models: a structural representationalist interpretation and an enactive interpretation. We argue that the structural representationalist interpretation of generative and recognition models does not do justice to the role that these constructs play in active inference under the FEP. We propose an enactive interpretation of active inference - what might be called enactive inference. In active inference under the FEP, the generative and recognition models are best cast as realising inference and control - the self-organising, belief-guided selection of action policies - and do not have the properties ascribed by structural representationalists.