This paper provides a concise description of the free energy principle, starting from a
formulation of random dynamical systems in terms of a Langevin equation and ending with a …

Active inference is a normative principle underwriting perception, action, planning, decision-
making and learning in biological or artificial agents. From its inception, its associated …

The active inference framework, and in particular its recent formulation as a partially
observable Markov decision process (POMDP), has gained increasing popularity in recent …

The free-energy principle (FEP) is a formal model of neuronal processes that is widely
recognised in neuroscience as a unifying theory of the brain and biobehaviour. More …

This paper considers functional integration in the brain from a computational perspective.
We ask what sort of neuronal message passing is mandated by active inference—and what …

This paper concerns the distributed intelligence or federated inference that emerges under
belief-sharing among agents who share a common world—and world model. Imagine, for …

This essay addresses Cartesian duality and how its implicit dialectic might be repaired using
physics and information theory. Our agenda is to describe a key distinction in the physical …

Active inference is an approach to understanding behaviour that rests upon the idea that the
brain uses an internal generative model to predict incoming sensory data. The fit between …

Understanding information processing in the brain—and creating general-purpose artificial
intelligence—are long-standing aspirations of scientists and engineers worldwide. The …

The aim of this paper is twofold:(1) to assess whether the construct of neural representations
plays an explanatory role under the variational free-energy principle and its corollary …