Collecting comprehensive data sets of the same subject has become a standard in
neuroscience research and uncovering multivariate relationships among collected data sets …

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 first comprehensive treatment of active inference, an integrative perspective on brain,
cognition, and behavior used across multiple disciplines. Active inference is a way of …

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

Fine-grained recognition poses the unique challenge of capturing subtle inter-class
differences under considerable intra-class variances (eg, beaks for bird species) …

The positive-negative axis of emotional valence has long been recognized as fundamental
to adaptive behavior, but its origin and underlying function have largely eluded formal …

Research on predictive processing models has focused largely on two specific algorithmic
theories: Predictive Coding for perception and Active Inference for decision-making. While …

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

To infer the causes of its sensations, the brain must call on a generative (predictive) model.
This necessitates passing local messages between populations of neurons to update beliefs …

This paper aims to integrate some key constructs in the cognitive neuroscience of cognitive
control and executive function by formalising the notion of cognitive (or mental) effort in …