Robotics is increasingly seen as a useful test bed for computational models of the brain
functional architecture underlying animal behavior. We provide an overview of past and …

Robotics can play a useful role in the scientific understanding of the sense of self, both
through the construction of embodied models of the self and through the use of robots as …

Active inference is a mathematical framework which originated in computational
neuroscience as a theory of how the brain implements action, perception and learning …

This paper develops a Bayesian mechanics for adaptive systems. Firstly, we model the
interface between a system and its environment with a Markov blanket. This affords …

Recent advances in neuroscience have characterised brain function using mathematical
formalisms and first principles that may be usefully applied elsewhere. In this paper, we …

Predictive processing has become an influential framework in cognitive sciences. This
framework turns the traditional view of perception upside down, claiming that the main flow …

Deep active inference has been proposed as a scalable approach to perception and action
that deals with large policy and state spaces. However, current models are limited to fully …

Abstract Service robots sharing the same environments with humans are typically designed
to have various humanlike features, because perceptions of robots as humanlike make them …

We present a normative computational theory of how the brain may support visually-guided
goal-directed actions in dynamically changing environments. It extends the Active Inference …

Active inference is a probabilistic framework for modeling the behavior of biological and
artificial agents, which derives from the principle of minimizing free energy. In recent years …