Table 1.

Definitions of the tuple underlying active inference.

a sample space Ω or non-empty set from which random fluctuations or outcomes are drawn

external states —hidden states of the world that cause sensory states and depend on action

sensory states —signals that constitute a probabilistic mapping from action and external states

active states —action that depends on sensory and internal states

internal states —representational states that cause action and depend on sensory states

ergodic density —a probability density function over external , sensory , active and internal states for a Markov blanket denoted by m

variational density —an arbitrary probability density function over external states that is parametrized by internal states