Table 1.

Definitions of the tuple underlying active inference.

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

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

sensory states the agent's sensations that constitute a probabilistic mapping from action and external states

action states an agent's action that depends on its sensory and internal states

internal states the states of the agent that cause action and depend on sensory states

ergodic density a probability density function over external ψ ∈ Ψ, sensory s ∈ S, active a ∈ A and internal states λ ∈ Λ for a system denoted by m

variational density q(ψ|λ) an arbitrary probability density function over external states that is parametrized by internal states