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

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• "Active inference is a self-organising process of action policy selection."quote0.871
• Active inference provides a principled account of epistemic exploration and intrinsic motivation as minimizing uncertainty.claim0.868
  §1, listing contributions.
• "active inference separates the problems of optimizing action and perception by assuming that action fulfills predictions based on inferred states"quote0.848
• Active inference dispenses with the Bellman optimality principle and replaces it with a (variational) principle of least action.claim0.841
  §2, expected free energy section.
• Active inference offers an attractive natural adaptation mechanism for non-stationary environments due to its Bayesian model updating properties.claim0.839
  §3, after non-stationary results.
• Active inference describes the dynamics of systems that persist at non-equilibrium steady-state and that can be statistically segregated from their environment via a Markov blanket.claim0.838
  Sets the theoretical grounding in Section 2.
• Active inference can be framed as the minimisation of surprise by perception and action.claim0.838
  Concise characterisation from Section 2.
• Active inference offers a degree of plausibility as a process theory of brain function.claim0.830
  Overall assessment from Discussion.