Active inference provides a principled account of epistemic exploration and intrinsic motivation as minimizing uncertainty.

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• Active inference treats exploration and exploitation as two different ways of tackling the same problem: minimizing uncertainty.claim0.884
  §2, comment on expected free energy decomposition.
• Active inference agents can carry out epistemic exploration and account for uncertainty about their environment in a Bayes-optimal fashion.claim0.875
  Abstract and §1, summarizing a key property.
• Active inference agents can learn epistemic habits in the absence of extrinsic rewards through ambiguity minimization.claim0.871
  §2, summarizing information-seeking behavior.
• Active inference is a normative principle underwriting perception, action, planning, decision-making and learning in biological or artificial agents.quote0.868
• Active inference offers a degree of plausibility as a process theory of brain function.claim0.860
  Overall assessment from Discussion.
• "Active inference is a self-organising process of action policy selection."quote0.859
• Active inference can be framed as the minimisation of surprise by perception and action.claim0.854
  Concise characterisation from Section 2.
• "active inference separates the problems of optimizing action and perception by assuming that action fulfills predictions based on inferred states"quote0.852