The variational free energy is an upper bound on surprise.

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• Variational free energy measures the fit between an internal (generative) model of its sensations and sensory observations.claim0.821
  Definitional claim from Section 2.
• Variational Free Energy (VFE)concept0.789
  Upper bound on surprisal minimised by any persisting agent; decomposes into noise and insufficient learning in the qFEP
• Free Energy Bound on Surpriseconcept0.787
  Mathematical quantity representing lower bound on probability of sensory input; minimized by both action and perception.
• Minimising expected free energy ensures preferred outcomes are realised, thereby avoiding surprise on average.claim0.782
  How expected free energy links to survival.
• By minimising variational free energy, agents perform approximate Bayesian inference.claim0.780
  Describes the epistemic function of variational free energy.
• The expected free energy subsumes many existing constructs in science and engineering.claim0.779
  Unifying nature of expected free energy claimed in Section 2 and 7.
• Minimising expected free energy specifies the optimal balance between goal-seeking and itinerant novelty-seeking behaviour.claim0.768
  Describes the exploitation-exploration trade-off.
• The expected free energy can be unpacked in terms of risk and ambiguity.claim0.766
  A key decomposition presented in Section 7.