Series: The Learn Arc — 50 posts through the Active Inference workbench. Previous: Part 44 — Session §9.1: Fit to data Hero line. The agent uses free energy to arbitrate between explanations of the world. The scientist uses free energy to arbitrate between models of the agent. Same equation, one level up. Self-similar Bayes In Session 9.1 we fit one model's parameters. In Session 9.2 we step back and ask: is this model even the right one? The answer comes from model evidence — the marginal likelihood p(data | model) — and its free-energy approximation is literally the same object Eq 4.13 minimised, just evaluated at the model level instead of the state level. Active Inference is self-similar this way: inference over states, inference over parameters, inference over models. All three are the same Bayes. Five beats Model evidence integrates out the parameters. p(data | M) = ∫ p(data | θ, M) p(θ | M) dθ . Not the max likelihood — the average over the prior. That integral is the currency of model comparison.…