Bayesian Model Reduction (BMR)

Where ideas in this framework connect to the rest of the corpus — the same concept, an analogy, or a restatement elsewhere.

• Separation Prior (sigma)
  ≈Avidya (Ignorance)· buddhist

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• Bayesian model reduction (method)method0.867
  A method for simplifying models by removing parameters that don't contribute; applied to eliminate the self-boundary prior.
• prior eliminated by Bayesian model reductionconcept0.796
  Bayesian model reduction removes the structural partition prior once evidence shows it is unnecessary, yielding a post-dual agent.
• Bayesian model reduction formalises post-hoc hypothesis testing to simplify the generative model.claim0.792
  Definition of Bayesian model reduction, Section 9.1.
• Bayesian model reduction after 12 trials correctly removes off-diagonal (redundant) parameters from the likelihood array, recovering the true contingency structure.finding0.786
  Validation that BMR correctly identifies and prunes wrong connections in the likelihood mapping
• Bayesian Model-Based Reinforcement Learningframework0.766
  RL variant that maintains beliefs over environment model; compared to active inference using Thompson sampling.
• Bayesian Model Selectionconcept0.763
  Choosing among candidate models based on model evidence.
• In simulations, positive evidence threshold for Bayesian model reduction corresponds to ΔF ≤ −3, equivalent to odds ratio of exp(−3) ≈ 0.05 (reduced model ~20 times more likely than full model).finding0.750
  Quantitative threshold used for accepting reduced models; linked to Bayes factor of ~20
• Bayesian Model Expansionmethod0.750
  Adding new states or parameters to the generative model if it increases model evidence, enabling concept learning.