finding

active

finding:bayesian-model-reduction-after-12-trials-correctly-removes-off-diagonal-redundant-parameters-from-the-likelihood-array-recovering-the-true-contingency-structure

Bayesian model reduction after 12 trials correctly removes off-diagonal (redundant) parameters from the likelihood array, recovering the true contingency structure.

Validation that BMR correctly identifies and prunes wrong connections in the likelihood mapping

Source paper

extracted_from

Active Inference, Curiosity and Insight

(2017) · Karl Friston · Marco Lin · Chris Frith · Giovanni Pezzulo +2

Neighborhood — ranked by edge-count

Claims (1)

claim

Insight ('aha moment') is produced by Bayesian model reduction—a qualitative change in generative model structure that is necessarily subpersonal and cannot be articulated at the level of the model.
supports
Core claim linking insight to post hoc Bayesian model optimization

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

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

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).finding0.837
Quantitative threshold used for accepting reduced models; linked to Bayes factor of ~20
Bayesian model reduction formalises post-hoc hypothesis testing to simplify the generative model.claim0.833
Definition of Bayesian model reduction, Section 9.1.
prior eliminated by Bayesian model reductionconcept0.826
Bayesian model reduction removes the structural partition prior once evidence shows it is unnecessary, yielding a post-dual agent.
In single-agent simulation of 32 trials, performance becomes perfect after trial 14 without Bayesian model reduction, with confidence increasing progressively.finding0.819
Baseline learning curve for pure epistemic learning without structure learning
Nearly all of 64 simulated agents attain 100% performance at around the 10th trial when allowed to perform abductive Bayesian model reduction after each trial.finding0.815
Group-level simulation result showing generalizability of BMR benefit across agents
Structure learning via Bayesian model reduction has a clear biological interpretation in terms of synaptic decay and switching off certain synaptic connections, reminiscent of REM sleep.claim0.803
Biological interpretation of Bayesian model reduction.
Once visible, the prior is eliminated via Bayesian model reduction resulting in a post-dual agent with unconstrained QRF deployments.claim0.795
Formal description of the transition to post-duality.
Bayesian Model Reduction (BMR)framework0.786
Formal mechanism by which the separation prior sigma is pruned from the generative model