Epistemic Learning

Learning model parameters through curious, uncertainty-reducing behavior; reducing ignorance about contingencies

Neighborhood — ranked by edge-count

concept

Table 1: Sources of Uncertainty Scored by Expected Free Energy and the Behaviors Entailed
associated_with
Summary table mapping uncertainty types to free energy formulations and corresponding behaviors

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.

Learningconcept0.840
Inference of parameters encoding contingencies of the world (e.g., likelihood matrix A) at slower timescale than perception.
Epistemic Behaviorconcept0.817
World-disclosing behavior that resolves uncertainty; driven by epistemic value and novelty components of expected free energy
Perceptual Learningconcept0.815
Process of inferring causes of sensory information; unified with value learning as integral aspects of free energy minimization.
Epistemic Competenceconcept0.808
The ability to gain relevant empirical information about the world and options.
Epistemic Explorationconcept0.805
Bayes-optimal exploration driven by uncertainty minimization; natural behavior in active inference without handcrafted mechanisms.
Meta-learningconcept0.802
The capability of GPT-3 to learn tasks from few-shot prompts during runtime.
Associative Learningconcept0.799
Sentience criterion; capacity occurs even in gene regulatory networks and non-neural morphogenetic agents.
Epistemic Foragingconcept0.796
Behavior driven by epistemic value; resolving uncertainty through action selection.