concept
active
concept:epistemic-explorationEpistemic Exploration
Bayes-optimal exploration driven by uncertainty minimization; natural behavior in active inference without handcrafted mechanisms.
Neighborhood — ranked by edge-count
Frameworks (1)
framework
- Active InferencecitesFoundational framework by Karl Friston; the paper extends it to three hierarchical levels for modeling meta-awareness.
Concepts (3)
concept
- Epistemic Foraging / Explorationrelated_tosame_asThe active sampling of observations to maximize information gain and resolve uncertainty about the environment.
- Expected Free EnergyimplementsFree energy expected under future outcomes; guides policy selection via epistemic and extrinsic value.
- Surprise Minimizationassociated_withCore principle: acting to maximize value is equivalent to minimizing surprise by sampling environment to conform to expectations.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Behavior driven by epistemic value; resolving uncertainty through action selection.
- World-disclosing behavior that resolves uncertainty; driven by epistemic value and novelty components of expected free energy
- Active inference theory of consciousness where a hyper-generative-model recursively monitors all inference layers; proposed as mechanism for contemplative wisdom in AI
- Learning model parameters through curious, uncertainty-reducing behavior; reducing ignorance about contingencies
- Expected information gain about hidden states; drives curiosity and novelty-seeking; mutual information term in expected free energy.
- Formal mechanism for curiosity and information-seeking behavior derived from expected free energy.
- The ability to gain relevant empirical information about the world and options.
- Inherent unreliability of biological substrate due to mutation, aging, cancer, parasites; proposed as driver of adaptive cognitive architecture.