Value Iteration

A dynamic programming method for computing optimal value functions and policies in known MDPs.

Neighborhood — ranked by edge-count

paper

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.

valueconcept0.810
Probability of sensory input expected by an agent, aligning value maximization with surprise minimization.
semantic valueconcept0.762
Meaning that arises from relations within the graphical system, not inherent in elements.
negative valueconcept0.751
Negative of value, equated with free-energy and surprise.
repetitionconcept0.750
The reappearance of similar elements, essential for unity and order in a living floor or ceiling.
Value Ruleconcept0.750
Spreadsheet-like rule defining how a rectangle's or object's value is computed; enables data-driven behavior across all Playground tools.
Expert Iterationmethod0.749
Second training stage: samples responses, filters for type hints, and fine-tunes on filtered responses across four rounds to reinforce evaluation behavior.
Epistemic Valueconcept0.747
Expected information gain about hidden states; drives curiosity and novelty-seeking; mutual information term in expected free energy.
Value of Informationconcept0.744
Economic concept related to epistemic value in expected free energy; information needed to realize rewards