car position

The scalar variable representing the car's location in the Mountain Car reinforcement learning problem, found to be encoded as a 1D manifold.

Neighborhood — ranked by edge-count

finding

In the Mountain Car case study, car position is a 1D manifold; linear interventions cross voids causing incoherence; following the 1D curve produces smooth control.
cites
Empirical demonstration that a semantically meaningful variable is encoded as a curved manifold, and that respecting its geometry is critical for effective intervention.

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.

Positional Informationconcept0.781
The biological mechanism by which chemical gradients create developmental patterns; cited as insufficient to explain coherence of embryological unfolding as a whole
Placement as Divisionmethod0.773
position of a roomconcept0.771
The location of a room within the building in relation to movement, light, and connection to the outdoors; the first stage of unfolding.
Position (Primary Move)concept0.758
What Determines The Position Of A Species Onquestion0.758
Alignmentconcept0.750
The goal of making model behavior match human values and intentions, often addressed during post-training.
Position Encodingsconcept0.735
Mechanism for encoding sequence order in transformers; paper argues these should reflect learned structural representations rather than fixed sines/cosines.
Placement (primary move)method0.734
Primary move: positioning elements as an act of division and distinction, the first gesture that defines the spatial field.