Update Stage

Second stage of DiffLogic CA where a DLGN computes each cell's new binary state from perception output and current state

Neighborhood — ranked by edge-count

framework

Differentiable Logic Cellular Automata (DiffLogic CA)
implements
The novel framework introduced in this paper, combining DLGN and NCA for fully differentiable discrete CA learning

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.

Belief Updatingconcept0.767
Recursive inference of hidden states and parameters using free energy minimization.
Perception Stageconcept0.760
First stage of DiffLogic CA update where each cell gathers information from neighboring cells via logic gate kernels
Synchronous Updatesconcept0.752
Default update strategy where all cells update simultaneously; contrasted with asynchronous updates
Genetic Algorithm With Developmental Stageframework0.750
Asynchronous Updatesconcept0.748
Update strategy where random subsets of cells are updated per step, simulating independent cell clocks
Harness-Updating Capabilityconcept0.734
The capability of an evolver model to produce useful persistent harness updates from execution evidence
Patch-Closureconcept0.731
A set property meaning all coordinate patches of its elements remain within the set; proved equivalent to axis-aligned hyperrectangles
processesconcept0.727
Represented by boxes in process theory; transformations that take systems as inputs/outputs