I prefer the name given in mathematical optimization, which is Constraints Satisfaction Problems; instead of using an imprecise physics metaphor, it gets a descriptive logical term of what's going on.
In CSPs, each cell is a 'decision variable' with a 'domain' of values, which get pruned by 'constraints' that propagate to values invalidated by the decisions made in the connected variables, until the whole 'problem' gets into either a solution which 'satisfies' all the constraints, or a contradictory state where a variable's domain is empty, causing the algorithm to backtrack.
CSPs have the advantage of having clear and efficient methods to go back to a previous state and keep exploring every alternate possibility, rather than having to restart from the beginning. The article hints at that possibility ('saving checkpoints' or'reverse the collapsing of a cell'); there's a whole field of study dedicated on the best ways to do that on a large scale for very general problems.
Boris the brave coined the term "Constraint Based Tile Generators" (CBTG) [0], which is a specialization of the more general CSPs to this particular domain.
Personally, I find CSPs overly general and mired in esoteric, byzantine terminology. It's a large cognitive load to put on people to run through the glossary of terms just to talk about the problem set up. I don't think the quantum mechanic analogy is great but I can see it being much more intuitive than the obscure language of CSPs.
TuringTest|4 months ago
In CSPs, each cell is a 'decision variable' with a 'domain' of values, which get pruned by 'constraints' that propagate to values invalidated by the decisions made in the connected variables, until the whole 'problem' gets into either a solution which 'satisfies' all the constraints, or a contradictory state where a variable's domain is empty, causing the algorithm to backtrack.
CSPs have the advantage of having clear and efficient methods to go back to a previous state and keep exploring every alternate possibility, rather than having to restart from the beginning. The article hints at that possibility ('saving checkpoints' or'reverse the collapsing of a cell'); there's a whole field of study dedicated on the best ways to do that on a large scale for very general problems.
zzyzek|4 months ago
Personally, I find CSPs overly general and mired in esoteric, byzantine terminology. It's a large cognitive load to put on people to run through the glossary of terms just to talk about the problem set up. I don't think the quantum mechanic analogy is great but I can see it being much more intuitive than the obscure language of CSPs.
[0] https://www.boristhebrave.com/2021/10/31/constraint-based-ti...