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WaveFunctionCollapse reviews and mentions
 I use Wave Function Collapse to create levels for my game (2022) [video]

It's Okay to Make Something Nobody Wants
Thank you! And yes, I agree. I was looking at uh https://github.com/mxgmn/WaveFunctionCollapse and wondering if that were applicable here :)
Have a good day!
 The Wavefunction Collapse Algorithm

Kullbackâ€“Leibler Divergence
Intuitively, it measures the difference between two probability distributions. It's not symmetric, so it's not quite that, but in my opinion, it's good intuition.
As motivation, say you're an internet provider, providing internet service to a business. You naturally want to save money, so you perhaps want to compress packets before they go over the wire. Let's say the business you're providing service to also compresses their data, but they've made a mistake and do it inefficiently.
Let's say the business has, incorrectly, determined the probability distribution for their data to be $q(x)$. That is, they assign probability of seeing symbol $x$ to be $q(x)$. Let's say you've determined the "true" distribution to be $p(x)$. The entropy, or number of bits, they expect to transmit per packet/symbol will be $\sum p(x) lg(q(x))$. Meaning, they'll compress their stream under the assumption that the distribution is $q(x)$ but the actually probability of seeing a packet, $x$, is $p(x)$, which is why the term $p(x) lg(q(x))$ shows up.
The number of bits you're transmitting is just $\sum p(x) lg(p(x))$. Now we ask, how many bits, per packet, is the savings of your method over the businesses? This is $\sum p(x) lg(q(x)/p(x))$, which is exactly the KullbackLeibler divergence (maybe up to a sign difference).
In other words, given a "guess" at a distribution and the "true" distribution, how bad is it between them? This is the KullbackLeibler distribution and why it shows up (I believe) in machine learning and fitness functions.
As a more concrete example, I just ran across a paper talking [0] about using WFC [1] to asses how well it, and other algorithms, do when trying to create generative "super mario brothers" like levels. Take a 2x2 or 3x3 grid, make a library of tiles, use that to generate a random level, then use the KL divergence to determine how well your generative algorithm has done compared to the observed distribution from an example image.
[0] https://arxiv.org/pdf/1905.05077.pdf
[1] https://github.com/mxgmn/WaveFunctionCollapse

All of it under the most poorly designed and maintained village
Reminds me of wave function collapse  a programmatic way to generate mazes.

How to detect and fix isolated terrain (islands or lakes) in a tilebased terrain?
I am using WFC to generate the terrain, with pretty much a copypaste implementation of the original WFC implemented into Unity.

How to make wfc or postgen script in blender?
If you still want to go the WFC route, the original WFC repository is a great place to start. There's also a (relatively barebones looking) Godot plugin you could take a look at.
 Wave Function Collapse

collapsed
wave function collapse studies  this is done with the https://github.com/mxgmn/WaveFunctionCollapse algorithm after I saw https://github.com/CodingTrain/WaveFunctionCollapse mention it. done in P5! IG https://www.instagram.com/ronivonu/

Room Generation Using Constraint Satisfaction
Thereâ€™s an interesting approach similar to this called [Wave Function Collapse](https://github.com/mxgmn/WaveFunctionCollapse) (no relation to wfc in physics idea besides inspiration). It can infer the probabilistic constraints from one input example, and it seems to generalize quite well. Hereâ€™s a [little demo](https://oskarstalberg.com/game/wave/wave.html)

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www.saashub.com  24 Apr 2024
Stats
mxgmn/WaveFunctionCollapse is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of WaveFunctionCollapse is C#.
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