Show HN: MarkovJunior, PPL based on pattern matching and constraint propagation
1–10 of 15 posts
Re: Show HN: MarkovJunior, PPL based on pattern matching and constraint propagation
#2This is really neat, thanks for making this!
Re: Show HN: MarkovJunior, PPL based on pattern matching and constraint propagation
#3Fascinating. One of the few things posted here that got me really excited! Probably because I studied the basics of Markov algorithms, but I never imagined the idea could be developed further in such an interesting way.
Re: Show HN: MarkovJunior, PPL based on pattern matching and constraint propagation
#4This is phenomenal! I have been toying with similar ideas, and I am so glad you are the same person behind Wave Function Collapse [1] . The fact that you have lifted the technique into a programming language is immensely powerful. Where do you want to go with it?
What research or other projects have been impactful on this work?
From the author, 40 minutes of the algorithm running through examples. [2]
Past stories about Wave Function Collapse [3]
[1] https://github.com/mxgmn/WaveFunctionCollapse
Youtube videos of WFC https://www.youtube.com/results?search_query=wave+function+c...
[2] https://www.youtube.com/watch?v=DOQTr2Xmlz0
[3] https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...
Re: Show HN: MarkovJunior, PPL based on pattern matching and constraint propagation
#5This is phenomenal! I have been toying with similar ideas, and I am so glad you are the same person behind Wave Function Collapse [1] . The fact that you have lifted the technique into a programming language is immensely powerful. Where do you want to go with it? What research or other projects have been impactful on this work? From the author, 40 minutes of the algorithm running through examples. [2] Past stories ab…
This paper is an excellent jumping off point into the academic literature.
https://www.semanticscholar.org/paper/Combining-Markov-Rando...
Re: Show HN: MarkovJunior, PPL based on pattern matching and constraint propagation
#6This is phenomenal! I have been toying with similar ideas, and I am so glad you are the same person behind Wave Function Collapse [1] . The fact that you have lifted the technique into a programming language is immensely powerful. Where do you want to go with it? What research or other projects have been impactful on this work? From the author, 40 minutes of the algorithm running through examples. [2] Past stories ab…
Thank you!
For MarkovJunior, the recent projects that were impactful the most were Imagegram by Guilherme S. Tows [1] and Daniel Ritchie's dissertation [2] about PPLs for procgen. I took quite a different approach from Ritchie's though.
Re: Show HN: MarkovJunior, PPL based on pattern matching and constraint propagation
#7Fascinating. One of the few things posted here that got me really excited! Probably because I studied the basics of Markov algorithms, but I never imagined the idea could be developed further in such an interesting way.
Thanks! I would have probably never known about Markov algorithms if I were not taught them in 8th grade =)
Re: Show HN: MarkovJunior, PPL based on pattern matching and constraint propagation
#8Most satisfying animations I've seen in a long time. I just can't stop staring at them, they are wonderful.
Are there any other possible use cases of this language other then image or maybe in-game world generation? Do you consider it just as an interesting academic problem or do you plan to use it somewhere?
Re: Show HN: MarkovJunior, PPL based on pattern matching and constraint propagation
#9This would be totally cool if it had an S-expression input syntax. (I mean, it's totally cool as it is, of course...)
Re: Show HN: MarkovJunior, PPL based on pattern matching and constraint propagation
#10An untested idea/suggestion...
In the first Open Problem, maybe the generator tweak for random Hamiltonian paths is that two grids are needed: one for the eventual H-path; and one of points that are the centroids of the first which is used to draw a random tree starting from some point, subject to some rules about distances to unconnected nearest neighbours being acceptable (hunch e.g. of length >= sqrt(2)). Then draw around that tree on the first grid to get the H-path. (Grid graph duality use.)
I'd guess this can be generalised to 3D by drawing the H-path on each 2D plane slice, and some simple rules about choosing the degree of interconnection between those planes.
It seems like all the tools for tuning the shape of the initial random trees already exist in MJ, based on the examples shown.