danvk
Joined 17 years ago
Joined 17 years ago
(I briefly got excited that there might be a street sign _in_ the photo, but if you zoom way in it says "DENTIST")
+1 to 1940s.nyc. Very different photos — those are were taken for tax assessment, the ones on OldNYC were taken to document the city as it changed. The photographer had an arrangement where he'd get tips from demolition crews, and go shoot buildings before they were gone forever.
[1]: https://digitalcollections.nypl.org/items/5a5e06a0-c539-012f...
I’d love to read a post explaining how TS conditional types are or are not a form of dependent types. Or, I’d like to understand dependent types well enough to write that post.
This analysis doesn't make use of the Boggle dice. It assumes that any cell can be any letter. In practice, all high-scoring boards can be rolled with the Boggle dice. My code does assume the letters are A-Z, though, so the Ñ die in Spanish Boggle would require some code changes.
Depending on wordlist and whether you want a 16 or 17 letter word, you get "charitablenesses", "supernaturalised" (British spelling), "quadricentennials" or "quartermistresses". These boards all score considerably lower than the REPLASTERING board. Full results here: https://github.com/danvk/hybrid-boggle/#highest-scoring-boar...
I hadn't realized until I did this "side quest" that most wordlists top out at 15 letter words. That makes sense for a Scrabble dictionary, but it's not great for Boggle.
There are some examples in these old posts:
- https://www.danvk.org/wp/2009-08-08/breaking-3x3-boggle/inde...
- https://www.danvk.org/wp/2009-08-11/a-few-more-boggle-exampl...
These bounds are pretty effective at finding the global max for 3x3 Boggle, but 4x4 is a lot bigger.
There is a mapping from Boggle optimization to ILP, but I’ve seen no evidence that this is an efficient way to solve it. I’ve been told that branch and cut is usually better than branch and bound, but I don’t know whether it’s applicable to Boggle.
For context, many people are interested in finding high-scoring Boggle boards, usually via simulated annealing, hillclimbing, or genetic algorithms. But so far as I can tell, I'm the only one interested in _proving_ that a particular board is best. Doing that was the new result here.
It sounds like your Trie implementation had a bug or inefficiency.
The proof used ENABLE2K — repeating it for other wordlists would require another ~23,000 CPU hours each.