An implementation of Tak and a computer opponent in C https://git.l-3.space/cgit/ctak/atom?h=main 2026-08-28T18:37:41Z 2026-08-28T18:37:41Z tslil clingman tslil@posteo.de 2023-01-15T20:31:00Z urn:sha1:0223a9bec5535fced1a7698b55fd42155d9b0446 Previously the code base assumed that there was a single, global game state which was the implicit target of all actions taken. Looking ahead at architectural improvements, this has now been (almost entirely) made explicit and functions take tak_state_p where necessary (and also where unnecessary). Two important fixes to actions.c were made: - Previously when generating the possible stack moves, stack height overflows (> 15) were not taken into account and this resulted in the tree search corrupting the board state. Now action search does not list all legal actions, rather the subset of these encodeable by the implementation. - The check for crushing on a stack move was incorrect (too strict), and this resulted in many legitimate moves being igonored. Finally, in other changes, weights have also been improved by training all games instead of some subset for chosen players, and clang-format was run on the codebase. 2026-08-28T18:37:41Z tslil clingman tslil@posteo.de 2021-10-05T22:22:23Z urn:sha1:cf175fc346f1b208766b1f55d3673a7b208f322a This is a special interface to negamax_cnn1986 which is designed to generate output for use in a CGI tak interface to be used over gemini. Also in this commit is a reformating of the various source files to use the traditional tab width of 8 spaces. 2026-08-28T18:37:41Z tslil clingman tslil@posteo.de 2021-07-02T16:00:00Z urn:sha1:640d404b3cf3324aca4424fc3da4806d4562d0e4 Previously check_win would call check_road_colour once for each road colour, and check_road_colour would call a depth-first search (DFS) for each of the two axes. This meant that we were doing (up to) *four* depth-first searches for each call of check_win. I have replaced both axial DFS with the world's worst TM implementation of a connected component generation algorithm backed by the least guaranteed disjoint set data structure. Essentially doing anything about union find correctly is slower than just ... not doing it. Although we lose the asymptotic complexity, in practice we're doing this millions of times per turn, for a fixed board size and that's what matters. All in all, it appears that i've managed to shave about 69ns off check_win, per call -- nice! This amounts to 50ms or so saved at depth 5 per engine move, in one of my test games. Unfortunately nearly 99% of the time is still taken by evaluating the convolutional neural network. It's slow. 2026-08-28T18:37:41Z tslil clingman tslil@posteo.de 2021-03-28T04:19:05Z urn:sha1:2dbb9fa9b69e49d49cebb1c17559f6fe67600a4d Eventually there'll be a more complicated data generation step than the one we're presently using, so having it in-lined in the loop is wasteful. Ideally also this would be update per ply and we could avoid recalculating it entirely for every query -- though it's probably ``fast enough'' for now. Also, caching is WIP. 2026-08-28T18:37:41Z tslil tslil@posteo.de 2021-02-05T21:49:14Z urn:sha1:ce09b6d94ac3dbf426e959b14fd7731001a003d1 2026-08-28T18:37:41Z tslil clingman tslil@posteo.de 2021-02-03T00:23:54Z urn:sha1:40c6b1dafab4de169bac8a799e7953e85061218e 2026-08-28T18:37:41Z tslil clingman tslil@posteo.de 2021-01-29T02:30:30Z urn:sha1:a77062ce3dc9a99ad0662010cc7eeb00dd5036a6 2026-08-28T18:37:41Z tslil clingman tslil@posteo.de 2021-01-24T17:07:18Z urn:sha1:815cde44e5060ad093347bb47fc66d41c9d3a3ed | 2026-08-28T18:37:41Z tslil clingman tslil@posteo.de 2021-01-21T19:56:55Z urn:sha1:eab1d81df4455eb89b2663dcdd45a024f4633a2e 2026-08-28T18:37:41Z tslil clingman tslil@posteo.de 2021-01-21T06:16:20Z urn:sha1:9fa3291044ff8d9f0f2b9c9a01cd210bf318ab74