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42 hoursmight as well enable size 6tslil clingman
Same network architecture, same training principle. Predictably this is too slow. Also statically allocate state in driver programmes.
42 hoursswitch to explicit game state & important bug fix & clang formattslil clingman
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.
42 hoursnew neural network arch (faster + better) & minor changes + fixestslil clingman
Gone is the convolutional neural network, for it turns out not only is it more difficult to train, but all of the extra information about board layers didn't make much of a difference at this size. So cnn1986 has been replaced by nn1986, a standard, two-layer, dense nn configured as a binary classifier and (mis)used in that capacity. Note: total number of parameters is unchanged. HARK: this new nn exposes a bug somewhere in ctak. Run ctlm with self-play to see the completely borked board state at the end.
42 hoursCorrected generation of training data for 6stslil clingman
42 hoursDon't generate header for training data + tweakstslil
For some reason it would seem that moving flats to a lower value and increasing the proximity between caps and top flats improves acquisition. Still not great, but every bit counts.
42 hoursChange the training data generation a littletslil clingman
Although it pains me to say it, ``label smoothing'' appears to be actually work. I'm also currently experimenting with training simply against _all_ games, instead of only bot matches. Once the training finishes i'll pit cttei against itself with old and new weights, hopefully there'll be a noticeable improvement.
42 hoursTEI interface working!tslil clingman
42 hoursTried some naive iterative deepening. Work on TEI interface nexttslil clingman
If TEI is implemented, then i could make use of Morten's racetrack (https://github.com/MortenLohne/racetrack) and develop a quantitative measure of the bot's performance. This is the current priority.
42 hoursJust some #weightgoals ;)tslil clingman
It turns out that while i was training on a 0/1 classification problem, i was using 2*eval - 1. Training using this function instead, and on bot-dominated game choices (chosen_player in extract.sh) seems to have given a better evaluation function. At the least, Morten's swindle doesn't work anymore.
42 hoursFairly important bug fixes to lcdlib, LCD now echoes input!tslil clingman
Input polling without line-buffering is done using ncurses, so the buildroot configuration had to change accordingly to include that library. The Makefile changed to accommodate stand-alone building of ct1986 and to include -lcurses where appropriate. There were also some typos about copying ct1986 and ctaklm to the correct directories.
42 hoursSyntax errors, small tweak to training data generationtslil clingman
42 hoursCleaned up build systemtslil clingman
42 hoursBusybox is irritatingtslil clingman
42 hoursBusybox needs LFS to buildtslil clingman
42 hoursCleaning up busyboxtslil clingman
42 hoursAuto-start the gametslil clingman
42 hoursWorking on better output + build system refinementtslil clingman
42 hoursInfrastructure more or less set up!tslil clingman
It remains to tweak ct1986.c and add a .login file to autorun stuff!