4 ms·
I wasn't able to find what time setting the AI was trained on, but I'm a 1400 bullet player and at that level it is uncommon to resign even if you are down a mi
by opportune 6y ago
I wasn't able to find what time setting the AI was trained on, but I'm a 1400 bullet player and at that level it is uncommon to resign even if you are down a minor piece and a pawn (or more, but in a good attacking position). The probability of being able to win due to time/a blunder is quite high.
I even saw an IM vs. NM bullet game the other day where the NM was in a losing position but stayed in to grab a stalemate: https://www.reddit.com/r/chess/comments/kwoikt/im_not_a_gm_levy_rozman_swindles_a_stalemate_from/ https://www.reddit.com/r/chess/comments/kwoikt/im_not_a_gm_l.... Not sure if Levy was being unsportsmanlike to stay in the game despite being in a losing position, but even at a high level I think it's normal to play to the end if your opponent is in time trouble.
- reidmcy 6y agoThey're trained on everything but Bullet/HyperBullet. The neural network just predicts moves and win probabilities so we don't have a way (yet) of making it concede.
- gamegoblin 6y agoIs there a way to treat resignation as a "move"? Even though the win probability is zero by definition, it still may be the most accurate move prediction in certain scenarios.
- reidmcy 6y agoYes, the output is just a large vector with each dimension mapping to a move. But we'd probably do it as different "head" so have a small set of layers that are trained just to predict resignations. Both options would break the lc0 chess engine we use for stuff like the Lichess bots though.
- alisonkisk 6y agoIt's never unsporting to play on in a bullet game since it's so short, unless it's a long drawn out stall that isn't making any progress. The winning player can quickly finish the game if it's a clear lost cause.