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They built a dumber clone of Stockfish, and they call it ‘zero’ for some reason. What is the meaning behind ‘zero’ anyways? It used to refer to zero-shot, but now it seems like it’s just a marketing term.
Earlier quoted context omitted.
I built something like this. It works as long as you're not too high-rated: chessmate.ai. Once players get higher rated it is more difficult to predict their moves because you need to model their search process, not just their intuitive move choice. It's also possible to train on one player's games only so that it is more personalized. It uses a similar approach to Maia but with a different neural network, so it had…
Really nice work! The tabs other than "play" don't seem to be working, but I was able to try some novelty openings and it certainly felt like it was responding with human moves. It would be great to have the ability to go back/forth moves to try out different variations. I'm curious how you combined Stockfish with your own model - but no worries if you're keeping the secret sauce a secret. All the best to you in buil…
Since the whole thing is executed in the browser (including the model) there aren't a ton of secrets for me to keep. Essentially it is expectation maximization: the bot tries to find the move with the highest value. What is "value"? Essentially, it is the dot product between the probability distribution coming out of the model and the centipawn evaluations from Stockfish.
In other words if the model thinks you will blunder with high probability, it will try to steer you towards making that mistake.
They built a dumber clone of Stockfish, and they call it ‘zero’ for some reason. What is the meaning behind ‘zero’ anyways? It used to refer to zero-shot, but now it seems like it’s just a marketing term.
AlphaZero was the successor to AlphaGo. AZ was notable because unlike AG, it used zero human games to learn to play: it just played games against itself. Typically in “supervised” machine learning you take human data and train a model to imitate it. AZ used zero human data to learn.
Leela Chess Zero started out as an open source copy of AZ but it’s probably better than AZ now.
They built a dumber clone of Stockfish, and they call it ‘zero’ for some reason. What is the meaning behind ‘zero’ anyways? It used to refer to zero-shot, but now it seems like it’s just a marketing term.
What are some of the go-to books/articles for computer chess? I like the game and have a decent understanding of basics, so studying algorithms based on the game would be a good opportunity for me to learn conventional algos, but also RL/ML/MCTS etc. Also I wonder what is the go-to codebase these days?
You can also ask any noob questions on their Discords.
OT: what's the state of the art in non-GM level computer chess? Say I want to play chess with an opponent that is at about the same skill level as me, or perhaps I want to play with an opponent about 100 rating points above me for training. Most engines let you dumb them down by cutting search depth, but that usually doesn't work well. Sure, you end up beating them about half the time if you cut the search down enoug…
But the gigantic synthetic dataset that is used for training is created with plenty of traditional search. So it is all a bit silly but I guess cool none the less ...
I believe GM and chess author (and all-round lovely fellow) Matthew Sadler rigged up Leela Zero to effectively play off intuition and do very little or no search for training games. He could usually beat it, but not always. Think it might have been in The Silicon Road to Chess Improvement.
It's somewhat telling that they chose Stockfish as the oracle and not AlphaZero.