Grandmaster level chess for a computer is a massive, massive regression. Big whoop.
Grandmaster-Level Chess Without Search
101–110 of 133 posts
Re: Grandmaster-Level Chess Without Search
#102Given that they used position evaluation from (a search chess engine[1]) Stockfish, how is this "without search"? Edit: looking further than the abstract, this is rather an exploration of scale necessary for a strong engine. Could go without "without search" in the title I guess. [1]: IIRC, it also uses a Leela-inspired NN for evaluation.
Does Stockfish really use a Leela-inspired NN? I thought the NNUE was independently developed and completely different (it's a very tiny network that runs on the CPU).
Yeah, NNUE is a separate invention that unfortunately, Deepmind often get undeserved credit for inspiring. It didn't even originate in chess engines but a shogi version of Stockfish. Architecture is completely different from the nets in Leela or Alpha Zero.
Re: Grandmaster-Level Chess Without Search
#103How much of this "grandmaster-level" play is an artifact of low time controls? I notice they only achieve GM ELO in Blitz against humans, achieve significantly worse ELO against bots, and do not provide the "Lichess Blitz ELO" of any of their benchmark approaches.
I wonder if one could make a neural net play human-like, at various levels, by for instance training smaller or larger nets. And by human-like, I don't mean ELO level, but more like the Turing tests - "does this feel like playing against a human?" I wonder how many time-annotated chess play logs are out there. (Between humans, I mean.)
This was studied with the 'Maia' project. See:
Re: Grandmaster-Level Chess Without Search
#104While its performance against humans is very impressive indeed, its performance against engines is somewhat less so: > Our agent’s aggressive style is highly successful against human opponents and achieves a grandmasterlevel Lichess Elo of 2895. However, we ran another instance of the bot and allowed other engines to play it. Its estimated Elo was far lower, i.e., 2299. Its aggressive playing style does not work as w…
This sounds a lot like Mikhail Tal!
Not really. Mikhail Tal was easily one of the strongest calculators in chess history. Definitely the strongest in his time besides maybe Fischer.
The idea that Tal mostly made dubious sacrifices is largely a myth heavily based in a joke he himself made. In actual fact he always did deep calculation and knew that no easy refutation existed, and that he had a draw by perpetual check in hand(until beaten by Ding a few years ago, Tal actually had the record streak of unbeaten games in classical chess). He was making calculated risks knowing his opponents would not be likely to outcalculate him. He also had a very deep understanding of positional play, he just had a very different style of expressing it, relying more on positional knowledge to create sharp positions centered around material imbalance.
Re: Grandmaster-Level Chess Without Search
#105Earlier quoted context omitted.
In one sense, I can understand why they would choose to use Stockfish in mate-in-N positions. The fact that the model can't distinguish between mate in 5 and mate in 3 is an implementation detail. Since the vast majority of positions are not known to be wins or draws, it's still an interesting finding. However, in reality all positions are actually wins (for black or white) or draws. One reason they gave for why stoc…
Is this in comparison to some other evaluation function which is perfect? I agree that all positions should have a certainty of win, draw, or lose with perfect play, but no engine is close to that level of evaluation function. I do suspect that this pathological behavior could be trained out with additional fine tuning, but likely not without slightly diminishing the model's overall ability.
It comes down to: What is the evaluation for? For a human using an engine to analyze, it is about getting to more win-likely positions. And for an engine, it really is the same; plus to guide the search. Having a perfect trinary win/draw/loss would certainly be the _truth_ about a position in some objective way, but it would almost certainly not be the optimal way to win chess games against a set opponent. 1. e4 and 1. h3 are almost certainly both draws with perfect play from both sides, but the former is much more likely to net a win, especially for a human using the engine.
Re: Grandmaster-Level Chess Without Search
#106They do use Stockfish for playing thought … “To prevent some of these situations, we check whether the predicted scores for all top five moves lie above a win percentage of 99% and double-check this condition with Stockfish, and if so, use Stockfish’s top move (out of these) to have consistency in strategy across time-steps.”
But only to complete a winning position.
That's a crucial part of chess that can't simply be swept under the rug. If I had won all the winning positions I've had over the years I'd be hundreds of points higher rated.
What if a human only used Stockfish in winning positions? Is it cheating? Obviously it is.
Re: Grandmaster-Level Chess Without Search
#107Earlier quoted context omitted.
That 'only' usage in the winning position could be a decisive for gaining GM rating.
Positions with 99% win percentage are not decisive for GM vs non-GM rating.
From the paper:
If Stockfish detects a mate-in-k (e.g., 3 or 5) it outputs k and not a centipawn score. We map all such outputs to the maximal value bin (i.e., a win percentage of 100%). Similarly, in a very strong position, several actions may end up in the maximum value bin. Thus, across time-steps this can lead to our agent playing somewhat randomly, rather than committing to one plan that finishes the game quickly (the agent has no knowledge of its past moves). This creates the paradoxical situation that our bot, despite being in a position of overwhelming win percentage, fails to take the (virtually) guaranteed win and might draw or even end up losing since small chances of a mistake accumulate with longer games (see Figure 4). To prevent some of these situations, we check whether the predicted scores for all top five moves lie above a win percentage of 99% and double-check this condition with Stockfish, and if so, use Stockfish’s top move (out of these) to have consistency in strategy across time-steps.
So they freely admit that their thing will draw or even lose in these positions. It's not merely making the win a little cleaner.
Re: Grandmaster-Level Chess Without Search
#108There is rampant misunderstanding of some parts of this article; allow me to help :) The "no-search" chess engine uses search (Stockfish) in in two ways: 1. To score positions in the training data. This is only training data, no search is performed when actually playing. 2. To play moves when the position has many options with a 99% win rate. This is to prevent pathological behavior in already won positions, and is n…
Sort of but it seems a bit of a cheat. Neural networks are universal approximators. Choose a function and get enough data from it and you can approximate it very closely and maybe exactly. If initially creating function F required algorithm Y ("search" or whatever), you can do your approximation to F and then say "Look F without Y" and for all we know, the approximation might be doing things internally that are actua…
The state space of chess is so huge that even a giant training set would be a _very_ sparse sample of the stockfish-computed value function.
So the network still needs to do some impressive generalization in order to „interpolate“ between those samples.
I think so, anyway (didn‘t read the paper but worked on alphazero-like algorithms for a few years)
Re: Grandmaster-Level Chess Without Search
#109Earlier quoted context omitted.
Does Stockfish really use a Leela-inspired NN? I thought the NNUE was independently developed and completely different (it's a very tiny network that runs on the CPU).
Yeah, NNUE is a separate invention that unfortunately, Deepmind often get undeserved credit for inspiring. It didn't even originate in chess engines but a shogi version of Stockfish. Architecture is completely different from the nets in Leela or Alpha Zero.
Wait, so progress on Stockfish would happen regardless of Alpha Chess? I always thought they were inspired by it in the newer versions, and got much improved rating from incorporating it.
Re: Grandmaster-Level Chess Without Search
#110270M parameters at I guess FP/BF16?
I'd be interested to see how well the ELO holds up when the model is quantized.
At INT8 a small transformer like this could have a pretty amazing speed and efficiency on an Edge TPU or other very low power accelerator chip. The question becomes then is it faster / more efficient than Stockfish 16 on a similarly powered CPU. As we've seen with LLM's, they can be extremely speedy when quantized and all the stops pulled out on hardware to efficiently infer them compared to the raw FP16 and naive implementations.