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Grandmaster-Level Chess Without Search

arxiv.org

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Re: Grandmaster-Level Chess Without Search

#121

Post by paulddraper »

mtlmtlmtlmtl wrote: post #107
paulddraper wrote: post #17

Earlier quoted context omitted.

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 quickl…

> So they freely admit that their thing will draw or even lose in these positions.

Yeah, they didn't use Stockfish for the lols.

They create a search-less engine for chess. And then used a search engine to pay a small minority of the game.

Re: Grandmaster-Level Chess Without Search

#122

Post by im3w1l »

dmurray wrote: post #113
zniturah wrote: post #25

Earlier quoted context omitted.

"Aready won position" or "99% win rate" is statistics given by Stockfish (or professional chess player). It is weird to assume that the same statement is true for the trained LLM since we are assessing the LLM itself. If it is using during the game then it is searching, thus the title doesn't reflect the actual work.

It's quite clear from the article that the 99% is the model's predicted win rate for a position, not its evaluation by Stockfish (which doesn't return evaluations in those terms). It's true that this is a relatively large deficiency in practice: how strong would a player be if he played the middlegame at grandmaster strength but couldn't reliably mate with king and rook? The authors overcame the practical problem by…

Human players have this concept of progress. I couldn't give a good succinct description of exactly what that entails, but basically if you are trading off pieces that's progress, if your king is breaking through the defensive formation of the pawn endgame that's progress. If you are pushing your passed pawn up the board that's progress. If you are slowly constricting the other king that's progress.

When we have a won position we want to progress and convert it to an actual win.

I think the operational definition I would use for progress is a prediction of how many more moves the game will last. A neural network can be used for that.

Re: Grandmaster-Level Chess Without Search

#123

Post by paulddraper »

mtlmtlmtlmtl wrote: post #106
paulddraper wrote: post #7

Earlier quoted context omitted.

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.

> That's a crucial part of chess that can't simply be swept under the rug.

Grandmasters very literally do it all the time.

> What if a human only used Stockfish in winning positions? Is it cheating? Obviously it is.

Yes, but this isn't that.

This is a computer that is playing chess. And FYI (usually) without search.

Re: Grandmaster-Level Chess Without Search

#124

Post by bjourne »

verteu wrote: post #80

How 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.

All of it? Inference speed is proportional to the number of parameters which can't vary depending on the time control. For longer time controls you'd need a larger network. For those who don't know chess, the quality of high-level play in five-minutes-each games is extremely much lower than in 90-minutes-each games.

Re: Grandmaster-Level Chess Without Search

#125

Post by im3w1l »

paradite wrote: post #99

Nice. I build AI-driven puzzle games where you can pick algorithms, tune parameters, or train ML models to play the game. Chess is on my priority list for the next game. Now I know that ML strategy is on par with search algorithms.

> I know that ML strategy is on par with search algorithms

It's on par with very strong humans, but not as good as a normal engine.

Re: Grandmaster-Level Chess Without Search

#126

Post by QuantumGood »

dayjaby wrote: post #33
IIAOPSW wrote: post #26

Slightly off topic but am I the only one that approaches strategy games by making a "zeroth order approximation". Eg find the shortest path to victory under the (obviously faulty) assumption that my opponent does nothing and the board is unchanging except for my moves. Now find my opponents shortest path to victory under the same assumption. Then evaluate, if we both just ignore each other and try to bum rush the vic…

On beginner level this might work, but if people are more competitive they begin to realize the benefit of not only playing the own game, but reading the enemies plan (e.g. scouting in Starcraft/AoE2) to counteract it as much as possible. Chess against humen is different. Usually, there is no path to victory, only to remis. People just follow strategic plans that people told them would be slightly beneficial later on…

Common advice to beginners:

"Improve the position of your worst placed piece."

For better players, determine which is most effective:

1 Improve the position of your worst placed piece.

2 Exchange or minimize the potential of your opponent's best-placed piece (e.g. trade off their bishop on a long diagonal)

3 Maximize the potential of your best-placed piece (sometimes by a sacrifice)

4 Prevent your opponent from developing some pieces

This is over-simplified, of course, but the balance of the position must be taken into account.

Re: Grandmaster-Level Chess Without Search

#127

Post by janalsncm »

actionfromafar wrote: post #97
verteu wrote: post #80

How 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.)

Maia chess did this. It works ok for low to mid elo levels (around 50% accuracy). But their project also didn’t use any search, it just directly predicted the move. Humans actually do perform search, so a more accurate model at higher elos will probably need to do something like that. However, humans don’t do a complete game search like stockfish, and we don’t do full game rollouts like lc0 either.

Re: Grandmaster-Level Chess Without Search

#128

Post by janalsncm »

dawnofdusk wrote: post #48
janalsncm wrote: post #38

Earlier quoted context omitted.

We don’t know if it’s using implicit search either. While it would be interesting if the network was doing some internal search, it’s also possible it has just memorized the evaluations from 10M games and is performing some function of the similarity of the input to those previously seen.

Even if it's "implicit" I'm not sure if that matters that much. The point is that the model doesn't explicitly search anything, it just applies the learned transformation. If the weights of the learned transformation encode a sort of precomputed search and interpolation over the dataset, from an algorithmic perspective this still isn't search (it doesn't enumerate board states or state-action transitions). >performin…

I agree, from a practical perspective what matters is that is distilling stockfish’s search to a certain extent, which could have computational efficiencies. “Without search” just means we’re not doing anything like minimax or MCTS.

Re: Grandmaster-Level Chess Without Search

#129

Post by mtlmtlmtlmtl »

paulddraper wrote: post #121
mtlmtlmtlmtl wrote: post #107

Earlier quoted context omitted.

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 quickl…

> So they freely admit that their thing will draw or even lose in these positions. Yeah, they didn't use Stockfish for the lols. They create a search-less engine for chess. And then used a search engine to pay a small minority of the game.

Yes. So how is this irrelevant for qualifying as GM-level play then? Being able to play these positions is a clear prerequisite for even being in the ballpark of GM strength. If you regularly choke in completely winning endgames, you'll never get there.

This is cheating, plain and simple. It would never fly in human play or competitive computer play. And it's most definitely disingenuous research. They made an engine, it plays a certain level, and then they augment it with preexisting software they didn't even write themselves to beef up their claims about it.

Re: Grandmaster-Level Chess Without Search

#130

Post by YeGoblynQueenne »

Lerc wrote: post #67
YeGoblynQueenne wrote: post #51

Earlier quoted context omitted.

>> 1. To score positions in the training data. This is only training data, no search is performed when actually playing. That's like saying you can have eggs without chickens, because when you make an omelette you don't add chickens. It's completely meaningless and a big fat lie to boot. The truth is that the system created by DeepMind consists of two components: a search-based system used to annotate a dataset of mo…

It doesn't matter where the egg came from, just that it is an egg. It could have luckily coalesced from gas (a Boltzmann egg), or perhaps even more radically, been laid by a duck. you say >They didn't train their system by self-play and they certainly didn't hire an army of low-paid workers to annotate moves for them. So you are certainly aware that there are avenues to creating the data set. Given that, it is quite…

>> So you are certainly aware that there are avenues to creating the data set. Given that, it is quite reasonable to say that search is unnecessary.

How is it unnecessary? They used none of those methods, so they had to use search. That is search being necessary, not the opposite.

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