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24

The answer is "No". If you have a defined fixed set of resources - CPUs, memory, cache, etc. - and you allow one engine to have full use of them then that engine is going to be able to analyse to a greater depth than if you take the same set of resources and split them in some way between several different engines. Inevitably the single engine ...


16

No, an ensemble of chess engines won't beat the best one. The reason is simply because of hardware. Let's take the strongest CPU engines right now to keep things simple. These are Stockfish, Komodo, Leela-CPU, Ethereal, Fire, and rofChade. Stockfish is the strongest. You have a four-core computer, running Stockfish. It's expected to beat all the other ...


16

You can't really objectively answer this question, but I'll share my view. One of the important factors to take into account is that Leela Chess Zero project requires tremendous computational resources to complete. The way project attains those resources is by convincing large number of people to donate part of their machine time to that project. To make ...


14

Well, it is a small sample, but assuming that there are a lot more games like these, I think it could be the following things. First, I am not sure when we first humans first decided that space was an advantage, but for as long as I have been playing, it has been a known factor. Both of these openings cede space compared to double-king-pawn openings and ...


11

Generally speaking, Leela tends to have a better "intuition" and Stockfish is very good at brute force calculations. So in a structure like the French/Caro-Kann, where calculation becomes less important and strategy becomes more important, Leela will tend to do better.


11

Because of the enormous skill difference between these computers and humans, any kind of analysis will inevitably be post-hoc. We can tell ourselves stories about how "Stockfish should have [insert plan]," (and I'm sure some people here will) but ultimately I think that any story we could come up with would be flawed at the level of Leela/Stockfish. This isn'...


11

Leela works by performing an exceptionally sophisticated positional evaluation at a relatively shallow search depth, whereas most chess engines work by performing a simple evaluation at as deep a search as possible. In theory this should produce a more positional style of play, and it does seem to be an effective strategy versus today's best conventional ...


10

Though I am not able to test it myself, I am confident of the following conclusion: An ensemble of engines should be able to beat the strongest individual engine Here are my key assumptions: Given typical time controls used for benchmarks, the time 'lost' by having a thin pre-evaluator before the engines would be negligible. As such we can say that the ...


9

Leela is special because it's the first strong open-source deep-learning engine. Defeating Stockfish (and also Komodo and Houdini) convincingly on all settings is a very significant milestone, practically more important than Google's AlphaZero. Google's system is inaccessible to anyone but themself. Human-understandable evaluation function has always been ...


9

In short, because DeepMind has TPUs. Lots and lots of TPUs. By far, the most time-consuming part of the training process is generating self-play games. DeepMind used 5000 TPUs to generate self-play games, which is a lot of processing power. Meanwhile, Lc0 crowdsources processing power from volunteer clients, which is much slower. From the DeepMind paper ...


8

Not an expert but you can play against a "virgin" Leela by using one of the younger nets. For example in the first Leela test (the so-called training run) the strongest net was 11248. If you play against, e.g., net 00010, it'll be much weaker. However, you can't train Leela by playing against it. You can play against the trained product, but you can't train ...


7

The answer is more complicated than you want to try to make it. Any definitive "yes" or "no" answer begs the questions of the conditions of the match, the hardware used, and the difference in strength of the players involved. Instead of answering your question directly, here I plan to go through the thought processes needed which guide ...


6

Nope, at some point a legal move is selected as best move. Who ever makes that decision can't be better than the best engine. Otherwise there is a new best engine.


6

Python utilities for experimenting with Leela Chess Zero a neural network based chess engine: https://github.com/glinscott/leela-chess/ Here: https://github.com/so-much-meta/lczero_tools This allows you to run the network in Python on specific board positions via python-chess, and get policy/value outputs. (Works with pytorch, and is also able to run the ...


6

Can't comment on hardware but will say something about Leela's strengths and weaknesses - If you look through the games from the TCEC superfinal, sometimes Leela is brilliant. For example in this position from game 61: [fen "r1bbnr2/pp1n1q1k/3p4/2pPp1pP/2P1PpP1/2NQ1N2/PP2BB2/2KR2R1 w - - 10 26"] Stockfish (White) evaluated this as +0.63, while Leela was ...


6

Lc0 is fully compatible with UCI. It's strength depends a ton on what hardware it's being run on. On any hardware (tested down to Raspberry Pi), it will be superhuman (over 2900 elo). With a RTX 2060 ($200ish) it should be roughly even with SF on 8 cores (although you may need to mess with settings a bit to get it there). A 2080ti puts decently (20 or so elo)...


6

This is happening because AlphaZero and Leela aren't playing against the same Stockfish. If you read the paper, AlphaZero beat Stockfish 8 (it also played a series against Stockfish 9 - same logic applies however). Both these versions of Stockfish are old, and significantly inferior to the latest version of Stockfish. AlphaZero beat Stockfish 8 by +155 -6 =...


4

Anytime a group of people get extremely hyped about something (and especially when they aggressively bash alternatives), there's a good chance this is just human tribalism at work. Leela may become extremely strong in the near future, but to say with 100% certainty this will happen now is naive. People also like change. Stockfish is a revolutionary engine (...


4

The bigger weights file corresponds to a larger Neural Network, which means more computation per node, but better evaluation per node.This is expected, and there is nothing that can make a bigger NN as fast as a smaller NN. The best solution is to use a small NN for blitz time control. I would personally recommend LD2 (available at Lc0.org/LD2)


4

The biggest things that stand out here is the power supply and hard drive. For the first, getting a cheap power supply tends to be a bad idea since if it breaks, it can bring down a lot of other stuff with it. 650W is plenty, but I'd recommend going with a more established brand like corsair or silverstone. For the hard drive, given that you can get a 1TB ...


4

Yes, you could in principle set up Leela such that it learns by playing against you. It would require some programming skills and a lot of time to play games. Currently Leela has been trained on 300.000.000 games. You should expect to have to play at least a couple of thousand games against it to see an improvement. Also, Leela doesn't learn anything if ...


4

Currently, it's Stockfish: in the latest FRC exhibition (November 2020) Stockfish beat Leela +8 -0 =42.


4

For early versions, the lczero project's download page refers you to the lc0 releases available on GitHub. For versions from 2018, you can go the lczero repository on GitHub. Note that while the downloads from from the former repository (lc0) provide both Windows builds and source code, the older releases from 2018 (lczero) give you only source code that you ...


3

Yes If the engines are learning engines, rather than stateless deterministic evaluators, then I think it is obvious that an ensemble would be stronger, for the same reason that I think a team of human chess players will, on average, beat all of the individuals in the team in a matchup. The hard part is deciding which move to use when multiple engines ...


3

This seems to be somehow LeelaFish's approach: https://github.com/killerducky/lc0/wiki/LeelaFish More about it here (and probably on more posts in the same forum): http://www.talkchess.com/forum3/viewtopic.php?t=70803&start=10


3

As you noted, w_i is not calculated by the search tree. It is simply the number of wins out of the total simulations performed at that node (if this is the method used to score the node). This scoring mechanism is also known as playout.


3

The weights for main networks are here. The best weights depends on whether you are using a cpu or gpu. For cpu, the best weights file is probably LD2 which is a small net trained off of data for t40. For strong gpus or longer searches, one of the recent t40 networks will be very strong.


2

After asking on the Discord as @Oscar Smith suggested in a comment, I got some results. The person I asked said that you could download good weight files for Leela from this webpage: http://lczero.org/networks/ This was also said: "nT40.T8.610 (used in TCEC Sufi): https://www.dropbox.com/s/rmcf0lf1hes10gi/256x20.T8-swa-610000?dl=0 and currently in use in ...


2

Part of this can be accomplished with Chessbase GUI. There is an option called cloud analysis. It is thougt to use engines in the cloud additional to your own engine. It ever could be used with two local engines, one determining the 1-n main variants, the other to evaluate the variants. A third engine could make proposals for answers to the main moves and so ...


2

As far as I can see Leelenstein is mostly derivative of Leela. It uses a fraction of the games produced by Leela's self-play to get to a similar playing strength. Given that most of these games have also been used to train Leela, there is little reason to expect Leelenstein to be better. Basically Leela produces customized trainingsdata via self-play, ...


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