So, how many of you are working on neural networks for chess?

[smatovic]

It seems to me, that the whole CCC forum is waiting for LC0 to pass Stockfish finally,
so how many of you programmers are working on neural networks for chess?

Myself still ponders on how to combine an AlphaBeta searcher with gpgpu ann eval...

--
Srdja

[Robert Pope]

I have to wait until I can get a new computer first. But, hopefully this summer.

[AlvaroBegue]

Myself still ponders on how to combine an AlphaBeta searcher with gpgpu ann eval...

I have a promising idea for that, but I don't really have the time to implement it. My job, my wife and my kids are getting in the way of the really important stuff!

[Daniel Shawul]

Myself still ponders on how to combine an AlphaBeta searcher with gpgpu ann eval...

I have a promising idea for that, but I don't really have the time to implement it. My job, my wife and my kids are getting in the way of the really important stuff!

Watch it you don't who might be surfing the web

[jorose]

One of the main reasons I am not working on an NN based engine is that I feel I don't have the resources. I think very few people have the resources to seriously train and test a NN based engine.
Reinforcement learning based NN engines are even worse in that regard.

I don't understand how it matters whether Leela or SF is stonger. Depends on the conditions anyways.

[jdart]

I think still NN engines even on higher-end commercial graphics cards play blunders at a pretty high rate.

I think there is probably room for a hybrid approach where maybe the NN is suggesting moves to a deep searcher, but I am not aware of anyone pursuing that.

Personally I have a pretty long to-do list for my non-NN engine and I am not planning to drop everything and start building a NN.

--Jon

[brianr]

One of the main reasons I am not working on an NN based engine is that I feel I don't have the resources. I think very few people have the resources to seriously train and test a NN based engine.
Reinforcement learning based NN engines are even worse in that regard.

I don't understand how it matters whether Leela or SF is stonger. Depends on the conditions anyways.

My resources include a 2 year-old GTX 1070 GPU. With that I was able to train (supervised learning) a 10x128 Leela net from the "standard CCRL" dataset (link below). It took about a week, and it is competitive with Crafty on between 2 and 4 CPUs, so about 2,900 Elo. It is not as serious as the larger Leela project, but has been quite rewarding learning enough to do it.

http://blog.lczero.org/2018/09/a-standard-dataset.html

[Daniel Shawul]

I think still NN engines even on higher-end commercial graphics cards play blunders at a pretty high rate.

I think there is probably room for a hybrid approach where maybe the NN is suggesting moves to a deep searcher, but I am not aware of anyone pursuing that.

Personally I have a pretty long to-do list for my non-NN engine and I am not planning to drop everything and start building a NN.

--Jon

My NN engine never makes a blunder because I spend 20% of the time doing a mulitpv search calculating scores for root moves,
and then combining that with MCTS scores like: 0.2 * ABscore + 0.8 * MCTSscore. That way the selection of moves at the root is biased
by the alphabeta prior score and that makes it avoid almost all blunders.

[Henk]

NN = far too slow = black box = useless

[jorose]

I think still NN engines even on higher-end commercial graphics cards play blunders at a pretty high rate.

I think there is probably room for a hybrid approach where maybe the NN is suggesting moves to a deep searcher, but I am not aware of anyone pursuing that.

Personally I have a pretty long to-do list for my non-NN engine and I am not planning to drop everything and start building a NN.

--Jon

My NN engine never makes a blunder because I spend 20% of the time doing a mulitpv search calculating scores for root moves,
and then combining that with MCTS scores like: 0.2 * ABscore + 0.8 * MCTSscore. That way the selection of moves at the root is biased
by the alphabeta prior score and that makes it avoid almost all blunders.

How is ScorpioNN coming along?