Google's AlphaGo team has been working on chess

[Jesse Gersenson]

I am trying to train Giraffe exactly how it is described here.

But it crashes,... [snip]

Anyone ever tried the training?

Matthew mentioned crashes, training and Windows here:
http://www.talkchess.com/forum/viewtopic.php?t=61808

However, calling Torch through the Lua interpreter during play is way too slow, so I wrote partial (evaluation only, no training support) Eigen implementations of the Torch modules I use. That means if you are building Giraffe yourself, unless you want to train the net, there's no dependency on Torch. This also means training on Windows is now totally impossible.

[petero2]

That is a start for sure -- proving a NN evaluation could be competive or even much better than a hand crafted evaluation function. The latency of evaluating the NN can be countered with a combination hardware (GPU/TPU) and software (async evaluations) which is what Google did for AlphaGo. Giraffe used only three layers of NN with chess specific inputs such as attack maps while AlphaZero used many more layers of CNN with just the rules of the game as input. Texel actually replaced its evaluation function with Giraffe's NN and showed that the eval is actually better but it would need a time odds to be competitive on the same hardware.

Statements like these could make me a believer.

The post describing this test is here.

Nice idea, a few points.

I tried the STS test and saw hardly any similarity between Giraffe (2016) and Texel GI. And so I ran the good old similarity test.

Code: Select all

Positions     8238                       Gira  Texe
{Giraffe w64 (time: 100 ms  scale: 1.0)} ----- 4.72
{Texel Gi    (time: 100 ms  scale: 1.0)} 4.72 -----

Only 4% where 65+% was to be expected?

Never seen such a low percentage, running it now at 1 second.

Last, I started a match, TC=40/60, I stopped after 40 games, 37.5 - 2.5 in favor of Texel GI while NPS favored Giraffe (2016) with approx. 20-25%.

------

Unless I have done something wrong I don't see how one can conclude the NN is on par with SF or your evaluation.

Giraffe contains a non-standard search that is quite weak and sometimes causes huge blunders to be played. For example, in the following position giraffe calculated for 3.1 seconds to depth 15 and played Ba6??, dropping a bishop for no compensation, due to a 1-ply tactical "combination".
[D]3r3k/1b3pbp/1p5n/2p1p2p/4PP2/2P2KP1/R3NN1P/1B6 b - - 1 30

For this reason I did not use giraffe to make my conclusions, I compared "texel gi" with "standard texel", so giraffe's search code was not involved at all.

Also, I did not conclude giraffe evaluation was "on par" with SF or texel evaluation, I only concluded that if it had been 10x faster it would have caused texel to be around 100 elo stronger than texel using its own evaluation. I guessed that this would have been roughly equal to SF evaluation.

[Rebel]

I am trying to train Giraffe exactly how it is described here.

But it crashes,... [snip]

Anyone ever tried the training?

Matthew mentioned crashes, training and Windows here:
http://www.talkchess.com/forum/viewtopic.php?t=61808

However, calling Torch through the Lua interpreter during play is way too slow, so I wrote partial (evaluation only, no training support) Eigen implementations of the Torch modules I use. That means if you are building Giraffe yourself, unless you want to train the net, there's no dependency on Torch. This also means training on Windows is now totally impossible.

What a pity. I may assume to see new engines with this option soon.

[Joost Buijs]

I am trying to train Giraffe exactly how it is described here.

But it crashes,... [snip]

Anyone ever tried the training?

Matthew mentioned crashes, training and Windows here:
http://www.talkchess.com/forum/viewtopic.php?t=61808

However, calling Torch through the Lua interpreter during play is way too slow, so I wrote partial (evaluation only, no training support) Eigen implementations of the Torch modules I use. That means if you are building Giraffe yourself, unless you want to train the net, there's no dependency on Torch. This also means training on Windows is now totally impossible.

What a pity. I may assume to see new engines with this option soon.

There seem to be people who have made native builds of 'torch' under Windows: https://github.com/torch/torch7/wiki/Wi ... -downloads

As usual the same old portability problem with programs depending too much on 3th party libraries, thats why I always try to avoid using 3th party libs as the plague.