[Computer-go] Facebook Go AI.

[Hiroshi Yamashita]

Hi,

Thank you for the paper.
Not only next move, but also opponent move and next counter move
 prediction is very interesting.

I have two questions.

darkforest : standard features, 1 step prediction on KGS dataset
darkfores1 : extended features, 3 step prediction on GoGoD dataset
darkfores2 : fine-tuned the learning rate, Based on darkfores1

1. How did you tune learning rate in darkfores2?

2. darkfores1 is stronger than darkforest. Is it because of 3 step
 prediction or using GoGoD? Do you have a result using
 "standard features, 1 step prediction on GoGoD"?

Regards,
Hiroshi Yamashita

----- Original Message ----- 
From: "Yuandong Tian" <yuandong.tian at gmail.com>
To: <computer-go at computer-go.org>
Sent: Wednesday, November 25, 2015 5:45 AM
Subject: Re: [Computer-go] Facebook Go AI.


> Hi all,
> 
> I am the first author of Facebook Go AI. Thanks for your interest! This is
> the first time I post a message here, so please forgive me if I mess up
> with anything.
> 
> 1. The estimation of 1d-2d is based on the win rate of free game in the
> last 3 months (since darkforest launched in Aug). See Table 6 in the paper.
> For ranked game, its rank is definitely lower since people tend to play
> more seriously. It seems that now darkforest is 1k and darkfores1 is 1d.
> 
> 2. Here is the Pachi 10k command line for no pondering.
> pachi -t =10000 threads=8,pondering=0
> 
> For pondering, it is simply
> pachi -t =10000 threads=8
> 
> In both cases, all the spatial patterns are properly loaded. See the
> following GTP response:
> W>> protocol_version
> Random seed: 1448000132
> Loaded spatial dictionary of 1064482 patterns.
> Loaded 3021829 pattern-probability pairs.
> 
> 3. We use pachi version 11.99 as shown in the following GTP response:
> W>> version
> W<< = 11.99 (Genjo-devel): If you believe you have won but I am still
> playing, please help me understand by capturing all dead stones. Anyone can
> send me 'winrate' in private chat to get my assessment of the position.
> Have a nice game!
> 
> 4. Darkfores2 is still DCNN model and no search is involved.
> 
> Thanks! If you have any comments, please let me know.
> 
> ----------------------------
> Yuandong Tian
> Research Scientist,
> Facebook Artificial Intelligence Research (FAIR)
> Website:
> https://research.facebook.com/researchers/1517678171821436/yuandong-tian/
>


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