date:20151229

Re: [Computer-go] Computer-go Digest, Vol 71, Issue 22

2015-12-29 Thread Michael Alford


On 12/29/15 4:10 AM, amanda oregon wrote:



You can reach the person managing the list at
computer-go-ow...@computer-go.org



Is veg no longer the manager?

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Re: [Computer-go] Computer-go Digest, Vol 71, Issue 22

2015-12-29 Thread Petr Baudis

On Tue, Dec 29, 2015 at 08:59:52AM -0800, Michael Alford wrote:
> On 12/29/15 4:10 AM, amanda oregon wrote:
> 
> >
> >You can reach the person managing the list at
> >computer-go-ow...@computer-go.org
> >
> 
> Is veg no longer the manager?

He's the list owner and pays the bills for computer-go.org; I do most of
the day-to-day (well, month-to-month) administration and moderation.

Petr Baudis
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Re: [Computer-go] CNN with 54% prediction on KGS 6d+ data

2015-12-29 Thread Detlef Schmicker

-BEGIN PGP SIGNED MESSAGE-
Hash: SHA1

Hi,

I am fighting with the problem most seem to have with the strong move
predictions at the moment, MCTS is not increasing the players a lot :)

I wonder, if somebody measured the performance of the pure CNN54
against pachi 10k (or 100k), to get a comparison with the darkforest CNN.

It is not too much work, but you probably did it already.

Thanks,

Detlef

Am 21.12.2015 um 12:42 schrieb Hiroshi Yamashita:
> Hi Detlef,
> 
> Thank you for publishing your data and latest oakform code! It was
> very helpful for me.
> 
> I tried your 54% data with Aya.
> 
> Aya with Detlef54% vs Aya with Detlef44%, 1 playout/move Aya
> with Detlef54%'s winrate is 0.569 (124wins / 218games).
> 
> CGOS BayseElo rating Aya with Detlef44%  (aya786n_Detlef_10k) 3040 
> Aya with Detlef54%  (Aya786m_Det54_10k ) 3036 
> http://www.yss-aya.com/cgos/19x19/bayes.html
> 
> Detlef54% is a bit stronger in selfplay, but they are similar on
> CGOS. Maybe Detlef54%'s prediction is strong, and Aya's playout
> strength is not enough.
> 
> Speed for a position on GTS 450. Detlef54%   21ms Detlef44%   17ms
> 
> Cumulative accuracy from 1000 pro games.
> 
> move rank  AyaDetlef54%  Mixture 1  40.8  47.6
> 48.0 2  53.5  62.4 62.7 3  60.2  70.7 71.0 
> 4  64.8  75.8 76.1 5  68.1  79.5 79.9 6
> 71.0  82.3 82.6 7  73.2  84.5 84.8 8  75.2
> 86.3 86.6 9  76.9  87.8 88.1 10  78.3  89.0
> 89.3 11  79.6  90.2 90.6 12  80.8  91.2
> 91.4 13  81.9  92.0 92.2 14  82.9  92.7
> 92.9 15  83.8  93.3 93.5 16  84.6  93.9
> 94.1 17  85.4  94.3 94.5 18  86.1  94.8
> 95.0 19  86.8  95.2 95.4 20  87.4  95.5
> 95.7
> 
> Mixture is pretty same as Detlef54%. I changed learning method from
> MM to LFR. Aya's own accuracy is from LFR rank, not MM gamma. So
> comparison is difficult.
> 
> Cumulative accuracy Detlef44% 
> http://computer-go.org/pipermail/computer-go/2015-October/008031.html
>
>  Regards, Hiroshi Yamashita
> 
> 
> - Original Message - From: "Detlef Schmicker"
>  To:  Sent: Wednesday,
> December 09, 2015 12:13 AM Subject: [Computer-go] CNN with 54%
> prediction on KGS 6d+ data
> 
> 
>> -BEGIN PGP SIGNED MESSAGE- Hash: SHA1
>> 
>> Hi,
>> 
>> as somebody ask I will offer my actual CNN for testing.
>> 
>> It has 54% prediction on KGS 6d+ data (which I thought would be
>> state of the art when I started training, but it is not
>> anymore:).
>> 
>> it has: 1 2 3
>>> 4 libs playing color
>> 1 2 3
>>> 4 libs opponent color
>> Empty points last move second last move third last move forth
>> last move
>> 
>> input layers, and it is fully convolutional, so with just editing
>> the golast19.prototxt file you can use it for 13x13 as well, as I
>> did on last sunday. It was used in November tournament as well.
>> 
>> You can find it http://physik.de/CNNlast.tar.gz
>> 
>> 
>> 
>> If you try here some points I like to get discussion:
>> 
>> - - it seems to me, that the playouts get much more important
>> with such a strong move prediction. Often the move prediction
>> seems better the playouts (I use 8000 at the moment against pachi
>> 32000 with about 70% winrate on 19x19, but with an extremely
>> focused progressive widening (a=400, a=20 was usual).
>> 
>> - - live and death becomes worse. My interpretation is, that the
>> strong CNN does not play moves, which obviously do not help to
>> get a group life, but would help the playouts to recognize the
>> group is dead. (http://physik.de/example.sgf top black group was
>> with weaker move prediction read very dead, with good CNN it was
>> 30% alive or so :(
>> 
>> 
>> OK, hope you try it, as you know our engine oakfoam is open
>> source :) We just merged all the CNN stuff into the main branch! 
>> https://bitbucket.org/francoisvn/oakfoam/wiki/Home 
>> http://oakfoam.com
>> 
>> 
>> Do the very best with the CNN
>> 
>> Detlef
> 
> ___ Computer-go mailing
> list Computer-go@computer-go.org 
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Re: [Computer-go] Computer-go Digest, Vol 71, Issue 22

2015-12-29 Thread amanda oregon

 

On Tuesday, December 29, 2015 12:00 PM, 
"computer-go-requ...@computer-go.org"  
wrote:
 

 Send Computer-go mailing list submissions to
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To subscribe or unsubscribe via the World Wide Web, visit
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When replying, please edit your Subject line so it is more specific
than "Re: Contents of Computer-go digest..."


Today's Topics:

  1. Re: Those were the days ... (Ingo Althöfer)
  2. Re: Those were the days ... (Detlef Schmicker)


--

Message: 1
Date: Tue, 29 Dec 2015 11:20:46 +0100
From: "Ingo Althöfer" <3-hirn-ver...@gmx.de>
To: computer-go@computer-go.org
Subject: Re: [Computer-go] Those were the days ...
Message-ID:
    
    
Content-Type: text/plain; charset=UTF-8

Hello all,


> Martin understood computer go weaknesses, so he played to exploit them.  A 
> modern program 
> not specifically tuned for those weaknesses would have a much more difficult 
> time.

Agreed. Concerning CNN bots (like darkfores3), a natural way would be to find
some players of Martin's calibre who play hundreds of games against the old MFoG
at handicap 29. These games might become the training set for the CNN.

> I released version 10 in 1997, so it might be more accurate to play against 
> version 10 
> rather than against version 12 at 12 kyu level.  I probably still have a 
> version 10 CD somewhere.

I also still have one, I think.

Anyway, as soon as a serious contender shows up, I am willing to allow
a match environment that may - in case of disputes - be helpful for the bot. 

Ingo.

PS. I want to see my 1,000 Euros finding their way to a pocket of a
talented go programmer!


--

Message: 2
Date: Tue, 29 Dec 2015 13:00:33 +0100
From: Detlef Schmicker 
To: computer-go@computer-go.org
Subject: Re: [Computer-go] Those were the days ...
Message-ID: <568275e1.5070...@physik.de>
Content-Type: text/plain; charset=utf-8

-BEGIN PGP SIGNED MESSAGE-
Hash: SHA1

I gave pure DCNN 54% a try against the 15 kyu version:)

http://files.gokgs.com/games/2015/12/29/mfgo15kyu0-NiceGo19N.sgf

There was no pass handling, therefore filled an eye, without would
have been 133.5 loss or so :)

Detlef

Am 29.12.2015 um 11:20 schrieb "Ingo Althöfer":
> Hello all,
> 
> 
>> Martin understood computer go weaknesses, so he played to exploit
>> them.  A modern program not specifically tuned for those
>> weaknesses would have a much more difficult time.
> 
> Agreed. Concerning CNN bots (like darkfores3), a natural way would
> be to find some players of Martin's calibre who play hundreds of
> games against the old MFoG at handicap 29. These games might become
> the training set for the CNN.
> 
>> I released version 10 in 1997, so it might be more accurate to
>> play against version 10 rather than against version 12 at 12 kyu
>> level.  I probably still have a version 10 CD somewhere.
> 
> I also still have one, I think.
> 
> Anyway, as soon as a serious contender shows up, I am willing to
> allow a match environment that may - in case of disputes - be
> helpful for the bot.
> 
> Ingo.
> 
> PS. I want to see my 1,000 Euros finding their way to a pocket of
> a talented go programmer! 
> ___ Computer-go mailing
> list Computer-go@computer-go.org 
> http://computer-go.org/mailman/listinfo/computer-go
> 
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End of Computer-go Digest, Vol 71, Issue 22
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Re: [Computer-go] Those were the days ...

2015-12-29 Thread Ingo Althöfer

Hi Detlef,

>I gave pure DCNN 54% a try against the 15 kyu version:)

did I get it right, that these 54 % were from normal 6-dan games
("normal" meaning small or no handicap)?

I think you need "Mueller High Handicap games" for feeding the CNN.
 
Cheers, Ingo.
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Re: [Computer-go] Those were the days ...

2015-12-29 Thread Detlef Schmicker

-BEGIN PGP SIGNED MESSAGE-
Hash: SHA1

Yes, the published

http://computer-go.org/pipermail/computer-go/2015-December/008324.html

I think, you can not win this with "normal" good moves :)

You have to exploit mfgo

Detlef

Am 29.12.2015 um 15:18 schrieb "Ingo Althöfer":
> Hi Detlef,
> 
>> I gave pure DCNN 54% a try against the 15 kyu version:)
> 
> did I get it right, that these 54 % were from normal 6-dan games 
> ("normal" meaning small or no handicap)?
> 
> I think you need "Mueller High Handicap games" for feeding the
> CNN.
> 
> Cheers, Ingo. ___ 
> Computer-go mailing list Computer-go@computer-go.org 
> http://computer-go.org/mailman/listinfo/computer-go
> 
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Re: [Computer-go] Those were the days ...

2015-12-29 Thread Detlef Schmicker

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Hash: SHA1

I gave pure DCNN 54% a try against the 15 kyu version:)

http://files.gokgs.com/games/2015/12/29/mfgo15kyu0-NiceGo19N.sgf

There was no pass handling, therefore filled an eye, without would
have been 133.5 loss or so :)

Detlef

Am 29.12.2015 um 11:20 schrieb "Ingo Althöfer":
> Hello all,
> 
> 
>> Martin understood computer go weaknesses, so he played to exploit
>> them.  A modern program not specifically tuned for those
>> weaknesses would have a much more difficult time.
> 
> Agreed. Concerning CNN bots (like darkfores3), a natural way would
> be to find some players of Martin's calibre who play hundreds of
> games against the old MFoG at handicap 29. These games might become
> the training set for the CNN.
> 
>> I released version 10 in 1997, so it might be more accurate to
>> play against version 10 rather than against version 12 at 12 kyu
>> level.  I probably still have a version 10 CD somewhere.
> 
> I also still have one, I think.
> 
> Anyway, as soon as a serious contender shows up, I am willing to
> allow a match environment that may - in case of disputes - be
> helpful for the bot.
> 
> Ingo.
> 
> PS. I want to see my 1,000 Euros finding their way to a pocket of
> a talented go programmer! 
> ___ Computer-go mailing
> list Computer-go@computer-go.org 
> http://computer-go.org/mailman/listinfo/computer-go
> 
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Re: [Computer-go] Those were the days ...

2015-12-29 Thread Ingo Althöfer

Hello all,


> Martin understood computer go weaknesses, so he played to exploit them.  A 
> modern program 
> not specifically tuned for those weaknesses would have a much more difficult 
> time.

Agreed. Concerning CNN bots (like darkfores3), a natural way would be to find
some players of Martin's calibre who play hundreds of games against the old MFoG
at handicap 29. These games might become the training set for the CNN.

> I released version 10 in 1997, so it might be more accurate to play against 
> version 10 
> rather than against version 12 at 12 kyu level.  I probably still have a 
> version 10 CD somewhere.

I also still have one, I think.

Anyway, as soon as a serious contender shows up, I am willing to allow
a match environment that may - in case of disputes - be helpful for the bot. 

Ingo.

PS. I want to see my 1,000 Euros finding their way to a pocket of a
talented go programmer!
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Re: [Computer-go] Computer-go Digest, Vol 71, Issue 22

Re: [Computer-go] Computer-go Digest, Vol 71, Issue 22

Re: [Computer-go] CNN with 54% prediction on KGS 6d+ data

Re: [Computer-go] Computer-go Digest, Vol 71, Issue 22

Re: [Computer-go] Those were the days ...

Re: [Computer-go] Those were the days ...

Re: [Computer-go] Those were the days ...

Re: [Computer-go] Those were the days ...

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