[Computer-go] 25x25 experiment

2015-04-27 Thread Petr Baudis
On Sun, Apr 26, 2015 at 11:26:42PM +0200, Petr Baudis wrote:
 On Sun, Apr 26, 2015 at 12:17:01PM +0200, remi.cou...@free.fr wrote:
  Hi,
  
  I thought it might be fun to have a tournament on a very large board. It 
  might also motivate research into more clever adaptive playouts. Maybe a 
  KGS tournament? What do you think?
 
 That's a cool idea - even though I wonder if 39x39 is maybe too extreme
 (I guess the motivation is maximum size KGS allows).
 
 I think that actually, GNUGo could become stronger than even the top
 MCTS programs at some point when expanding the board size, but it's hard
 for me to estimate exactly when - if at 25x25 or at 49x49...

I've let play Pachi (in the same configuration that ranks it as 2d on
KGS, but with 15s/move) to play GNUGo for a few games on 25x25 just to
see how it would go.  I'm attaching three SGFs if anyone would like to
take a look, Pachi never had trouble beating GNUGo.

Couple of observations:

(i) The speed is only about 60% playouts in the same time compared
to 19x19.

(ii) GNUGo needs to be recompiled to work on larger boards, modify
the MAX_BOARD #define in engine/board.h.  (Same with Pachi.)

(iii) As-is, Pachi might get into stack overflow trouble if ran on
larger boards than 25x25.

(iv) 25x25 is the last board size where columns can be represented by
single English alphabet letters.  This is the reason for the GTP
limitation, but might trigger other limitations in debug routines etc.

(v) The very first game (not included), Pachi lost completely.
I discovered that my max playout length was 600 moves; bumping that
to 1200 made things boring again.

(vi) Some typically fast operations take much longer on large boards,
e.g. tree pruning (because much wider tree breadth; on 19x19 it's
rarely more than 100ms but it can take seconds on 25x25 for some
reason); this would actually make Pachi occassionally lose byoyomi
periods by a second or two without a manual time allocation adjustment.

And a conjencture:

(vii) (Even) games against GNUGo still aren't interesting on 25x25.
The same factors that might benefit GNUGo compared to MCTS programs
should also benefit DNN players and the difference might be more
visible because a DNN should be much stronger than GNUGo.  I wonder
if the oakfoam or any other effort on building an open source DNN
implementation can already play standalone games and how well it works?

-- 
Petr Baudis
If you do not work on an important problem, it's unlikely
you'll do important work.  -- R. Hamming
http://www.cs.virginia.edu/~robins/YouAndYourResearch.html


z3-0.sgf
Description: application/go-sgf


z4-0.sgf
Description: application/go-sgf


z5-0.sgf
Description: application/go-sgf
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Re: [Computer-go] How about a 39x39 tournament?

2015-04-27 Thread Ingo Althöfer


Hi all,
 
I would like to see some bot-vs-bot games on 37x37 or 39x39.
 

Von: Erik van der Werf erikvanderw...@gmail.com
 Personally I think 39x39 is too big. Also, there is a problem with GTP;
 the protocol does not support boards over 25x25.
 
Some years ago, Gian-Carlo Pascutto had provided a large-board version of
Leela. For that he had introduced a natural extension of the sgf 
board-coordinates.
 
On 37x37, Leela lost clearly to a human 3-kyu, despite having 8 handicap stones.
 
Ingo.
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Re: [Computer-go] How about a 39x39 tournament?

2015-04-27 Thread remi . coulom
I have just tested: the KGS client only accept board sizes = 25, 
unfortunately. But 25x25 worked fine with Crazy Stone.

Rémi

- Mail original -
De: Urban Hafner cont...@urbanhafner.com
À: computer-go@computer-go.org
Envoyé: Lundi 27 Avril 2015 17:51:19
Objet: Re: [Computer-go] How about a 39x39 tournament?



That sounds fun. But we should figure out how KGS implements the coordinates 
for such large boards. 


On Mon, Apr 27, 2015 at 10:40 AM, Nick Wedd  mapr...@gmail.com  wrote: 



I find that I can create KGS tournaments on sizes of board up to 38x38, 
but not 39x39 and larger. I will gladly do so if there is enough demand. 



Nick 




On 27 April 2015 at 08:03, Ingo Althöfer  3-hirn-ver...@gmx.de  wrote: 




Hi all, 

I would like to see some bot-vs-bot games on 37x37 or 39x39. 


Von: Erik van der Werf  erikvanderw...@gmail.com  
 Personally I think 39x39 is too big. Also, there is a problem with GTP; 
 the protocol does not support boards over 25x25. 

Some years ago, Gian-Carlo Pascutto had provided a large-board version of 
Leela. For that he had introduced a natural extension of the sgf 
board-coordinates. 

On 37x37, Leela lost clearly to a human 3-kyu, despite having 8 handicap 
stones. 

Ingo. 


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Re: [Computer-go] 25x25 experiment

2015-04-27 Thread Detlef Schmicker
oakfoam has BOARDSIZE_MAX set to 25, but it seems it is only used to say 
unsupported board size at the moment :)
I think the reason was gtp, but it was set long before I joined the 
project 



I dont see a reason, why there should be any problems using it with DNN 
on 19x19 trained network. If a 25x25 will be sheduled, I will take part :)



Detlef


Am 27.04.2015 um 12:00 schrieb Petr Baudis:

On Sun, Apr 26, 2015 at 11:26:42PM +0200, Petr Baudis wrote:

On Sun, Apr 26, 2015 at 12:17:01PM +0200, remi.cou...@free.fr wrote:

Hi,

I thought it might be fun to have a tournament on a very large board. It might 
also motivate research into more clever adaptive playouts. Maybe a KGS 
tournament? What do you think?

That's a cool idea - even though I wonder if 39x39 is maybe too extreme
(I guess the motivation is maximum size KGS allows).

I think that actually, GNUGo could become stronger than even the top
MCTS programs at some point when expanding the board size, but it's hard
for me to estimate exactly when - if at 25x25 or at 49x49...

I've let play Pachi (in the same configuration that ranks it as 2d on
KGS, but with 15s/move) to play GNUGo for a few games on 25x25 just to
see how it would go.  I'm attaching three SGFs if anyone would like to
take a look, Pachi never had trouble beating GNUGo.

Couple of observations:

(i) The speed is only about 60% playouts in the same time compared
to 19x19.

(ii) GNUGo needs to be recompiled to work on larger boards, modify
the MAX_BOARD #define in engine/board.h.  (Same with Pachi.)

(iii) As-is, Pachi might get into stack overflow trouble if ran on
larger boards than 25x25.

(iv) 25x25 is the last board size where columns can be represented by
single English alphabet letters.  This is the reason for the GTP
limitation, but might trigger other limitations in debug routines etc.

(v) The very first game (not included), Pachi lost completely.
I discovered that my max playout length was 600 moves; bumping that
to 1200 made things boring again.

(vi) Some typically fast operations take much longer on large boards,
e.g. tree pruning (because much wider tree breadth; on 19x19 it's
rarely more than 100ms but it can take seconds on 25x25 for some
reason); this would actually make Pachi occassionally lose byoyomi
periods by a second or two without a manual time allocation adjustment.

And a conjencture:

(vii) (Even) games against GNUGo still aren't interesting on 25x25.
The same factors that might benefit GNUGo compared to MCTS programs
should also benefit DNN players and the difference might be more
visible because a DNN should be much stronger than GNUGo.  I wonder
if the oakfoam or any other effort on building an open source DNN
implementation can already play standalone games and how well it works?



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Re: [Computer-go] May KGS bot tournament, 19x19

2015-04-27 Thread Nick Wedd
Thank you, Peter, for pointing out the error.

Gmail automatically detects URLs in emails, and makes them into
links. However, it seems it sometimes does it slightly wrong.  Here
is the corrected message:

The May KGS bot tournament will be on Sunday May 3rd, starting at
16:00 UTC and ending by 23:00 UTC.  It will use 19x19 boards, with time
limits of 14 minutes each plus fast Canadian overtime, and komi of 7.5.
There are details at http://www.gokgs.com/tournInfo.jsp?id=956
http://www.gokgs.com/tournInfo.jsp?id=942

Please register by emailing me, with the words KGS Tournament
Registration in the email title, at mapr...@gmail.com .

On 24 April 2015 at 17:55, Nick Wedd mapr...@gmail.com wrote:

 The May KGS bot tournament will be on Sunday May 3rd, starting at
 16:00 UTC and ending by 23:00 UTC.  It will use 19x19 boards, with time
 limits of 14 minutes each plus fast Canadian overtime, and komi of 7.5.
 There are details at http://www.gokgs.com/tournInfo.jsp?id=95
 http://www.gokgs.com/tournInfo.jsp?id=9426

 Please register by emailing me, with the words KGS Tournament
 Registration in the email title, at mapr...@gmail.com .

 Nick
 --
 Nick Wedd  mapr...@gmail.com




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Re: [Computer-go] How about a 39x39 tournament?

2015-04-27 Thread Nick Wedd
I find that I can create KGS tournaments on sizes of board up to 38x38,
but not 39x39 and larger. I will gladly do so if there is enough demand.

Nick

On 27 April 2015 at 08:03, Ingo Althöfer 3-hirn-ver...@gmx.de wrote:



 Hi all,

 I would like to see some bot-vs-bot games on 37x37 or 39x39.


 Von: Erik van der Werf erikvanderw...@gmail.com
  Personally I think 39x39 is too big. Also, there is a problem with GTP;
  the protocol does not support boards over 25x25.

 Some years ago, Gian-Carlo Pascutto had provided a large-board version of
 Leela. For that he had introduced a natural extension of the sgf
 board-coordinates.

 On 37x37, Leela lost clearly to a human 3-kyu, despite having 8 handicap
 stones.

 Ingo.
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Re: [Computer-go] How about a 39x39 tournament?

2015-04-27 Thread Urban Hafner
That sounds fun. But we should figure out how KGS implements the
coordinates for such large boards.

On Mon, Apr 27, 2015 at 10:40 AM, Nick Wedd mapr...@gmail.com wrote:

 I find that I can create KGS tournaments on sizes of board up to 38x38,
 but not 39x39 and larger. I will gladly do so if there is enough demand.

 Nick

 On 27 April 2015 at 08:03, Ingo Althöfer 3-hirn-ver...@gmx.de wrote:



 Hi all,

 I would like to see some bot-vs-bot games on 37x37 or 39x39.


 Von: Erik van der Werf erikvanderw...@gmail.com
  Personally I think 39x39 is too big. Also, there is a problem with GTP;
  the protocol does not support boards over 25x25.

 Some years ago, Gian-Carlo Pascutto had provided a large-board version of
 Leela. For that he had introduced a natural extension of the sgf
 board-coordinates.

 On 37x37, Leela lost clearly to a human 3-kyu, despite having 8 handicap
 stones.

 Ingo.
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 --
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Re: [Computer-go] May KGS bot tournament, 19x19

2015-04-27 Thread Nick Wedd
This is weird.  My corrected message now highlights all three digits of
956,
but still links to tournament 942.  The correct link is, I hope,

a href=http://www.gokgs.com/tournInfo.jsp?id=956;
http://www.gokgs.com/tournInfo.jsp?id=956/a


On 27 April 2015 at 09:48, Nick Wedd mapr...@gmail.com wrote:

 Thank you, Peter, for pointing out the error.

 Gmail automatically detects URLs in emails, and makes them into
 links. However, it seems it sometimes does it slightly wrong.  Here
 is the corrected message:

 The May KGS bot tournament will be on Sunday May 3rd, starting at
 16:00 UTC and ending by 23:00 UTC.  It will use 19x19 boards, with time
 limits of 14 minutes each plus fast Canadian overtime, and komi of 7.5.
 There are details at http://www.gokgs.com/tournInfo.jsp?id=956
 http://www.gokgs.com/tournInfo.jsp?id=942

 Please register by emailing me, with the words KGS Tournament
 Registration in the email title, at mapr...@gmail.com .

 On 24 April 2015 at 17:55, Nick Wedd mapr...@gmail.com wrote:

 The May KGS bot tournament will be on Sunday May 3rd, starting at
 16:00 UTC and ending by 23:00 UTC.  It will use 19x19 boards, with time
 limits of 14 minutes each plus fast Canadian overtime, and komi of 7.5.
 There are details at http://www.gokgs.com/tournInfo.jsp?id=95
 http://www.gokgs.com/tournInfo.jsp?id=9426

 Please register by emailing me, with the words KGS Tournament
 Registration in the email title, at mapr...@gmail.com .

 Nick
 --
 Nick Wedd  mapr...@gmail.com




 --
 Nick Wedd  mapr...@gmail.com




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Re: [Computer-go] 25x25 experiment

2015-04-27 Thread Detlef Schmicker

Sorry, it is not,


but I offer my trained DCNN http://physik.de/net.tgz

it has about 44% prediction rate and uses only the position

it a a caffe file which is quite easy to use:

void Engine::getCNN(Go::Board *board,Go::Color col, float result[])
{
  int size=board-getSize();
float *data;
data= new float[2*size*size];
//fprintf(stderr,2\n);
if (col==Go::BLACK) {
  for (int j=0;jsize;j++)
for (int k=0;ksize;k++)
  {//fprintf(stderr,%d %d %d\n,i,j,k);
  if (board-getColor(Go::Position::xy2pos(j,k,size))==Go::BLACK)
  {
  data[j*size+k]=1.0;
  data[size*size+size*j+k]=0.0;
  }
  else if 
(board-getColor(Go::Position::xy2pos(j,k,size))==Go::WHITE)

  {
  data[j*size+k]=0.0;
  data[size*size+size*j+k]=1.0;
  }
  else
  {
  data[j*size+k]=0.0;
  data[size*size+size*j+k]=0.0;
  }
}
}
if (col==Go::WHITE) {
  for (int j=0;jsize;j++)
for (int k=0;ksize;k++)
  {//fprintf(stderr,%d %d %d\n,i,j,k);
  if (board-getColor(Go::Position::xy2pos(j,k,size))==Go::BLACK)
  {
  data[j*size+k]=0.0;
  data[size*size+size*j+k]=1.0;
  }
  else if 
(board-getColor(Go::Position::xy2pos(j,k,size))==Go::WHITE)

  {
  data[j*size+k]=1.0;
  data[size*size+size*j+k]=0.0;
  }
  else
  {
  data[j*size+k]=0.0;
  data[size*size+size*j+k]=0.0;
  }
}
}


  Blobfloat *b=new Blobfloat(1,2,size,size);
  b-set_cpu_data(data);
  vectorBlobfloat* bottom;
  bottom.push_back(b);
  const vectorBlobfloat* rr = caffe_test_net-Forward(bottom);
  //for (int j=0;j19;j++)
//{
//for (int k=0;k19;k++)
//{
//fprintf(stderr,%5.3f ,rr[0]-cpu_data()[j*19+k]);
//}
//fprintf(stderr,\n);
//}
  for (int i=0;isize*size;i++) {
  result[i]=rr[0]-cpu_data()[i];
if (result[i]0.1) result[i]=0.1;
  }
  delete[] data;
  delete b;
}



Am 27.04.2015 um 13:44 schrieb Petr Baudis:

On Mon, Apr 27, 2015 at 12:35:05PM +0200, Detlef Schmicker wrote:

I dont see a reason, why there should be any problems using it with
DNN on 19x19 trained network. If a 25x25 will be sheduled, I will
take part :)

I'm sorry for being unclear!  I actually meant DCNN as a standalone
player, not part of MCTS.  Is it possible to run oakfoam's DCNN
implementation like that?  (Have you measured its stength?)

Thanks,

Petr Baudis
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Re: [Computer-go] How about a 39x39 tournament?

2015-04-27 Thread Gian-Carlo Pascutto
On 27-04-15 09:03, Ingo Althöfer wrote:

 Some years ago, Gian-Carlo Pascutto had provided a large-board version of
 Leela. For that he had introduced a natural extension of the sgf 
 board-coordinates.

I just followed the official specification, which allows up to 52x52:
http://www.red-bean.com/sgf/go.html
http://www.red-bean.com/sgf/index.html

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Re: [Computer-go] 25x25 experiment

2015-04-27 Thread Petr Baudis
On Mon, Apr 27, 2015 at 12:35:05PM +0200, Detlef Schmicker wrote:
 I dont see a reason, why there should be any problems using it with
 DNN on 19x19 trained network. If a 25x25 will be sheduled, I will
 take part :)

I'm sorry for being unclear!  I actually meant DCNN as a standalone
player, not part of MCTS.  Is it possible to run oakfoam's DCNN
implementation like that?  (Have you measured its stength?)

Thanks,

Petr Baudis
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[Computer-go] Three Lectureships

2015-04-27 Thread Lucas, Simon M
This may be of interest to readers of this list.

We are looking for people of outstanding
ability who are passionate about research and
education.

The lectureships are in:


· Computer Science and Artificial Intelligence

· Computer Games and Artificial Intelligence

· Computational Finance

These are tenure track, and equivalent to Assistant Professor grade.

Of special interest to this list is that we’re looking to expand
our teaching of computer games at Essex, with an exciting new
MSc in the area.

Closing date for applications: May 28, 2015
Preferred starting date: September 1, 2015
Starting Salary £38,511 - £45,954 (GBP) per annum

More details:  http://tinyurl.com/cseejobs

Best wishes,

  Simon Lucas

Professor Simon Lucas
Head of School
Computer Science and Electronic Engineering
University of Essex, UK
https://www.essex.ac.uk/csee/



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Re: [Computer-go] Utilizing multiple parametersets/bias systems/bots

2015-04-27 Thread Leandro Marcolino
Hi, Marc,

You may want to take a look at my papers, they are kind of related to these
ideas (although I didn't yet change the team on the fly, as you are
suggesting):

* http://teamcore.usc.edu/people/sorianom/aaai14.pdf
* http://teamcore.usc.edu/papers/2013/ijcai13.pdf
* http://teamcore.usc.edu/people/sorianom/AAMAS2011.pdf

Concerning changing the settings dynamically, my most recent work may help
(when using voting):

* http://teamcore.usc.edu/papers/2015/aamas2015.pdf

Let me know if you have questions/comments... :)

Best,
Leandro

On Sun, Apr 26, 2015 at 7:59 AM, Marc Landgraf mahrgel...@gmail.com wrote:

 Heya,
 I lately tried to think about, whether it would be possible to combine the
 strengths of different bots, or at least different parameter sets/bias
 systems for one bots in some way. They may shine at different
 situations/phases during the game, but how to figure out, which one is
 currently the better one?

 What I now came up with, was the following:
 For simplicity we assume for now, that our different bots are using the
 same playouts, but different approaches during the tree phase. So maybe
 they use different ways to bias nodes, different selection formulas etc.
 Gonna focus on them using different bias systems.
 Now you split up your playouts in percentiles:
 25%: Bot1 selects the white moves, Bot2 the black ones
 25%: the other way around
 0x%50%: Bot1 selects for both.
 50%-x%: Bot2 selects for both.
 You track the win rates of those first 2 quarters separately and also
 calculate winrate of Bot1 vs Bot2.
 Now if the bots are identical obviously both should win 50%. But if the
 bots are different, you may see different results.
 E.g. when Bot1 wins 55% of his games, his move selection is probably
 better then Bot2's move selection. Here you have to be careful about wrong
 conclusions, because if you would setup a depth-first bot vs a width-first
 you would certainly also get win rates heavily in favor of the depth-first.
 But where this could shine is, when using different bias systems. Because
 it actually tells you, which bias system is doing better in the current
 board situation.
 Now you can use that knowledge to calculate x. E.g. if either bot wins
 60%+ he gains all 50% of the remaining playouts, and let the balance slide
 linearly, if the win rate is 40-60% for the bots against each other. (use
 whatever formula here, open for testing)

 This should enable you to figure out on the fly, which bias system is
 doing a better job at the current situation, while doing playouts. You are
 just tracking some additional stats.

 Of course, there are pros and cons to this method:
 + In general, switching selection method in the tree should not cost any
 time, and tracking those additional stats also costs close to no time. Only
 additional time used comes from using a second bias function or similar
 (because now you have to calculate the bias twice, for most nodes)
 - At the same time, the amount of data is actually increasing, because you
 have to track the stats for the different bots. This may cause memory
 issues! (but when using a distributed memory solution anyway, it does not
 create additional data, if each memory/thread unit is assigned to one of
 those percentiles of playouts)
 +- In general the costs increase depends on how different the 2 Bots are.
 If they are the same, there would be basically no cost.
 + Allows you to figure out, which bot/bias/selection is doing better right
 now
 - but may lead to false conclusions, like above mentioned depth vs width
 example
 +- As long as both bots are of similar strength, you should not lose from
 using this kind of system. Worst case is, that you play the wrong bots
 move, if you had above mentioned false conclusions. But when they are close
 in strength, that is not worse than using just one bot all the time. Of
 course, if one bot is dominating the other one in all situations, you are
 losing quality, when figuring out again and again, that this is the case.
 (because in 50% of the playouts, half of the moves were selected by the
 worse bot)



 So some quick ideas how it could be modified further:
 - all percentages are obviously placeholders and could be adjusted (even
 dynamically)
 - assuming you have a low cost and a very high time cost bias function,
 you can actually check, if it is worth using the high cost bias function,
 or if the board situation is simple enough to churn out more playouts using
 the cheaper function.
 - identifying certain game situations: you may know, that one bias is
 doing much better in corner fights or liberty races, so if that one is
 dominating, you are probably in such a situation and can now adjust further
 (e.g. modify playouts, add additional routines, whatever)
 - using more then 2 routines, possibly in conjunction with the idea above
 to identify situations.

 Of course, one could now also think how to expand this idea, with using
 different playouts, but I'm not sure how to judge,