Re: [Computer-go] Standard Computer Go Datasets - Proposal

[Erik van der Werf]

On Fri, Nov 13, 2015 at 10:46 AM, Darren Cook  wrote:
>
> The advantages of storing games:
>   * accountability/traceability
>   * for programs who want to learn sequences of moves.
>

Another advantage of storing games is that it is much more efficient; you
only have to encode one move per position.

Erik
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Re: [Computer-go] Scraping lower-ranked games from kgs

[Arthur Cater]

Thanks for the tip. I agree and I have no intention to misbehave.

Arthur

> On Nov 13, 2015, at 8:38 AM, Petri Pitkanen  
> wrote:
> 
> Yes scraping for large amounts of data from  a smallish server is not really 
> polite. May overload the server. Besides quite inefficient. You could make a 
> request to owner of site instead. Assuming you can present good enough reason 
>  you might get lucky

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Re: [Computer-go] Standard Computer Go Datasets - Proposal

[Gonçalo Mendes Ferreira]

I think if you start calculating the Zobrist hashes and scraping 
features yourself you will have a neverending variety of datasets.


I would prefer datasets of whole, high quality games without SGF errors, 
perhaps cleaned of identifying information. Parsing an SGF is already 
trivial. I personally divide them in:


- Handicap used or not
- Normal (5.5 - 7.5) or not komi, this disqualifies some older games
- Rules used
- Board size

Following the idea of having more information instead of very specific 
features already extracted, it would be interesting to also have the 
playing times, although I don't know where you'd get that from.


You'd be an angel if you could provide a large dataset of matches with 
Chinese rules, specially in board sizes other than 19x19.


It would of course also have to be completely free for any use. I 
personally only use the KGS 6d+ and a collection of 70k pro games that I 
don't know where it came from. The GoGoD is proprietary. :)


Gonçalo F.

On 11/13/2015 08:39 AM, Josef Moudrik wrote:

Hello List,

There has been some debate in science about making the research more
reproducible and open. Recently, I have been thinking about making a
standard public fixed dataset of Go games, mainly to ease comparison of
different methods, to make results more reproducible and maybe free the
authors of the burden of composing a dataset. I think that the current
practice can be improved a lot.

Since the success of this endeavor crucially depends on how many authors
use the dataset, I would like to ask You (potential authors) a few
questions:

1) Would this be welcomed and used? Would You personally use it? (Am I not
reinventing the wheel?)

2) What parameters should the dataset have? The number of dataset variants
(if any) should be in my opinion kept at bare minimum to reduce
"fragmentation".

2a) Size: My current view is that at least 2 sizes are necessary: small
(1000-2000 games?) and large dataset (5-6 games).
2b) Strength & year span: Currently I am thinking about including modern
professional games only (1970-2015)

3) Do you have any other comments, requirements for the dataset and ideas?


Thanks for Your attention,
Kind regards
Josef Moudrik



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Re: [Computer-go] Standard Computer Go Datasets - Proposal

[Gonçalo Mendes Ferreira]

At least in the past some DCNN made use of the players ranks, so it 
should be best to leave it.


On 11/13/2015 10:27 AM, Josef Moudrik wrote:

On Fri, Nov 13, 2015 at 11:16 AM Erik van der Werf 
wrote:


On Fri, Nov 13, 2015 at 10:46 AM, Darren Cook  wrote:


The advantages of storing games:
   * accountability/traceability
   * for programs who want to learn sequences of moves.



Another advantage of storing games is that it is much more efficient; you
only have to encode one move per position.

Erik



Yes,
I think that having full games would be much more useful. The anonymization
of the I had in mind would include hiding information not important for
computer processing such as file-names, player names, dates, ranks,
comments (given that the dataset would ensure consistent "balanced"
distribution). Like this, the database would have no (or much less) use for
human study.



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Re: [Computer-go] Mylin Valley The World Computer Weiqi Tournament

[Hiroshi Yamashita]

Hi,

It seems DolBaram won. (from last photo on web)

1st DolBaram
2nd Zen
3rd ManyFaces of Go
4th Ray
http://51wq.lianzhong.com/Home/NewsDetails?newsID=539=%25e7%2584%25a6%25e7%2582%25b9%25e6%2596%25b0%25e9%2597%25bb

Hiroshi Yamashita

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[Computer-go] Standard Computer Go Datasets - Proposal

[Josef Moudrik]

Hello List,

There has been some debate in science about making the research more
reproducible and open. Recently, I have been thinking about making a
standard public fixed dataset of Go games, mainly to ease comparison of
different methods, to make results more reproducible and maybe free the
authors of the burden of composing a dataset. I think that the current
practice can be improved a lot.

Since the success of this endeavor crucially depends on how many authors
use the dataset, I would like to ask You (potential authors) a few
questions:

1) Would this be welcomed and used? Would You personally use it? (Am I not
reinventing the wheel?)

2) What parameters should the dataset have? The number of dataset variants
(if any) should be in my opinion kept at bare minimum to reduce
"fragmentation".

2a) Size: My current view is that at least 2 sizes are necessary: small
(1000-2000 games?) and large dataset (5-6 games).
2b) Strength & year span: Currently I am thinking about including modern
professional games only (1970-2015)

3) Do you have any other comments, requirements for the dataset and ideas?


Thanks for Your attention,
Kind regards
Josef Moudrik
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Re: [Computer-go] Standard Computer Go Datasets - Proposal

[Petr Baudis]

  Hi!

On Fri, Nov 13, 2015 at 08:39:20AM +, Josef Moudrik wrote:
> There has been some debate in science about making the research more
> reproducible and open. Recently, I have been thinking about making a
> standard public fixed dataset of Go games, mainly to ease comparison of
> different methods, to make results more reproducible and maybe free the
> authors of the burden of composing a dataset. I think that the current
> practice can be improved a lot.

  I think the current de facto standard dataset is GoGoD (some year, not
quite fixed).  So I think it's useful to differentiate your proposal
against this dataset - what are the current problems and what will be
the advantage?

  One advantage would be of course if the dataset is freely available.
But it's not clear how to achieve that, i.e. where to get a large
professional game collection without copyright protection.

> 2a) Size: My current view is that at least 2 sizes are necessary: small
> (1000-2000 games?) and large dataset (5-6 games).

  What's the usecase for a small dataset?

-- 
Petr Baudis
If you have good ideas, good data and fast computers,
you can do almost anything. -- Geoffrey Hinton
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Re: [Computer-go] Standard Computer Go Datasets - Proposal

[Darren Cook]

> standard public fixed dataset of Go games, mainly to ease comparison of
> different methods, to make results more reproducible and maybe free the
> authors of the burden of composing a dataset. 

Maybe the first question should be is if people want a database of
*positions* or *games*.

I imagine a position database to be a set of board descriptions, with
each pro move marked on it. Ideally each move would say not just the
number of times it was chosen, but break it down by rank of player.

Each would have a zobrist hash calculated, in all 8 combinations, and
the lowest chosen. This handles rotations and duplicates. If there was
as a ko-illegal point on the board that needs to be stored, and also be
part of the zobrist hash.


A database of positions has some advantages:
  * No licensing issues (*)
  * Rotational duplicates already removed
  * Ready-to-go with the information (most) programs want to learn.


The advantages of storing games:
  * accountability/traceability
  * for programs who want to learn sequences of moves.

Darren


*: At least that was my conclusion when I looked into this before. Game
collections can be copyrighted; moves cannot. A database of moves can be
freely distributed, even it was generated from copyrighted game
collections, as long as there exists no way to regenerate the game
collection from it.

Text corpora (used in machine translation studies, for instance) follow
the same idea: if you split the corpora into sentences, then shuffle
them up randomly, you can distribute the set of sentences.

(I did wonder about storing player ranks, e.g. if a given position has a
move chosen by only a single 9p, and you can then extract each follow-up
position, you could extract a game. But, IMHO, you cannot regenerate any
particular game collection this way. If it is a concern, it can be
solved by only using a random 80% of moves from games.)

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Re: [Computer-go] Scraping lower-ranked games from kgs

[Petri Pitkanen]

Yes scraping for large amounts of data from  a smallish server is not
really polite. May overload the server. Besides quite inefficient. You
could make a request to owner of site instead. Assuming you can present
good enough reason  you might get lucky

2015-11-13 8:39 GMT+02:00 Josef Moudrik :

> Hello,
>
> I have a simple script for downloading info (gamelist, list of oponents,
> games) one by one here:
>
> http://repo.or.cz/gostyle.git/blob/HEAD:/kgs/kgs.py
>
> If you want to download more players, you need to search through opponents
> of players you know. But do not spam the kgs server too much please :-)
>
> Regards,
> Josef
>
>
> On Thu, Nov 12, 2015 at 2:35 PM Arthur Cater  wrote:
>
>> Hello,
>> I would be interested for research purposes in getting lots of game sgfs
>> of
>> lower-ranked players, to contrast with the high dan and pro games that
>> get put into collections. Even kyu games. I was thinking of getting them
>> from kgs archives.
>>
>> I wonder if anyone already has a script that could (or could be easily
>> adapted to) do this? And would they share?
>>
>> Thanks,
>>
>> Arthur
>>
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Re: [Computer-go] Standard Computer Go Datasets - Proposal

[fotland]

I would only use it if it is licensed for commercial use.
 
David

On Fri, 13 Nov 2015 08:39:20 +, Josef Moudrik  wrote:

  Hello List, 
There has been some debate in science about making the research more
reproducible and open. Recently, I have been thinking about making a
standard public fixed dataset of Go games, mainly to ease comparison of
different methods, to make results more reproducible and maybe free the
authors of the burden of composing a dataset. I think that the current
practice can be improved a lot.
 
Since the success of this endeavor crucially depends on how many
authors use the dataset, I would like to ask You (potential authors) a
few questions:
 
1) Would this be welcomed and used? Would You personally use it? (Am I
not reinventing the wheel?)
 
2) What parameters should the dataset have? The number of dataset
variants (if any) should be in my opinion kept at bare minimum to
reduce "fragmentation".
 
2a) Size: My current view is that at least 2 sizes are necessary: small
(1000-2000 games?) and large dataset (5-6 games). 
2b) Strength & year span: Currently I am thinking about including
modern professional games only (1970-2015)
 
3) Do you have any other comments, requirements for the dataset and ideas?
 
 
Thanks for Your attention,
Kind regards
Josef Moudrik
 

-

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Re: [Computer-go] Standard Computer Go Datasets - Proposal

[Josef Moudrik]

Hello,

On Fri, Nov 13, 2015 at 10:13 AM  wrote:
> I would only use it if it is licensed for commercial use.

Yes, I would like to licence this as such, please see below.

On Fri, Nov 13, 2015 at 10:23 AM Petr Baudis  wrote:

> I think the current de facto standard dataset is GoGoD (some year, not
> quite fixed). So I think it's useful to differentiate your proposal
> against this dataset - what are the current problems and what will be
> the advantage?

Yes, I know GoGoD is used frequently, but I think that the lack of
"precise" specification is the problem. There are many choices an author
has to make when using the GoGoD database: year of release, year span,
handicap games?, amateur/professional? (how to tell? pro rank is d not p).
Related thing is that some of the games (If I remember my experience
correctly) cannot be parsed by some libraries in which case they are
usually skipped. All these are branching points that make "precise"
replication of results hard.

> One advantage would be of course if the dataset is freely available.
> But it's not clear how to achieve that, i.e. where to get a large
> professional game collection without copyright protection.

I consider this "negotiation" as the hardest work I will have to do, but
before I start, I want to research if the dataset would be even used. From
the point of view of copyright law, I believe that what is protected is the
"collection of games" and "additional materials" (comments, etc), not the
actual individual games themselves (which as a record of a historical event
afaik cannot be copyrighted). The "collection of games" and "additional
materials" right of current collection owners could be protected by
anonymization of the records and mixing of different databases, if the
current owners agree.

>From the licensing point of view, again given that owners agree, I would
like to release the dataset under something like
free-for-all-purposes-with-attribution license. This I have to research yet.

> What's the usecase for a small dataset?

I had prototype testing in mind, s.t. authors can say "our method is slow,
so we only tested on the SmallGoDataset" instead of "we randomly took 1000
games from the BigGoDataset", but I assume there would be other usecases as
well. Anyway, I think the big and small datasets would not imo cause much
use-fragmentation, because the use cases for big vs small would be
different. But maybe I am overthinking things and this would not be used
much..


Regards,
Josef
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Re: [Computer-go] Standard Computer Go Datasets - Proposal

[Dave Dyer]

I was recently working on assigning final scores to completed games, using
the large data set from Badukmovies.com.  

My observation is that the size of the data set (50,000 games) is not
large enough to get good coverage of unusual situations occurring in real
games.

There's a definite need for a curated collection of atypical but
interesting games, probably manipulated to explore the boundaries
between interesting and normal.

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Re: [Computer-go] Standard Computer Go Datasets - Proposal

[Dave Dyer]

I was recently working on assigning final scores to completed games, using
the large data set from Badukmovies.com.  

My observation is that the size of the data set (50,000 games) is not
large enough to get good coverage of unusual situations occurring in real
games.

There's a definite need for a curated collection of atypical but
interesting games, probably manipulated to explore the boundaries
between interesting and normal.

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Re: [Computer-go] Frisbee Go Simulation

[robertfinkng...@o2.co.uk]

  
  
If this catches on, perhaps the rules will be referred to as the
  Ingo rules ;-)
  
  Since this is based on a real world variant of Go, why not base
  epsilon on that? The fact that the limit of displacement from the
  intended position is limited to the immediately adjacent points,
  suggests that the thrower is pretty accurate. The distribution is
  narrow enough that the chance of going further afield is
  (effectively) zero. Therefore epsilon should be pretty tiny. It
  must be large enough that there is a chance of the frisbee being
  at least 50% over the line (i.e. epsilon > 0), but small enough
  that the chance of it going 70.7% over the line is vanishingly
  small (otherwise we would be allowing it to be displaced onto the
  diagonally adjacent positions).
  
  Assuming a Gaussian distribution (probably not true for frisbees
  but it will do) and assuming 3 standard deviations away is close
  enough to "vanishingly small", we have 3.sigma = 0.7071...
  (sqrt(0.5)), sigma = 0.2357 (sqrt(0.5)/3), tipping point for throw
  being >50% over the line t.sigma = 0.5, t = 0.5 / sigma =
  3.sqrt(0.5) = 2.12 => epsilon = 0.017, approximately 1 in 60.
  
  Looking at this from a purely combinatorial point of view,t we
  need 1/epsilon > number-of-moves-in-a-game but 1/epsilon^2
  << number-of-moves-in-a-game, which 0.017 seems to satisfy
  for all common board sizes.
  
  Hopefully such a small epsilon also avoids destroying the
  possibility of local tactical play but also introduces a new
  element to the game (75% chance of at least once displaced move in
  81 move game, over 99% chance of at least one displaced move in a
  361 move game).
  
  In fact to model the real world, epsilon ought to vary depending
  on the move. It should increase depending on distance from
  throwing position, and should not be equal for N,S,E and W
  displacement. Assuming standing south of the board, we expect
  epsilon N > S > E = W (range is normally harder to judge
  than direction and overthrows tend to be worse than under-throws).
  
  It seems to me this may bring in interesting elements to move
  choice - it may be better to play a weaker move which is closer
  and therefore more likely to be played successfully than a
  stronger move which is less likely to be played successfully.
  
  But perhaps this over complicates things - how does it work out
  with fixed epsilon around 0.017.
  
  Raffles
  

On 11-Nov-15 15:29, Álvaro Begué wrote:


  1/5 also seems natural (equal chance of hitting
each the 5 possible points).

Álvaro.


  
  
On Wed, Nov 11, 2015 at 10:08 AM, John
  Tromp 
  wrote:
  > By the way: It would also be necessary to
  decide about
  > the eps for the event. Natural candidates would be
  > eps=0.1 or eps=0.125.
  
I would say the 2 most interesting choices are 1/8 or
1/4.
The latter guarantees you miss your aim by distance 1,
while the former gives you an even chance to hit it.

-John
  

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Re: [Computer-go] Standard Computer Go Datasets - Proposal

[Steven Clark]

To answer the original question: yes, the curation of a dataset like this
would be hugely beneficial to the community. Look at what ImageNet has done
for computer vision. In fact, it might be good to emulate ImageNet further
and pre-split the dataset into a publicly-available training set, and a
hidden testing set, for truly objective comparisons between move-prediction
algorithms.

If you undertake this, many thanks in advance!

On Fri, Nov 13, 2015 at 1:20 PM, Dave Dyer  wrote:

>
> I was recently working on assigning final scores to completed games, using
> the large data set from Badukmovies.com.
>
> My observation is that the size of the data set (50,000 games) is not
> large enough to get good coverage of unusual situations occurring in real
> games.
>
> There's a definite need for a curated collection of atypical but
> interesting games, probably manipulated to explore the boundaries
> between interesting and normal.
>
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[Computer-go] Program declining some games on KGS

[Peter Drake]

My program, Orego, is playing on KGS as Orego4. It's taking on all comers,
but refuses one particular opponent, apparently because there is an
unfinished game between Orego4 and this opponent.

Does anyone know what exactly might cause this or how to fix it? There is
certainly no code in Orego that keeps track of specific opponents; I
wouldn't even know how to get that information out of kgsgtp.

-- 
Peter Drake
https://sites.google.com/a/lclark.edu/drake/
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Re: [Computer-go] Program declining some games on KGS

[Hiroshi Yamashita]

Hi,

I think human player can push "Resume" and select Orego4 game.
Then, when Orego4 is idle, it will join resume game.

Regards,
Hiroshi Yamashita

- Original Message - 
From: "Peter Drake" 

To: 
Sent: Saturday, November 14, 2015 7:52 AM
Subject: [Computer-go] Program declining some games on KGS



My program, Orego, is playing on KGS as Orego4. It's taking on all comers,
but refuses one particular opponent, apparently because there is an
unfinished game between Orego4 and this opponent.

Does anyone know what exactly might cause this or how to fix it? There is
certainly no code in Orego that keeps track of specific opponents; I
wouldn't even know how to get that information out of kgsgtp.

--
Peter Drake
https://sites.google.com/a/lclark.edu/drake/








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Re: [Computer-go] Frisbee Go Simulation

[fotland]

Attached is a frisbee go game 9x9 between me and a Chines 5-dan
amateur.  50% chance of playing in the intended spot.  When a
connection is required, it is just up to chance who wins the fight.
 It's a little silly, but was a lot of fun to play.
 
David

On Wed, 11 Nov 2015 23:13:51 +0100, "Ingo Althöfer"  wrote:

  Hmm.


>> Would the game end after two unintentional passes?

> Good point. In principle I would say so.

That makes little sense to me.
IMO, the principled rule is that two consecutive intentional passes
end the game.


We should have some test games to see how long a game would be
"typically" stretched by unintended passes.

Ingo.
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frisbee.sgf
Description: application/go-sgf
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Re: [Computer-go] Mylin Valley The World Computer Weiqi Tournament

[fotland]

I don't have records but I watched three games between Zen and
Dolburam, and in each case Dol Buram won in the middle game fighting by
capturing some large group.  In the final of the elimination
tournament the game server crashed wen the game was about 2/3 finished,
so they played another game from the beginning.
 
Dol Buram in playing a pro now with four stones.  The game is being
streamed at
 
51wq.lianzhong.com/yidongwq/index.html
 
David

On Fri, 13 Nov 2015 13:22:48 +, Aja Huang  wrote:

  Congratulations to Dol Baram!  
I was wondering if Dol Baram's author is reading this list and if he
could kindly give a brief description on his main approaches? From my
observation Dol Baram's style is quite human-like and it reads very
well in life-and-death situations. I suspect Dol Baram combines a
life-and-death solver with the main search.
 
Aja

On Fri, Nov 13, 2015 at 12:30 PM, Rémi Coulom  wrote:

  Thanks Hiroshi. This seems to be a more recent post:

http://51wq.lianzhong.com/Home/NewsDetails?newsID=546=%25e7%2584%25a6%25e7%2582%25b9%25e6%2596%25b0%25e9%2597%25bb

Congratulations to Dol Baram!

Rémi

On 11/13/2015 01:17 PM, Hiroshi Yamashita wrote:

  Hi,

It seems DolBaram won. (from last photo on web)

1st DolBaram
2nd Zen
3rd ManyFaces of Go
4th Ray
http://51wq.lianzhong.com/Home/NewsDetails?newsID=539=%25e7%2584%25a6%25e7%2582%25b9%25e6%2596%25b0%25e9%2597%25bb

Hiroshi Yamashita

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-

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Re: [Computer-go] Mylin Valley The World Computer Weiqi Tournament

[fotland]

The result of the top four single elimination tournament was the same
order as the preliminary round robin.
 
Ray is quite strong, and only 18 months old.  Many Faces played it
twice, in the round robin, and in the final.  In the final it was
quite far ahead in the middle game, but missed a cut, allowing MF to
make the game close, then MF outplayed it in the endgame and won.
 
David

On Fri, 13 Nov 2015 21:17:23 +0900, Hiroshi Yamashita  wrote:

  Hi,

It seems DolBaram won. (from last photo on web)

1st DolBaram
2nd Zen
3rd ManyFaces of Go
4th Ray
http://51wq.lianzhong.com/Home/NewsDetails?newsID=539=%25e7%2584%25a6%25e7%2582%25b9%25e6%2596%25b0%25e9%2597%25bb

Hiroshi Yamashita

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Re: [Computer-go] Frisbee Go Simulation

[Josef Moudrik]

>
> (effectively) zero. Therefore epsilon should be pretty tiny. It must be
> large enough that there is a chance of the frisbee being at least 50% over
> the line (i.e. epsilon > 0), but small enough that the chance of it going
> 70.7% over the line is vanishingly small (otherwise we would be allowing it
> to be displaced onto the diagonally adjacent positions).
>

I do not understand, I think that we do not need to ensure that the stone
cannot land diagonally by small epsilon, since ingo defined it s.t. it
cannot. Having small epsilon as you suggest makes any attempts at writing a
specialized frisbee-go code not really fruitful, since the displacement is
quite rare; so realistically, with small epsilon, no-one would probably
bother to do anything different than to run current programs unchanged.

I think that frisbee-go is much interesting for larger epsilons - e.g. 1/8,
1/6 - because it has nontrivial strategical/tactical implications. For
instance, seki are no longer sekis in this setting, since the loosing party
can always improve its expected outcome by trying to be lucky, and
therefore the winning side can do the same (of course sometimes this is
quite like starting the "1 year ko"). Also when the game ends each dame
is essentially assigned "randomly", so under chinese rules score can
"change randomly". Moreover, larger epsilons change the game's dynamic s.t.
it is easier to live and harder to kill (hypothesis). Another thing is that
the MCTS might work much better with this setting (since random playouts
are much more true).

ingo: One note for rules (you should add) is that when players throw stone
to a location where the probability of landing on a valid location is
exactly zero (all 5 positions are stones or invalid) this counts as a pass
(otw, the loosing party might play the "non-voluntary pass" moves and make
the game infinite. (sorry if I overlooked someone mentioning this already)

Regards,
Josef
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Re: [Computer-go] Frisbee Go Simulation

[Ingo Althöfer]

Hi David,  hi all,

thanks for all the constructive feedback. I will reply later in detail.

We are in Berlin. When returning to the hotel shortly past midnight,  
the hungarian flag was at halfmast. Then we saw the terrible news
from Paris. Berlin is suffering vicariously with the people in Paris.
 
Ingo.


Gesendet: Samstag, 14. November 2015 um 04:55 Uhr
Von: fotl...@smart-games.com
An: computer-go@computer-go.org
Betreff: Re: [Computer-go] Frisbee Go Simulation
Attached is a frisbee go game 9x9 between me and a Chines 5-dan amateur.  50% 
chance of playing in the intended spot.  When a connection is required, it is 
just up to chance who wins the fight.  It's a little silly, but was a lot of 
fun to play.
 
David

On Wed, 11 Nov 2015 23:13:51 +0100, "Ingo Althöfer" <3-hirn-ver...@gmx.de> 
wrote:
Hmm.


> >> Would the game end after two unintentional passes?
>
> > Good point. In principle I would say so.
>
> That makes little sense to me.
> IMO, the principled rule is that two consecutive intentional passes
> end the game.

We should have some test games to see how long a game would be
"typically" stretched by unintended passes.


Ingo.
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Re: [Computer-go] Standard Computer Go Datasets - Proposal

[Petr Baudis]

  Hi!

On Fri, Nov 13, 2015 at 09:46:54AM +, Darren Cook wrote:
> (I did wonder about storing player ranks, e.g. if a given position has a
> move chosen by only a single 9p, and you can then extract each follow-up
> position, you could extract a game. But, IMHO, you cannot regenerate any
> particular game collection this way. If it is a concern, it can be
> solved by only using a random 80% of moves from games.)

  Dropping player names and some positions is a nice idea - especially,
from a moral standpoint, if the collection includes a prominent notice
encouraging voluntary donations by the users to the source collection,
e.g. GoGoD.

  (A technical notice: you want info about last + second-to-last move
in the position as that's a feature that's often used in patterns.
Plus, bridging over just a 1-3 moves seems pretty easy to do by brute
force.  A better scheme might be to drop, say, a block of 20 moves
starting at move 40-80 at random.)

  I think a good question is what other uses besides learning move
patterns do people envision.

-- 
Petr Baudis
If you have good ideas, good data and fast computers,
you can do almost anything. -- Geoffrey Hinton
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Re: [Computer-go] Standard Computer Go Datasets - Proposal

[Josef Moudrik]

On Fri, Nov 13, 2015 at 11:16 AM Erik van der Werf 
wrote:

> On Fri, Nov 13, 2015 at 10:46 AM, Darren Cook  wrote:
>>
>> The advantages of storing games:
>>   * accountability/traceability
>>   * for programs who want to learn sequences of moves.
>>
>
> Another advantage of storing games is that it is much more efficient; you
> only have to encode one move per position.
>
> Erik
>

Yes,
I think that having full games would be much more useful. The anonymization
of the I had in mind would include hiding information not important for
computer processing such as file-names, player names, dates, ranks,
comments (given that the dataset would ensure consistent "balanced"
distribution). Like this, the database would have no (or much less) use for
human study.
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Re: [Computer-go] Scraping lower-ranked games from kgs

[Arthur Cater]

Thank you Josef for that script.

> 
> If you want to download more players, you need to search through opponents of 
> players you know. But do not spam the kgs server too much please :-)
> 

Point taken, I would not want to spoil the kgs experience for users.
I think a few hundred a day would be easily handled, after all I’ve heard it 
said
that approx 25k games a day are played on it. Clearly if I tried to download
all games from say 2010 onward in one go that would be horrendous and
most uncivilised of me.

Arthur


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Re: [Computer-go] Mylin Valley The World Computer Weiqi Tournament

[Rémi Coulom]

Thanks Hiroshi. This seems to be a more recent post:

http://51wq.lianzhong.com/Home/NewsDetails?newsID=546=%25e7%2584%25a6%25e7%2582%25b9%25e6%2596%25b0%25e9%2597%25bb

Congratulations to Dol Baram!

Rémi

On 11/13/2015 01:17 PM, Hiroshi Yamashita wrote:

Hi,

It seems DolBaram won. (from last photo on web)

1st DolBaram
2nd Zen
3rd ManyFaces of Go
4th Ray
http://51wq.lianzhong.com/Home/NewsDetails?newsID=539=%25e7%2584%25a6%25e7%2582%25b9%25e6%2596%25b0%25e9%2597%25bb 



Hiroshi Yamashita

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