RE: [computer-go] Rank on servers at 9x9

2010-02-14 Thread David Fotland

Many Faces has the same issue.  The pruning and tuning that is required for
19x19  doesn't help 9x9.  It seems that now the programs are strong enough
that 9x9 requires a good opening book, and I'd rather spend my time making
19x19 stronger.

David

 
 Zen's algorithm is getting heavier and heavier. It works well on 19x19
 but does not so on 9x9. 
 --
 Yamato
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Re: [computer-go] Rank on servers at 9x9

2010-02-13 Thread Darren Cook
 The difference between ManyFaces blitz and slow is also a lovely gem of
 information. A quick check shows both accounts are playing a lot of
 
 I have a data about this.
 AyaMC4 and AyaMC play on same condition, but it is not for human.
  AyaMC4 is blitz.
 
 Human is about 1 rank weaker in blitz.

Hi Hiroshi,
That is interesting; can I just check I've not misunderstood? You are
saying that humans play about 1 rank (more precisely, 0.7 ranks) weaker
when playing blitz against a fixed strength opponent?

Going back to the Many Faces blitz (1.8d) and slow (0.6d), suggests that
ManyFaces playing blitz against a human playing at slow time levels
would be 1.8d - 0.7 = 1.1d. I.e. ManyFaces *loses* half a rank by
thinking more :-)

That is unlikely to be the case, implying people lose more strength
playing blitz? In the Aya experiment I wonder if people playing slowly
against a fast opponent tend to speed up and not use all their thinking
time?

Darren

P.S. Using your last year's data, the difference is 1.2 ranks, which
exactly matches the ManyFaces data, but still suggests ManyFaces gets no
benefit from thinking more.


 AyaMC4  1k (0.1k) 10sec/mov (8cores)  1minute  + 15sec byoyomi (x10)
 AyaMC   1k (0.8k) 10sec/mov (8cores) 10minutes + 30sec byoyomi (x5)
 AyaMC2  3k (2.6k) 1 playouts 10minutes + 30sec byoyomi (x5)
 AyaBot2 4k (3.6k)  5000 playouts 10minutes + 30sec byoyomi (x5)
 AyaBot4 5k (4.6k)  5000 playouts 10minutes + 30sec byoyomi (x5)
 
 These are last year's data,
 
 AyaMC4  2k (1.4k) 10sec/mov (8cores)  1minute  + 15sec byoyomi (x10)
 AyaMC   3k (2.6k) 10sec/mov (8cores) 10minutes + 30sec byoyomi (x5)
 (about 16 playouts/mov)


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Specializing in intelligent search (in multiple languages), discovery
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Re: [computer-go] Rank on servers at 9x9

2010-02-12 Thread Hiroshi Yamashita

I think we can guess something from CGOS rating.
I made a table about CGOS and KGS bot rating.
At least in 19x19, CGOS and KGS rank is similar.


CGOS  KGS? CGOS 9x9  CGOS 19x19 KGS rank 19x19

1800  6k   gnugo3.7.10   gnugo3.7.106k GnuGo  (postneo, etc)
1900  5k
2000  4k
2100  3k Aya693c_1c 3k AyaMC2 (10k playouts)
2200  2k   Aya693a_10k  2k pachi2
2300  1k pachi-c919f1k ManyFaces  (30minutes)
2400  1d mfgo12-610-2c  1d ManyFaces1 (10sec blitz)
2500  2d   Aya693_1c Zen-4.9-1c 2d Zen19 Zen  (15sec/move)
2600  3d   Fuego-1095-1c
2700  4d   Zen-4.9-1c
2800  5d   Zengg9-4x4c
2900  6d

Hiroshi Yamashita


- Original Message - 
From: Darren Cook dar...@dcook.org

To: computer-go computer-go@computer-go.org
Sent: Friday, February 12, 2010 4:43 PM
Subject: [computer-go] Rank on servers at 9x9



Do any of the strongest MCTS programs have a rank at 9x9 on any major
server? I found the fuego9 account on KGS but it appears to be
unranked and only playing free games (*). The ManyFaces account
appears to play only 19x19.

I know the programs are stronger at 9x9 than 19x19, but I'm trying to
get a figure of just exactly how strong they are against humans of known
rank. Ideally in a statistically meaningful way (not just a short series
of games against one player), and on non-supercomputer hardware.

Thanks in advance,

Darren

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Re: [computer-go] Rank on servers at 9x9

2010-02-12 Thread Darren Cook
Thanks for all the replies! It is much appreciated.

Hiroshi Yamashita wrote:
 I think we can guess something from CGOS rating.
 I made a table about CGOS and KGS bot rating.
 At least in 19x19, CGOS and KGS rank is similar.

That is a very interesting table. It is curious that Zen is only 2 ranks
higher on 9x9. However Aya is 4 ranks higher and Fuego [1] is about 2kyu
on KGS, so (if KGS and CGOS 19x19 correspond for it too, then) also 4
ranks higher.

The difference between ManyFaces blitz and slow is also a lovely gem of
information. A quick check shows both accounts are playing a lot of
games, so this should be statistically significant; the ranking charts
are hard to read, but it looks like 1 to 1.5 ranks difference. (Is there
a way on KGS to get the underlying rating number?)

Darren



 
 
 CGOS  KGS? CGOS 9x9  CGOS 19x19 KGS rank 19x19
 
 1800  6k   gnugo3.7.10   gnugo3.7.106k GnuGo  (postneo, etc)
 1900  5k
 2000  4k
 2100  3k Aya693c_1c 3k AyaMC2 (10k playouts)
 2200  2k   Aya693a_10k  2k pachi2
 2300  1k pachi-c919f1k ManyFaces  (30minutes)
 2400  1d mfgo12-610-2c  1d ManyFaces1 (10sec blitz)
 2500  2d   Aya693_1c Zen-4.9-1c 2d Zen19 Zen  (15sec/move)
 2600  3d   Fuego-1095-1c
 2700  4d   Zen-4.9-1c
 2800  5d   Zengg9-4x4c
 2900  6d
 
 Hiroshi Yamashita


[1]: http://www.gokgs.com/graphPage.jsp?user=Fuego


-- 
Darren Cook, Software Researcher/Developer

Specializing in intelligent search (in multiple languages), discovery
of context, aiding communication, and basically helping people find
and make good use of their data.

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http://dcook.org/mlsn/ (Multilingual open source semantic network)
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Re: [computer-go] Rank on servers at 9x9

2010-02-12 Thread Petr Baudis
On Fri, Feb 12, 2010 at 10:08:07PM +0900, Darren Cook wrote:
 Thanks for all the replies! It is much appreciated.
 
 Hiroshi Yamashita wrote:
  I think we can guess something from CGOS rating.
  I made a table about CGOS and KGS bot rating.
  At least in 19x19, CGOS and KGS rank is similar.
 
 That is a very interesting table. It is curious that Zen is only 2 ranks
 higher on 9x9. However Aya is 4 ranks higher and Fuego [1] is about 2kyu
 on KGS, so (if KGS and CGOS 19x19 correspond for it too, then) also 4
 ranks higher.

I guess that this is because the higher your rating is, the more
difficult it is to get even stronger. ;-)

 The difference between ManyFaces blitz and slow is also a lovely gem of
 information.
  2300  1k pachi-c919f1k ManyFaces  (30minutes)
  2400  1d mfgo12-610-2c  1d ManyFaces1 (10sec blitz)

My guess is that this is caused by huge amount of domain-knowledge from
classical ManyFaces used to prune the tree initially - that gives big
constant boost against MCTS bots with equal thinking time, but with
additional time this does not contribute anything anymore and MFGo
scales similarly to other MCTS bots. At least that's my interpretation,
I wonder what David Fotland thinks about it. (Another factor is that
10sec blitz is much more prone for the human opponents to lose on time.)

 A quick check shows both accounts are playing a lot of
 games, so this should be statistically significant; the ranking charts
 are hard to read, but it looks like 1 to 1.5 ranks difference. (Is there
 a way on KGS to get the underlying rating number?)

In your graphical editor from the rank graph, perhaps. ;-)

-- 
Petr Pasky Baudis
A great many people think they are thinking when they are merely
rearranging their prejudices. -- William James
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Re: [computer-go] Rank on servers at 9x9

2010-02-12 Thread Darren Cook
 The difference between ManyFaces blitz and slow is also a lovely gem of
 information.
 2300  1k pachi-c919f1k ManyFaces  (30minutes)
 2400  1d mfgo12-610-2c  1d ManyFaces1 (10sec blitz)
 
 My guess is that this is caused by huge amount of domain-knowledge from
 classical ManyFaces used to prune the tree initially - that gives big
 constant boost against MCTS bots with equal thinking time, but with
 additional time this does not contribute anything anymore and MFGo
 scales similarly to other MCTS bots.

The above stat was from KGS, not CGOS. So, my thought was: MCTS doesn't
scale with extra thinking time as well as humans do. Which conveniently
matches my hypothesis that MCTS doesn't use extra CPU cycles very
efficiently.

Though, as you say, those foolish humans foolishly managing their blitz
time foolishly does distort things a bit.

Darren


-- 
Darren Cook, Software Researcher/Developer

Specializing in intelligent search (in multiple languages), discovery
of context, aiding communication, and basically helping people find
and make good use of their data.

http://dcook.org/gobet/  (Shodan Go Bet - who will win?)
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Re: [computer-go] Rank on servers at 9x9

2010-02-12 Thread Yamato
Darren Cook wrote:
Hiroshi Yamashita wrote:
 I think we can guess something from CGOS rating.
 I made a table about CGOS and KGS bot rating.
 At least in 19x19, CGOS and KGS rank is similar.

That is a very interesting table. It is curious that Zen is only 2 ranks
higher on 9x9. However Aya is 4 ranks higher and Fuego [1] is about 2kyu
on KGS, so (if KGS and CGOS 19x19 correspond for it too, then) also 4
ranks higher.

Zen's algorithm is getting heavier and heavier. It works well on 19x19
but does not so on 9x9.

Another problem is 7.5 komi. I guess it gives very big advantage to white
for high-dan level players. 7.0 komi would give better results.

--
Yamato
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Re: [computer-go] Rank on servers at 9x9

2010-02-12 Thread Hideki Kato

Darren Cook: 4b7552b7.9060...@dcook.org:
Thanks for all the replies! It is much appreciated.

Hiroshi Yamashita wrote:
 I think we can guess something from CGOS rating.
 I made a table about CGOS and KGS bot rating.
 At least in 19x19, CGOS and KGS rank is similar.

That is a very interesting table. It is curious that Zen is only 2 ranks
higher on 9x9. However Aya is 4 ranks higher and Fuego [1] is about 2kyu
on KGS, so (if KGS and CGOS 19x19 correspond for it too, then) also 4
ranks higher.

Please don't compare the ratings of different versions of programs on 
different hardware.  The rating of Zen (at least version 4.2) on 
CGOS 9x9 is about 3 ranks higher than KGS, although (:-) only 1 rank 
higher than CGOS 19x19.

Followings are the rating and rank of Zengg-4x4c (CGOS) and Zengg19 
(KGS) respectively, though the games for Zengg19 aren't many 
enough.  Zengg-4x4c and Zengg19 share the same code based on 
Zen-4.2 and hardware (a cluster of 4 quad-core PCs).

CGOS 9x9 bayeselo   2919+75-64
CGOS 19x19 bayeselo 2830+80-71
KGS 19x19   3d

I don't know why Hirosi didn't use bayeselo for the ratings on 
CGOS, which should give more reliable rating numbers.  Below is 
another table using bayeselo.
http://cgos.boardspace.net/9x9/bayes.html
http://cgos.boardspace.net/19x19/bayes.html

CGOS 9x9CGOS 19x19  KGS 19x19
GNU Go v3.7.10 lvl101805+7-61800 (ref)  6k
Aya693_1c   2493+-742175+-443k AyaMC2 (10k po)  

Fuego svn1095 1c2629+-22
Fuego svn1095 2c2150+31-30
Fuego svn1089 8c2759+86-71  2353+-141   2k Fuego?
Zen v4.9 1c 2795+74-68  2716+210-146
Zen v4.9 8c 2d Zen19? (15sec/move)
Zengg (v4.2) 4x4c   2919+75-64  2830+80-71  3d Zengg19 
(20:00+5x0:30)

Note that Zen19 (KGS) runs on an 8-core MacPro while Zen-4.9-1c ran 
on just one core.  I also wonder if Zen19 and Fuego on KGS are v4.9 
and svn1089, respectively.

Watching the ratings of GNU Go and Zengg on CGOS 19x19 and KGS in 
above table, they don't scale the same, say, 6k to 3d should be plus 
800 Elo but is 1000 Elo on CGOS.

Hideki

The difference between ManyFaces blitz and slow is also a lovely gem of
information. A quick check shows both accounts are playing a lot of
games, so this should be statistically significant; the ranking charts
are hard to read, but it looks like 1 to 1.5 ranks difference. (Is there
a way on KGS to get the underlying rating number?)

Darren



 
 
 CGOS  KGS? CGOS 9x9  CGOS 19x19 KGS rank 19x19
 
 1800  6k   gnugo3.7.10   gnugo3.7.106k GnuGo  (postneo, etc)
 1900  5k
 2000  4k
 2100  3k Aya693c_1c 3k AyaMC2 (10k playouts)
 2200  2k   Aya693a_10k  2k pachi2
 2300  1k pachi-c919f1k ManyFaces  (30minutes)
 2400  1d mfgo12-610-2c  1d ManyFaces1 (10sec blitz)
 2500  2d   Aya693_1c Zen-4.9-1c 2d Zen19 Zen  (15sec/move)
 2600  3d   Fuego-1095-1c
 2700  4d   Zen-4.9-1c
 2800  5d   Zengg9-4x4c
 2900  6d
 
 Hiroshi Yamashita


[1]: http://www.gokgs.com/graphPage.jsp?user=Fuego


-- 
Darren Cook, Software Researcher/Developer

Specializing in intelligent search (in multiple languages), discovery
of context, aiding communication, and basically helping people find
and make good use of their data.

http://dcook.org/gobet/  (Shodan Go Bet - who will win?)
http://dcook.org/mlsn/ (Multilingual open source semantic network)
http://dcook.org/work/ (About me and my work)
http://dcook.org/blogs.html (My blogs and articles)
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