Re: [computer-go] Can a computer beat a human?

2007-01-23 Thread David Doshay
At the Cotsen Open 1.5 years ago SlugGo beat an 8k, and lost on time  
to his 8k brother, but the board position was a win by more than 100  
points for SlugGo. But I agree that 10k is about right; SlugGo also  
lost to a few 12k players.


I also agree that picking up 4 stones seems within reach, even though  
I have not quite pulled that off ... yet.


To beat any pro player is going to take a breakthrough and probably a  
new method. It is just a little early to tell if MC is that method,  
but it seems to scale well, so it may be. If the required new method  
is not MC, then it is impossible to know when that breakthrough will  
happen, because by its nature, it is not going to simply evolve out  
of what we are doing now, but requires some new insight.


Cheers,
David



On 23, Jan 2007, at 10:17 PM, Ray Tayek wrote:

the programs seem to be about 10-kyu (based on my observations of  
slugo and smart go at the cotsen open and manyfaces on my pc). 32gb/ 
300 mhz is probably about 3gb/3ghz. so they can beat some 11-kyu  
humans.


my suspicion is that the programs could play a few (4?) stones  
stronger with better heuristics and less brute force (except in the  
end game).


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Re: [computer-go] Can a computer beat a human?

2007-01-23 Thread Ray Tayek

At 01:51 PM 1/23/2007, you wrote:

Let me clear one thing up...  I mean, a professional go player. ...


this would be equivalent to somewhere between 7-10 dan amateur.

at least decades. probably much longer. (at least without quantum stuff).

thanks


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Re: [computer-go] Can a computer beat a human?

2007-01-23 Thread Ray Tayek

At 01:22 PM 1/23/2007, you wrote:
...  It plays the best game you could ever program it to play.  How 
fast would the computer have to be to beat a human?  ... but I would 
say a computer with perfect software, 32 GB of RAM (so a lot) and a 
300 Mhz processor (slow processor) would be able to beat a human.


the programs seem to be about 10-kyu (based on my observations of 
slugo and smart go at the cotsen open and manyfaces on my pc). 
32gb/300 mhz is probably about 3gb/3ghz. so they can beat some 11-kyu humans.


my suspicion is that the programs could play a few (4?) stones 
stronger with better heuristics and less brute force (except in the end game).


thanks

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Re: [computer-go] Best computer go development library?

2007-01-23 Thread Phil G
Here are a few:
 
PubGo+ is a set of C++ classes for Go Programming by P. J. Leonard. It is 
published under the GPL. 
Effective Go Board Library by Łukasz Lew (he's active on this list).
HouseBot is an open source C++ program for playing the game of go (which I'm a 
developer on).
 
I have been developing a computer go program in C# using Microsoft Visual 
Studio and Mono.  It has most of the basics: board/stone/chain/region 
management + undo, pattern matching, Benson, final scoring, Computer Go 
Protocol (GTP), Smart Go Format (SGF), direct CGOS interface, etc. I would be 
willing to share the source code for research purposes. Contact me directly, if 
interested. Eventually I'll probably release the C# code to GPL or LGPL. Small 
parts of the original C++ code (and backported code from C# to C++) are already 
available from the HouseBot SVN which is GPL.
 
Phil
 
- Original Message 
From: Thomas Johnson <[EMAIL PROTECTED]>
To: computer-go@computer-go.org
Sent: Tuesday, January 23, 2007 2:52:34 PM
Subject: [computer-go] Best computer go development library?


Hi folks,

I'm interested in doing some experiments in developing a computer go algorithm. 
I definitely don't want to rewrite any of the basic stuff (board management, 
scoring, etc) if it's already available somewhere. What's the best library 
available (if any) for doing this kind of thing? If it makes a difference, I'll 
probably be writing in C++ on Linux or C# on Windows, depending on the software 
available for each. 

Thanks
Tom 


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Re: [computer-go] Can a computer beat a human?

2007-01-23 Thread Hideki Kato
I strongly believe it's not hardware but software (ie. when we will 
develop  a strong enough algorithm) issue.

- gg

Nick Apperson: <[EMAIL PROTECTED]>:
>Let me clear one thing up...  I mean, a professional go player.  A rough
>approximation of what the human brain is capable of when it is optimized for
>go compared with a computer that has its software optimized (not limited by
>programming ability and programmer time) for go.
>
>On 1/23/07, Joshua Shriver <[EMAIL PROTECTED]> wrote:
>>
>> My 500mhz computer beats me fairly easy ;) with Gnugo so depends on
>> the person you're comparing.
>>
>> -Josh
>>
>> On 1/23/07, Nick Apperson <[EMAIL PROTECTED]> wrote:
>> > This is something I have been wrestling with.  It is kind of a
>> theoretical
>> > question.  Assuming a program that utilizes all avaliable resources
>> > perfectly.  It plays the best game you could ever program it to
>> play.  How
>> > fast would the computer have to be to beat a human?  I could see people
>> > argue that if the program had enough knowledge it could be a pretty slow
>> > computer (less than 100 Mhz), I could also see someone state the reality
>> > that our brains (when you sum up the computational power of an entire
>> > thinking brain) have way more processing power than a cluster of high
>> > performance workstations and so technology isn't able to provide
>> computer
>> > hardware that would be fast enough.  I think I vastly underestimate the
>> > human brain, but I would say a computer with perfect software, 32 GB of
>> RAM
>> > (so a lot) and a 300 Mhz processor (slow processor) would be able to
>> beat a
>> > human.  Thoughts?
>> >
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>> >
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Re: [computer-go] an idea for a new measure of a computer go program's rank.

2007-01-23 Thread Weston Markham

Personally, I use the terminology in much the same way as Heikki.  I
use the word "mistake" to describe (for example) a move that loses a
large group, but does not change the game from a win to a loss.  It
makes sense to me to generally apply "mistake" to any move that loses
points relative to the best move on the board.  The term "blunder"
means, essentially, a move that lost the game.  It can be quite
difficult, of course, to determine unambiguously whether or not a
particular move is a blunder.  In an otherwise close match, a large
mistake (i.e., loses many points) is probably a blunder.  Toward the
end of a close game, it may be possible to find unambiguous blunders,
and some of these could be single point mistakes.

Weston

On 1/23/07, Heikki Levanto <[EMAIL PROTECTED]> wrote:

On Sun, Jan 21, 2007 at 08:16:07PM -0800, Ray Tayek wrote:
> >I don't know the percentage of blunders. It also depends on what you
> >call a blunder. Is a 1 point mistake a blunder?
>
> no, maybe 10 or more points

My gut feeling is that a real blunder is enough to loose the game.
Between equally strong players, a one point mistake can be a blunder, if
it was late in the yose, and the game was won by half a point. On the
other hand, throwing away a 20-stone group may not be a blunder if you
were already going to loose by 100 points. It could even be a
(mis?)calculated risk, ignoring a threatening move in order to get an
attack on an even larger group, even if that attack later turns out not
to work...

Just my uninformed gut feeling, of course.

-H

--
Heikki Levanto   "In Murphy We Turst" heikki (at) lsd (dot) dk

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[computer-go] Best computer go development library?

2007-01-23 Thread Thomas Johnson

Hi folks,

I'm interested in doing some experiments in developing a computer go
algorithm. I definitely don't want to rewrite any of the basic stuff (board
management, scoring, etc) if it's already available somewhere. What's the
best library available (if any) for doing this kind of thing? If it makes a
difference, I'll probably be writing in C++ on Linux or C# on Windows,
depending on the software available for each.

Thanks
Tom
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Re: [computer-go] Can a computer beat a human?

2007-01-23 Thread Don Dailey
On Tue, 2007-01-23 at 15:22 -0600, Nick Apperson wrote:
> This is something I have been wrestling with.  It is kind of a
> theoretical question.  Assuming a program that utilizes all avaliable
> resources perfectly.  It plays the best game you could ever program it
> to play.  How fast would the computer have to be to beat a human?  I
> could see people argue that if the program had enough knowledge it
> could be a pretty slow computer (less than 100 Mhz), I could also see
> someone state the reality that our brains (when you sum up the
> computational power of an entire thinking brain) have way more
> processing power than a cluster of high performance workstations and
> so technology isn't able to provide computer hardware that would be
> fast enough.  I think I vastly underestimate the human brain, but I
> would say a computer with perfect software, 32 GB of RAM (so a lot)
> and a 300 Mhz processor (slow processor) would be able to beat a
> human.  Thoughts? 

Excellent question.  So you really mean,  if God would program a
computer
to be as strong as possible would it beat humans at human-like
time-controls?

It's obvious that you can't program a 10 instruction per second computer
to beat a human - so it's also clear that there would be some minimum 
level of hardware required.  

I could make a guess, but I certainly don't trust my intuition here.
My guess is that God could program a core 2 duo system of today to
beat a strong human.

- Don


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Re: [computer-go] Can a computer beat a human?

2007-01-23 Thread Nick Apperson

Let me clear one thing up...  I mean, a professional go player.  A rough
approximation of what the human brain is capable of when it is optimized for
go compared with a computer that has its software optimized (not limited by
programming ability and programmer time) for go.

On 1/23/07, Joshua Shriver <[EMAIL PROTECTED]> wrote:


My 500mhz computer beats me fairly easy ;) with Gnugo so depends on
the person you're comparing.

-Josh

On 1/23/07, Nick Apperson <[EMAIL PROTECTED]> wrote:
> This is something I have been wrestling with.  It is kind of a
theoretical
> question.  Assuming a program that utilizes all avaliable resources
> perfectly.  It plays the best game you could ever program it to
play.  How
> fast would the computer have to be to beat a human?  I could see people
> argue that if the program had enough knowledge it could be a pretty slow
> computer (less than 100 Mhz), I could also see someone state the reality
> that our brains (when you sum up the computational power of an entire
> thinking brain) have way more processing power than a cluster of high
> performance workstations and so technology isn't able to provide
computer
> hardware that would be fast enough.  I think I vastly underestimate the
> human brain, but I would say a computer with perfect software, 32 GB of
RAM
> (so a lot) and a 300 Mhz processor (slow processor) would be able to
beat a
> human.  Thoughts?
>
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Re: [computer-go] Re: libgoboard v0.97 released

2007-01-23 Thread Heikki Levanto
On Tue, Jan 23, 2007 at 10:35:08PM +0100, Heikki Levanto wrote:
> I just downloaded it and had a quick look.

Perfect timing - while I was writing my mail, you released 0.98
That works much more better. Now I get something like


playout_benchmark 100
=
Initial board:
komi 7
A  B  C  D  E  F  G  H  J
 9  .  .  .  .  .  .  .  .  .  9
 8  .  .  .  .  .  .  .  .  .  8
 7  .  #  O  #  .  .  .  .  .  7
 6  .  .  #  #  .  .  .  .  .  6
 5  .  .  .  .  .  #  .  O  .  5
 4  .  .  .  .  .  #  O  .  O  4
 3  .  .  #  .  .  #  #  O  .  3
 2  .  .  .  .  #  .  #  O  .  2
 1  .  .  .  .  .  #  .  .  .  1
A  B  C  D  E  F  G  H  J
Performance:
  100 playouts
  13.3568 seconds
  74.868 kpps
Black wins = 890260
White wins = 109740
P(black win) = 0.89026



Much more reasonable number of wins for both players, P in range, and
seems to correlate with the the position.  Problem solved.

Now I just need the time to play with it all...

- Heikki

P.S. and better n umbers too, once I got my cpufreq scaling to give me
full cpu speed when needed...

-- 
Heikki Levanto   "In Murphy We Turst" heikki (at) lsd (dot) dk

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Re: [computer-go] an idea... computer go program's rank vs time

2007-01-23 Thread Don Dailey
On Tue, 2007-01-23 at 21:08 +0100, [EMAIL PROTECTED] wrote:
> Yes. Don's scalability argument states that ELO gain is proportional 
> to time doubling.
> For me scalable use of time implies that time translates into depth.
> The extra depth is:
> 
> m - m0 = log(2)/log(b). 
> 
> So if the ELO gain for time doubling in Chess equals 100 over a wide 
> time scale and if Go has a 10 times larger branching factor than 
> Chess, then the ELO gain for time doubling in Go would equal 100/log
> (10) = 43 (everything else assumed equal).
> 
> I'm not sure i agree with Don, but i just want so say that if he is 
> right, than mathematically he is also right with a larger branching 
> factor.

It's trivial to prove programs are infinitely scalable.   It's a 
bit more difficult to prove humans are - but I think it's probably 
a similar proof.  

I believe a scalable program can be "highly scalable" or "less scalable"
meaning they improve less or more with time.   Humans appear to be of
the "highly scalable" variety, at least in chess they improve with time
faster than computers do.   A chess program playing at 3 minutes per
move is about 300 ELO stronger than the same program playing at 5 
seconds per move.   A human is more like 400-500 ELO stronger.  

There is strong evidence that in chess this doubling tapers off
at strong levels.  This makes a great deal of sense.   Ernst Heinz
did some experiments that proved empirically (with high statistical
confidence) that strength tapers off with search depth in computers.
Although he measured this using search depth,  I believe the tapering
is more related to strength.  It just happens that the deeper searching
programs were playing stronger.   If someone could construct a 
computer that played just as well with half the search depth, I think
the tapering would be approximately consistent with the deep searching
program of similar levels.

The tapering is very gradual and even at high ply depths the ELO
improvement for a doubling is quite good.  That's why I believe in
GO it will be hard to see this tapering effect.   I believe GO players
are farther from the ultimate top that chess players (I mean the very
best players.)   Once you are playing almost perfectly,  you won't
get quite as much from the extra thinking time.   

I did an experiment long ago with a checkers-like game I made up.
It is simple checkers on a 6x6 board and only 1 jump allowed.  It's
possible to construct an enormously deep searching program with this
little mini-game.I also found that the really super deep levels
taper off,  and yet it is gradual and you never seem to stop 
benefiting measurably from each additional ply of search.   The 
program searches deep enough that it's easily to imagine that it
can't make errors, but obviously one side is making errors.

The worlds best checkers program are like this too.  They go much
deeper than in chess and they are quite amazing how deeply they
search.   I think they are way beyond human strength now, but they
still lose games to each other and make mistakes that 1 more ply
of search would solve.

That's really the point - 1 extra ply always solves a thick layer of
problems that you couldn't solve before. 
  

- Don
   



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Re: [computer-go] Can a computer beat a human?

2007-01-23 Thread Joshua Shriver

My 500mhz computer beats me fairly easy ;) with Gnugo so depends on
the person you're comparing.

-Josh

On 1/23/07, Nick Apperson <[EMAIL PROTECTED]> wrote:

This is something I have been wrestling with.  It is kind of a theoretical
question.  Assuming a program that utilizes all avaliable resources
perfectly.  It plays the best game you could ever program it to play.  How
fast would the computer have to be to beat a human?  I could see people
argue that if the program had enough knowledge it could be a pretty slow
computer (less than 100 Mhz), I could also see someone state the reality
that our brains (when you sum up the computational power of an entire
thinking brain) have way more processing power than a cluster of high
performance workstations and so technology isn't able to provide computer
hardware that would be fast enough.  I think I vastly underestimate the
human brain, but I would say a computer with perfect software, 32 GB of RAM
(so a lot) and a 300 Mhz processor (slow processor) would be able to beat a
human.  Thoughts?

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Re: [computer-go] Can a computer beat a human?

2007-01-23 Thread dhillismail
 The answer is "yes." Many computer programs (including my own) can beat me 
easily on today's hardware and I am, indeed, a human.
 
 Glad I could clear that up for you. ;-)
 
 - Dave Hillis
 
 

 
-Original Message-
From: [EMAIL PROTECTED]
To: computer-go@computer-go.org
Sent: Tue, 23 Jan 2007 4:22 PM
Subject: [computer-go] Can a computer beat a human?


This is something I have been wrestling with.  It is kind of a theoretical 
question.  Assuming a program that utilizes all avaliable resources perfectly.  
It plays the best game you could ever program it to play.  How fast would the 
computer have to be to beat a human?  I could see people argue that if the 
program had enough knowledge it could be a pretty slow computer (less than 100 
Mhz), I could also see someone state the reality that our brains (when you sum 
up the computational power of an entire thinking brain) have way more 
processing power than a cluster of high performance workstations and so 
technology isn't able to provide computer hardware that would be fast enough.  
I think I vastly underestimate the human brain, but I would say a computer with 
perfect software, 32 GB of RAM (so a lot) and a 300 Mhz processor (slow 
processor) would be able to beat a human.  Thoughts? 

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Re: [computer-go] Re: libgoboard v0.97 released

2007-01-23 Thread Heikki Levanto
On Mon, Jan 22, 2007 at 06:48:34PM +0100, ?ukasz Lew wrote:
> >Few interesting things has happened so I decided to announce new version:

Hi,

I just downloaded it and had a quick look. I am running on a
Debian/etch system, dual-core AMD-64.

Make finished fine, and the program seems to run. engine_opt without
arguments displays an empty 9x9 board and 
Performance:
  20 playouts
  6.25239 seconds
  31.9878 kpps
Black wins = 3086277172
White wins = 3221005275
P(black win) = 1.53369

So far so good.

When I try to load one of the example positions, I get exactly the same
numbers. When I try to add a few more stones to get a totally
unbalanced position, I still get

   Initial board:
   komi 7
   A  B  C  D  E  F  G  H  J
9  .  .  .  .  .  .  .  .  .  9
8  .  .  #  .  .  .  .  .  .  8
7  .  #  O  .  .  .  #  .  .  7
6  .  #  .  #  .  #  .  .  .  6
5  .  .  .  .  .  #  .  O  .  5
4  .  .  .  .  .  #  O  .  O  4
3  .  #  .  .  .  #  #  O  .  3
2  .  .  .  .  #  .  #  O  .  2
1  .  .  .  .  .  #  .  .  .  1
   A  B  C  D  E  F  G  H  J
   Performance:
 10 playouts
 2.68816 seconds
 37.2001 kpps
   Black wins = 3085887684
   White wins = 3220998203
   P(black win) = 1.5338

Obviously I am doing something wrong here, but what?

- Heikki


-- 
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[computer-go] Can a computer beat a human?

2007-01-23 Thread Nick Apperson

This is something I have been wrestling with.  It is kind of a theoretical
question.  Assuming a program that utilizes all avaliable resources
perfectly.  It plays the best game you could ever program it to play.  How
fast would the computer have to be to beat a human?  I could see people
argue that if the program had enough knowledge it could be a pretty slow
computer (less than 100 Mhz), I could also see someone state the reality
that our brains (when you sum up the computational power of an entire
thinking brain) have way more processing power than a cluster of high
performance workstations and so technology isn't able to provide computer
hardware that would be fast enough.  I think I vastly underestimate the
human brain, but I would say a computer with perfect software, 32 GB of RAM
(so a lot) and a 300 Mhz processor (slow processor) would be able to beat a
human.  Thoughts?
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Re: [computer-go] an idea... computer go program's rank vs time

2007-01-23 Thread Nick Apperson

you are right about my math being wrong.  I wasn't paying that much
attention to that step, but with the correct math (as was pointed out) you
end up with a linear equation assuming what I said to assume.  Man, its only
been a couple years and my precalc skills have gone to crap...  Thanks for
the correction.  And Dave, you said what I was trying to say, except
better.  The only thing I have to add is that one major difference between
humans and computers is that brains are able to think in parallel much more
effeciently.  For a game such as go, we are able to use that ability more
because of the larger branching factor.

On 1/23/07, [EMAIL PROTECTED] <[EMAIL PROTECTED]> wrote:


- Oorspronkelijk bericht -
Van: Matt Gokey <[EMAIL PROTECTED]>
Datum: maandag, januari 22, 2007 9:59 pm
Onderwerp: Re: [computer-go] an idea... computer go program's rank vs
time
> Nick Apperson wrote:
>
> > He is saying this (I think):
> >
> > to read m moves deep with a branching factor of b you need to
> look at p
> > positions, where p is given by the following formula:
> >
> > p = b^m (actually slightly different, but this formula is
> close enough)
> >
> > which is:
> >
> > log(p) = m log(b)
> > m = log(p) / log(b)
> >
> > We assume that a doubling in time should double the number of
> positions
> > we can look at, so:
> >
> >
> > m(with doubled time) = log(2p) / log(b)
> > m(with doubled time) = log(2) * log(p) / log(b)
> Your math is wrong (I think).
>
> The correct equivalency for the last line would be:
> m(with doubled time) = (log(2) + log(p)) / log(b)
>

Yes. Don's scalability argument states that ELO gain is proportional
to time doubling.
For me scalable use of time implies that time translates into depth.
The extra depth is:

m - m0 = log(2)/log(b).

So if the ELO gain for time doubling in Chess equals 100 over a wide
time scale and if Go has a 10 times larger branching factor than
Chess, then the ELO gain for time doubling in Go would equal 100/log
(10) = 43 (everything else assumed equal).

I'm not sure i agree with Don, but i just want so say that if he is
right, than mathematically he is also right with a larger branching
factor.

Dave
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Re: [computer-go] an idea for a new measure of a computer go program's rank.

2007-01-23 Thread Heikki Levanto
On Sun, Jan 21, 2007 at 08:16:07PM -0800, Ray Tayek wrote:
> >I don't know the percentage of blunders. It also depends on what you
> >call a blunder. Is a 1 point mistake a blunder?
> 
> no, maybe 10 or more points

My gut feeling is that a real blunder is enough to loose the game.
Between equally strong players, a one point mistake can be a blunder, if
it was late in the yose, and the game was won by half a point. On the
other hand, throwing away a 20-stone group may not be a blunder if you
were already going to loose by 100 points. It could even be a
(mis?)calculated risk, ignoring a threatening move in order to get an
attack on an even larger group, even if that attack later turns out not
to work...

Just my uninformed gut feeling, of course.

-H

-- 
Heikki Levanto   "In Murphy We Turst" heikki (at) lsd (dot) dk

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[computer-go] position

2007-01-23 Thread Thomas Wolf
About 2 months ago I sent a note to this email list about a research chair
position and a postdoc position, both financed through the SHACRNET High
Perfomance Consortium.  The advert below does not have high performance
computing as a requisite attached. But because it mentions discrete math,
combinatorics and experience in computation as valuable strengths, this might
be of interest to someone on the email list. Together with a few students we
already have a small but active computer Go group at our math department.

Thomas Wolf
Prof at Department of Mathematics
Brock University
Ontario, Canada

---

BROCK UNIVERSITY
FACULTY OF MATHEMATICS AND SCIENCES

MATHEMATICS

The Department of Mathematics invites applications for a tenure-track
appointment in an area of discrete and computational mathematics at the rank
of Assistant Professor starting July 1, 2007.

The Department offers an MSc in Mathematics and Statistics, has an innovative
and unique B.Sc. Mathematics program called MICA (Mathematics Integrated with
Computers and Applications) and plays a leading role in Mathematics Education.

The successful candidate must have a PhD in Mathematics or related field by
the time of the appointment, a proven record of or potential for research
excellence, and an active research program that will attract external
funding. Ideally, the candidate’s area of research would complement that of
current faculty.

The position requires undergraduate teaching including Combinatorics and
Mathematics for Computer Science, graduate teaching, and supervision of
graduate students. The successful candidate must demonstrate strong teaching
abilities and a committed interest in the use of technology for the
exploration, understanding and applications of mathematics.

The appointment is subject to the availability of funds. The review of
applications will start on February 28, 2007 and will continue until the
position is filled. Applicants should send a curriculum vitae, an outline of
their research plan and a description of teaching philosophies, and arrange
for at least three letters of reference (one of which should address teaching)
to be sent directly to:

Chair of the Mathematics Search Committee
Department of Mathematics
Brock University
St. Catharines, Ontario
L2S 3A1, Canada
E-mail: [EMAIL PROTECTED]

In accordance with Canadian Immigration requirements, priority will be given
to citizens and permanent residents of Canada. Brock University encourages
applications from all qualified individuals including women, members of
minorities, native people, and persons with disabilities.

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Re: [computer-go] an idea... computer go program's rank vs time

2007-01-23 Thread dave . devos
- Oorspronkelijk bericht -
Van: Matt Gokey <[EMAIL PROTECTED]>
Datum: maandag, januari 22, 2007 9:59 pm
Onderwerp: Re: [computer-go] an idea... computer go program's rank vs 
time
> Nick Apperson wrote: 
> 
> > He is saying this (I think): 
> > 
> > to read m moves deep with a branching factor of b you need to 
> look at p 
> > positions, where p is given by the following formula: 
> > 
> > p = b^m (actually slightly different, but this formula is 
> close enough) 
> > 
> > which is: 
> > 
> > log(p) = m log(b) 
> > m = log(p) / log(b) 
> > 
> > We assume that a doubling in time should double the number of 
> positions 
> > we can look at, so: 
> > 
> > 
> > m(with doubled time) = log(2p) / log(b) 
> > m(with doubled time) = log(2) * log(p) / log(b) 
> Your math is wrong (I think). 
> 
> The correct equivalency for the last line would be: 
> m(with doubled time) = (log(2) + log(p)) / log(b) 
> 

Yes. Don's scalability argument states that ELO gain is proportional 
to time doubling.
For me scalable use of time implies that time translates into depth.
The extra depth is:

m - m0 = log(2)/log(b). 

So if the ELO gain for time doubling in Chess equals 100 over a wide 
time scale and if Go has a 10 times larger branching factor than 
Chess, then the ELO gain for time doubling in Go would equal 100/log
(10) = 43 (everything else assumed equal).

I'm not sure i agree with Don, but i just want so say that if he is 
right, than mathematically he is also right with a larger branching 
factor.

Dave
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Re: [computer-go] Fast Board implementation

2007-01-23 Thread dhillismail
 Here is another MC speedup trick. I think it may have been mentioned 
before but it's worth repeating.
 
 This applies to the case where my program is going to run N playout games 
and then select the most visited node as its move for that turn (which will not 
always be the node with the highest percentage of wins). It is rarely necessary 
to run all N playout games.
 
 After more than half of the playout games have been completed, some moves 
may become mathematically eliminated because they have been visited too few 
times for them to be able to catch up to the leader. So, at regular intervals 
thereafter, I can perform a popularity pruning operation at the root. If there 
are M playout games to go, and a move at the root would need more than M more 
visits to catch up with the most popular (visited) move, then any further 
playout games through that move would be wasted. I might as well prune it now. 
When all but one move at the root has been pruned away, no further playout 
games are needed for this turn. Popularity pruning averages to about a 20% 
speedup free and clear.
 
 Of course, one can prune a move at the root a little earlier, or prune 
moves beyond the root, but then you have moved into a different regime.
 
- Dave Hillis
antminder on KGS

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Re: [computer-go] Go Board Library v0.98

2007-01-23 Thread Łukasz Lew

Thanks.
This is fixed in v 0.98

Łukasz

On 1/23/07, terry mcintyre <[EMAIL PROTECTED]> wrote:


I was able to reproduce the problem with the odd "White Wins" value.

Turns out that win_cnt was not initialized in playout_benchmark. Adding an
explicit
initialization fixed that problem. My c++ is extremely rusty, so I used
  win_cnt[0]=0;
  win_cnt[1]=0;

There is probably a c++ specific idiom which I am unaware of.
 Terry McIntyre


- Original Message 
From: Łukasz Lew <[EMAIL PROTECTED]>
To: computer-go 
Sent: Tuesday, January 23, 2007 8:17:40 AM
Subject: [computer-go] Go Board Library v0.98

I will annoy You once again, because:

I added a mercy rule to the simple playout, and it turned out that it
is *faster* that my previous mega-optimised playout.

In current release old playout_t is gone, we have only simple_playout::run.
Some beautification, and helpful macros.
Also whole package is much more user friendly (README, automagic.gtp).

http://duch.mimuw.edu.pl/~lew/download.php?file_no=9

Best Regards,
Łukasz Lew
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Re: [computer-go] Go Board Library v0.98

2007-01-23 Thread terry mcintyre
I was able to reproduce the problem with the odd "White Wins" value.

Turns out that win_cnt was not initialized in playout_benchmark. Adding an 
explicit
initialization fixed that problem. My c++ is extremely rusty, so I used 
  win_cnt[0]=0;
  win_cnt[1]=0;

There is probably a c++ specific idiom which I am unaware of.
 
Terry McIntyre

- Original Message 
From: Łukasz Lew <[EMAIL PROTECTED]>
To: computer-go 
Sent: Tuesday, January 23, 2007 8:17:40 AM
Subject: [computer-go] Go Board Library v0.98

I will annoy You once again, because:

I added a mercy rule to the simple playout, and it turned out that it
is *faster* that my previous mega-optimised playout.

In current release old playout_t is gone, we have only simple_playout::run.
Some beautification, and helpful macros.
Also whole package is much more user friendly (README, automagic.gtp).

http://duch.mimuw.edu.pl/~lew/download.php?file_no=9

Best Regards,
Łukasz Lew

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[computer-go] Go Board Library v0.98

2007-01-23 Thread Łukasz Lew

I will annoy You once again, because:

I added a mercy rule to the simple playout, and it turned out that it
is *faster* that my previous mega-optimised playout.

In current release old playout_t is gone, we have only simple_playout::run.
Some beautification, and helpful macros.
Also whole package is much more user friendly (README, automagic.gtp).

http://duch.mimuw.edu.pl/~lew/download.php?file_no=9

Best Regards,
Łukasz Lew
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Re: [computer-go] Re: libgoboard v0.97 released

2007-01-23 Thread Łukasz Lew

On 1/22/07, David Doshay <[EMAIL PROTECTED]> wrote:

Randomization of seed may not be a good idea. For some experiments it
is better to know the starting seed and keep it the same, for others,
like play against humans, randomization is probably preferable.

I would suggest having a runtime flag that can be set either way.

Cheers,
David



You are right, I will do something like that in next release.
Thanks
Lukasz




On 22, Jan 2007, at 2:01 PM, Łukasz Lew wrote:

>> On Cygwin, the results are ok and always the same.
>
> I will add randomization of seed.
>

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