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Re: [computer-go] ANN(s) playing a perfect game...
Campbell,
You can find one part of what I am working on, the part I have matured
enough to release under the GPL:
http://sourceforge.org/projects/semiann
It is my first public iteration. I did several private iterations. It
is optimized for the Sun and IBM JVM JIT(HotSpot) compilers. If you
have any comments on it, let me know. I have had other priorities come
up that have taken me away from this project for a month. I hope to
return in early January. 'Tis the season of many distractions.
As I progress through parts and mature them for public consumption, I
will release them under the GPL on sourceforge. No point in having
people reinvent the low level crap, at least if they are working in Java
(regardless of Diep's closed view of the world). It works better if
more of us are working at higher levels on actual interesting problems
as opposed to lower level optimizations. I am convinced the Go
breakthrough(s) are all at way higher levels than the myopic discussions
about tactics that seem to predominate discussions (mainly because that
is what is more readily achievable given the strong influence of
traditional Boolean methods).
I will likely hop on board David Weiss's Moyoman once I am preparing a
client to play in tournaments, etc.. I have no interest in UIs, Go comm
protocols or any of the low level boring rote programming crap. I am
very thankful David has chosen to handle all of that for me.
Jim O'Flaherty
Campbell Macdonald wrote:
Jim:
I enjoyed your note. Do you have a site where your
ANN work is published? Let me know. If this is
proprietary, I understand.
Thanks
Campbell
--- "Jim O'Flaherty, Jr." <jim_oflaherty_jr@xxxxxxxxxxxxxxxxx>
wrote:
Imran,
I am working with ANNs using GAs. What I am finding
is there is a huge
number of people who are out of synch with more
modern ANN techniques,
and write ANNs off out of hand. It is not unique to
this group. There
is enormous amounts of information in a number of
domains. And there
even more "less informed self-righteous" software
developers.
No one (including the uh..."geniuses" of this group)
has the time to
follow all the tangents in the many differing
related fields. And no
single technique I have seen discussed here is going
to "solve the
computer-go problem" such that the program based on
their particular
"uber" technique will achieve a dan level rating
against similarly
skilled humans, at least not consistently and
long-term. If hardware
speed keeps doubling, perhaps it might happen in 10
years.
I suspect a hybrid approach, which a couple people
have referred to,
will be what finally makes a substantial
breakthrough. Given the type
of dialog I see in this group, I am very suspicious
it will come from
here. I personally detect very little spirit of
collaboration. And I
think the hybrid is going to require that. I do see
a member or two
trying for collaboration. And most of the rest of
the group is so
scarcity (it's mine, it's a secret, I'm brilliant
and won't share my
*ultimate* partial solution with you, etc.) focused,
it is very
disappointing. It does not generate the social
cohesion I think will be
required for the hybrid. Still, I am getting some
value from the
conversation. And I am getting a good idea of the
people I think I will
find interesting in working with later.
And as you said, it borders on trivial to get an ANN
to perform near
perfect on the simpler games. I know as I have done
it, been on a team
that has done it or dl'ed and tried it out for
tic-tac-toe, connct-four,
gomoku/pente and other small games. As to ANNs
playing checkers, chess,
Go, etc. with perfect play, HA! I suspect that is
decades off without
some parallel hardware breakthrough. And even then,
it smacks of
"trying hard" as opposed to "trying smart". And it
will happen much
sooner for checkers/draughts than for chess. And it
will be eons after
it happens for chess before it will happen for Go.
In fact, perfect
play is likely unprovable ideal for Go. I had put
impossible - but with
proper encoding on a future quantum computer, it
might actually become
achievable. Who knows?
Jim O'Flaherty
Imran Ghory wrote:
On Sat, 4 Dec 2004, John Tromp wrote:
Imran Ghory wrote:
Nine men's morris and Connect 4 however both are,
and both can be played
to a very high (better than human) level by
neural networks.
You mean better than the average human, right?
To beat the best humans at Connect-4 requires
(near-)perfect play,
which appears quite beyond the capabilities of
neural nets.
nope, neural nets can reach near-perfect play. Just
knock up a quick test
using tic-tac-toe or some other similar game and
see for yourself.
Imran
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