Re: computer-go: Pattern matching

["Andrew Watson" <andrewwatson@xxxxxxxxxxx>]

could someone let me know how to get off the list?



> From: Patricia Hughes and David Elsdon <babel17@xxxxxxxxxxxxxxxxx>
> Reply-To: computer-go@xxxxxxxxxxxxxxxxx
> To: computer-go@xxxxxxxxxxxxxxxxx
> Subject: Re: computer-go: Pattern matching
> Date: Tue, 09 Nov 1999 16:57:45 +0100
>
> I am strongly in agreement with Tristan !!
>
> Tristan Cazenave wrote:
>
> >  I think we can expect a computer AI to learn better than a person.
> > As well as we can expect a computer AI to play chess better than a 
> person.
> >
> > In my opinion, working on making an AI learn better than a person is
> > fundamental, not only for Go, but for AI in general.
> > I wrote several papers related to this problem for Go, and I believe 
> than
> > in
> > the future learning AI Go program will be among the strongest programs.
> > If search is what makes a chess or a traditional board game program
> > strong,
> > search AND good learning maybe what makes a Go program strong.
> >
> > There is so much knowledge involved in a Go program that mastering it is
> > not
> > a human task, it is an AI task. Working on Go programs using
> > metaknowledge,
> > that is knowledge to create and use knowledge is a research that can 
> lead
> > to
> > a strong increase in the level of Go programs. Moreover it may enable to
> > master AI techniques that will enable AI to apply to more complex 
> domains
> > than it presently does.
>
> And disagree with Moucheng:
>
> "Xu, Mousheng" wrote:
>
> > * Strongly doubt AI will work for Go programming. :)
>
> I don't want to get into too much of a discussion amount what counts as
> AI,
> but I think that a program using knowledge representatation and/or
> learning
> is an AI program.
>
> Deeper Blue uses a lot of chess knowledge as well as an extraordinary
> amount
> of search.
> The champion checker playing program uses checker knowledge plus search.
> The champion backgammon program "learned" to be that good !!
>
> So in Go where brute force search is not very effective even more AI
> will be required.
>
> > * We can't assume AI can do everything.
>
> Why not ?? Any knowledge which a person has can be represented in a
> computer. I don't say it will be easy.
> Give me an example of knowledge that cannot be represented on a machine
> !!
>
> > In some areas, AI does better than human, that's because people don't
> > understand the subject enough.
>
> I don't under this. The difficult areas for AI are those which people do
> not
> understand thoroughly - i.e. are unable to articulate. Common sense
> knowledge is notoriously hard to capture, though by no means impossible.
>
> Once knowledge it clearly and completely articulated it can be
> represented on
> a computer.
>
> > Go is probably different. Go knowledge can be very well explained by
> > "shape", which means human beings know Go very well, can translate the
> > knowledge very well, and can learn the knowledge very well. We know Go,
> > we know it!
>
> If we know it well, then we can articulate it and we can represent it on
> a
> computer. I am a knowledge engineer and I've been doing this sort of
> thing
> for the last 15 years !! The game of Go is "just" a bigger challenge.
>
> > The knowledge of "shape" can be somewhat understood by the
> > computer as well, but to let it master the knowledge has to do with
> > (huge) numbers.
>
> No bigger than the numbers (of patterns) that we humans have to cope
> with.
>
> > One can give so many "simple" questions to a computer to
> > learn, and it may progress 0 or a very little over years.
>
> Surely this is under-estimating the power of computers. Data-Mining
> software, for example, can trawl through gigabytes of data and find
> interesting patterns (using various machine learning techniques) where
> mere
> humans simply wouldn't have a chance.
>
> > I don't doubt, that after many many many years, an AI program will
> > eventually be a 9
> > dan pro, but that might take as long as to wait for Darwin to evolve to 
> a
> > monkey.
>
> I confidently expect a computer to "beat" a 9 Dan Professional before
> the
> year 2010.
>
> > * AI still has a chance to win, but that would be AFTER we understand Go
> > better in a form a computer can understand.
>
> I think we will come to understand Go better by writing Go programs. A
> Go
> program is operationalised Go Knowledge. If you write a book about some
> aspect of Go you can get away with being quite sloppy. When you write a
> Go
> program you have to be very precise because your program will do
> "exactly"
> what you tell it to. This makes a Go program a very accurate
> representation
> of the whole body of Go knowledge. When we are able to combine this very
> accurate representation with state-of-the-art computer learning
> techniques
> we will start to get really strong Go programs.
>
> I am working on it !!
>
> But don't hold your breath !!
>
> Cheers
>
> David Elsdon
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