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From: geert@sparc.aie.nl (Geert-Jan van Opdorp)
Subject: Re: The game: GO
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In-Reply-To: hall@aplcenmp.apl.jhu.edu's message of Fri, 13 Oct 1995 13:17:28 GMT
Date: Fri, 13 Oct 1995 14:24:39 GMT
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	<GEERT.95Oct12232108@sparc.aie.nl> <DGE295.738@aplcenmp.apl.jhu.edu>
Organization: AI Engineering BV, Amsterdam, Netherlands
Xref: glinda.oz.cs.cmu.edu comp.ai.games:2509 comp.ai:34068

In article <DGE295.738@aplcenmp.apl.jhu.edu> hall@aplcenmp.apl.jhu.edu (Marty Hall) writes:


> In article <GEERT.95Oct12232108@sparc.aie.nl> geert@sparc.aie.nl 
> (Geert-Jan van Opdorp) writes:
> 
> >There are quite a number of aspects of the game that can
> >more or less be quantified. The problem is that most of
> >them are hard to define formally.
> 
> Hard, but I don't think that they are that much harder to define
> than in chess, etc. What makes Go so much harder to program is the
> tremendously huge branching factor (in the 300's for the early game,
> vs. an average of about 35 for chess).


Of course there are quantities that are very hard
to define in chess. The point is that in chess
there is no need to try anyway, while in Go,
because of the astronomic size of the problem space,
you may have to. Before you could do
any alpha-beta search like in chess
you'll have to make quite a severe
selection of candidate moves.  And that 
is what makes it both hard and interesting from 
the AI point of view.



-- 
Geert-Jan van Opdorp
AI-Engineering
Amsterdam, The Netherlands
geert@aie.nl
