[computer-go] Monte-Carlo for Tactical Search

[Don Dailey]

I was responding more to the general misconception than anything you
said in particular.   You just reminded me of it with something you
said.

I think what will happen in the future of go programming is that all the
techniques will gradually come together.  Monte Carlo programs started
out purely random, now they have a "tree in memory" portion.   Some
monte carlo programs have started using patterns.   Local search is no
doubt helpful for specific things and I think some monte carlo programs
do a little of that.   And now there is talk of adding a little monte
carlo to a conventional program.    

It might be rather like mtd() in chess.  At one point there were all
these different kinds of searches, PVS, scout, and top level aspiration
and more - but mtd showed them all in a simple framework.  In a way they
are all variations of each other. 

- Don


On Fri, 2006-09-01 at 09:10 +0200, Benjamin Teuber wrote:
> Hi Don,
> I get the impression our little debate was rather based on a 
> misunderstanding than a real different view...
> 
> Global search is fine, as long as it does something more than just 
> playing out games until the end - of course, even that might be a 
> misconception of mine.
> And while others are working to improve the search in general, I'd like 
> to think about the things needed in an evaluation function, and how to 
> make use of MC for these things.
> I also don't think the evaluation should replace MC by a 100% - they 
> should rather be concurrent sources of information, whose reliability  
> can be judged using probability theory.
> 
> Benjamin
> 
> 
> Don Dailey schrieb:
> > Whenever I mention the phrase "global search" it's usually followed up
> > with something like,  "that doesn't work" or "that's stupid."   So I'm
> > on your side of this issue.   Most people assume I mean brute force
> > stupid search but I envision something like what you are saying.
> >   
> 
> > I don't know if monte carlo programs will every reign supreme - they
> > seem to be doing ok on small boards and I think they will be improved
> > tremendously - but the way they are done now they are basically global
> > searchers.   The "monte carlo" part could be replaced with an evaluation
> > function.   
> >   
> >
> >
> >   
> >>> Also,  it's very clear that monte carlo is very scalable.  In 
> >>> real terms that means it will eventually "outrun" any 
> >>> technique that is not. 
> >>>       
> >> This is clearly a true statement, but it seems that you are assuming that
> >> the existing strong programs use techniques that are not scalable.  But
> >> existing progrrams are scalable.  They are running on much stronger
> >> processors today than they were 20 years ago, they use more time, and they
> >> are stronger.
> >>     
> >
> > I'm only arguing for scalable methods, but I admit that I didn't realize
> > the best programs are scalable.  I should listen to the real programmer
> > more - many others are very critical of using search "because it can't
> > possibly produce a super grandmaster."
> >   
> >
> >
> >   
> >> David
> >>
> >>
> >>     
> >
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