Thanks a lot for your quick answer.
By conjecture, i suppose you mean that
no experiments yet has been ran as
to assess this hypothesis ?
I think Sylvain (and maybe just everyone else) has tried
at some point to use a UCT decision bot, as a way to
get the simulation done. Then using those high level
simulations in an other UCT decision tree (or AMAF,
or FirstMove wining stats)
>From what i recall, the results were disappointing.
Also don dailey tried to build an AMAF over a bot
that would use AMAF as a decision with very little
expectation that this would lead to anything worthy.
I don't know how hard Sylvain tried at his time.
Yet you have this feeling that using High level mogo
games as a way to get a simulation done could lead
to interesting results. I also have this feeling.
For example, it is well known that Mogo-style decision
(or crazy stone) lead to very poor understanding of seki
(and/or semeai ?) Would'nt the use of high level game
as simulation get to better understanding of those
really nasty situations ?
Then, i guess that if nobody has ever run
any experiments, as to get measure of
the efficiency of increasing the UCT tree
against using high-level-simulation, there must be a reason ...
Is it that that it is known it would consume to much time and resources ?
Is it that knowing the results of this measure would prove of little value ?
If there is a point where high-level-simulations really give a stronger
evaluation
function, wouldn't it be good to know about it ?
Date: Sun, 30 Nov 2008 10:10:14 +0100
From: [EMAIL PROTECTED]
To: computer-go@computer-go.org
Subject: Re: [computer-go] Mogo Opening, Building Strategy ?
Is there any theoretical reasons for the Mogo Opening being built out of
self play, rather than by spending time increasing the number of simulations
at the root, and after a time, keeping what seems to be the best ?
There are practical reasons: our approach can be used with humans or other
programs as opponent as well;
we can benefit from games launched for other purposes than opening-building;
and we can easily parallelize
the algorithm on grids.
No other reason, at least for me - but these reasons are enough I guess. The
alternate approach is nice,
but is difficult to use for tenths of years of CPU - whereas using preemptable
mode in grids, we can have access
to a huge computational power.
>From a more technical point of view, I think that the idea of using results of
>games of strong versions of mogo
is better for avoiding biases in the MC. But it's only a conjecture.
Olivier
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