Author: Dann Corbit
Date: 10:59:34 05/18/05
Go up one level in this thread
On May 18, 2005 at 12:29:29, Vasik Rajlich wrote:
[snip]
>Actually, there are two separate issues here:
>
>1) how you select the moves to search
>2) how you propagate the scores up the tree
>
>I took the original statement by Robin to mean simply that in some cases, a
>human will propagate scores up the tree in a minimax manner - which is of course
>true.
>
>Note that there are many ways to propagate scores in a non-minimax manner as
>well. One example is taking into account second-best moves. Maybe at some point
>in the tree, one side can either force a perpetual check, or continue playing in
>an unclear position. These two possibilities together should be equivalent to
>having some advantage - but such reasoning is outside the scope of minimax,
>which can only take into account the score from a single branch.
>
>Similar arguments can be used in the opening. Maybe you like to play 1. e4, but
>right at this moment the defense 1. .. c6 is annoying you and you see no
>advantage. According to a strict minimax, you should stop playing 1. e4, but
>practically speaking you might play it anyway, since not everyone will play 1.
>.. c6.
>
>Note also that not all computer chess programs use minimax propagation. Two
>alternatives are B* (Berliner, etc) & BPIP (Smith & Baum), and probably there
>are many more.
Or A* or lots of others. We also do not have to use a DFS, but could use a BFS
(or even solve it in travelling salesman manner if in a fit of utter insanity).
>I hope that this is at least partially clear (somehow I suspect not :)) ..
I would like to add two cents:
The tree propagation will be exactly as good as the quality of data. So if you
have top notch players/engines/whatever and all at slow time control then the
backsolving will create better and better node evaluations. But if you have
guest online games by VOG or FICS at G/5 minutes sprinked in, you will get
stupid answers.
In each and every case, the answer propagated back will be only an ESTIMATE
unless there is a forced win/loss/draw for all forward branches. So the
centipawn evaluations or the point win percentages will just be ballpark figures
of "probably in this neighborhood" type. If you see 0.0 centipawns or 0.5 of
points scored you cannot assume you will draw that position even under ideal
play because it is only an estimate.
If you have a large database of openings, what backsolving can be most useful
for is closing off dead branches because of new novelties found by good players
or programs. The books may not have logged the refutation yet (or you may not
have the latest book that does document it). You may also uncover a nifty new
novelty by loading your database with new SSDF games or games from some other
tournament that others have not studied yet. So you can spring a surprise on
some opponent, because a computer {or a strong player or whatever} found some
new wrinkle. With a huge number of games and openings, it would be very, very
tedious for a human to perform all the same analysis and also very error prone.
I imagine that a top level chess player (GM/IM) is going to check BCO/MCO/NCO
and whatever carefully before they use some new novelty and also that they will
carefully scrutinize the new line unearthed by backsolving before they believe
in it.
In any case, the value is clear to me. If we trust computer analysis then we
trust "backsolving" because that is basically what computers do when they play
the game.
Our answers will only be as good as our original data. The old computer adage
goes GI-GO {Garbage In - Garbage Out}
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