Author: Robert Hyatt
Date: 09:30:38 02/25/04
Go up one level in this thread
On February 25, 2004 at 12:09:16, Daniel Clausen wrote:
>On February 25, 2004 at 10:52:27, Robert Hyatt wrote:
>
>>On February 25, 2004 at 05:56:16, martin fierz wrote:
>
>[snip]
>
>>>i don't know whether i should believe the eval discontinuity thing. i know
>>>somebody recently quoted a paper on this, but it's just a fact: exchanging any
>>>pieces necessarily changes the evaluation. sometimes not by very much. big
>>>changes are usually the exchange of the queen, the exchange of the last rook,
>>>the exchange of the last piece. these eval discontinuities are *real*. i don't
>>>believe in smoothing them out. perhaps if you write an eval with
>>>discontinuities it's harder to get it right that everything fits in with each
>>>other, and that's why it's supposed to be bad?!
>>
>>No. When you have a discontinuity, you give the search something to play with,
>>and it can choose when to pass over the discontinuity, sometimes with
>>devastating results..
>
>The arguments of you two could be combined to this:
>
> Eval discontinuities are _real_ but it hurts the search too much and
> therefore it's better to be a tad less realistic in eval here in order
> to get maximum performance out of the search+eval.
>
>
>Does that make any sense?
>
>Sargon
That is not quite the issue. Consider the following X-Y plot of your
eval function (Y axis) against some positional component (X-axis):
|
|
|
| *
E |* * * * *
V | * *
A | * *
L |
|
|
|
|
|
|
| * * * * * * * * * * * * * * * * * * * * * * *
|_________________________________________________________________
some feature you are evaluating
Notice the sudden drop to zero. If you start off in a position where the score
is non-zero for this term, and you can search deep enough to drive over the
"cliff" for this term and hit zero, strange things happen. The search can use
this as a horizon-effect solution to some problem. And it will be able to use
that sudden drop (when something goes too far) as opposed to the big bonus just
before it goes too far, to manipulate the score, the path, the best move, and
possibly the outcome of the game.
This is what Berliner's paper was about. I suspect that anybody that has worked
on a chess engine for any length of time has run across this problem and had to
solve it by smoothing that sudden drop so that there is no "edge condition" that
the search can use to screw things up.
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