Author: Dieter Buerssner
Date: 07:25:02 04/10/01
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On April 10, 2001 at 08:58:14, Ulrich Tuerke wrote: >On April 10, 2001 at 07:05:59, Tony Werten wrote: > >>On April 09, 2001 at 23:40:21, Jon Dart wrote: >> >>>>On April 09, 2001 at 17:04:09, Vincent Diepeveen wrote: >>> >>>> An interesting thing is lazy evaluation, as the problems of it are >>>> very similar to futility pruning. [...] >>>> My big question was: what score to return for example if evaluation in this >>>> position is e and e+ 3.5 pawns <= alfa ? >>> >>>> Must one return alpha, estimated evaluation or evaluation+3.5 pawns, >>>> when talking about e+margin <= alfa (idem story for e-margin >= beta) ? >>> >>>I return the estimated evaluation. But I fail to see that it makes a lot of >>>difference. If it's below alpha, you're not going to propagate this evaluation >>>up the tree, anyway. >> >>With failsoft alfabeta it easily could. >I think that it is a bad idea to return the estimated eval here because it can >result in some root-value far outside the aspiration window. It would be >interpreted as a corresponding bound which may cause serious trouble (fail low >in fail high verification search for instance). >IMO, it's much safer to return the corresponding beta or alpha. In case of >traversion of this value to the root this would cause a continous re-search >(i.e. over a neighbour region of the original window). I also have thought about this problem. I am using fail-soft alpha-beta search. I agree, that returning alpha or beta is safest. Nevertheless, some limited testing has shown here, that returning an estimation solved the testpostions I used with less nodes on average. From my understanding, returning an estimation should work and be theoratically sound. In eval, I first check for cases, which I don't want to estimate, like pawn endgames, endgames where one side has no pawns, etc. For other cases, I more or less compute bound values. 1) material score + highest positional advantage seen for this side 2) material score - highest positional advantage seen for the other side where, with positional evaluation, I mean the overall positional score, that includes both sides. 1) is compared with alpha, if <= alpha, it is returned as estimation 2) is compared with beta, if >= beta, it is returned as estimation I also made some tests, to see how often this fails. IIRC this happened very rarely. Regards, Dieter
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