Author: Uri Blass
Date: 05:51:12 01/30/06
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On January 30, 2006 at 08:40:09, Uri Blass wrote: >On January 30, 2006 at 07:49:53, Michael Diosi wrote: > >> >>Hello. >> >>I have a few, this one is from Russel/ Norvig : Advances in Artificial >>Intelligence A Modern Approach (page 130) >>[d]8/1p1P4/k1p5/8/8/3PPPPP/r7/7K b - - 0 1 >> >>You can see here that black can give a series of checks "pushing" the inevitable >>queening over the horizon. So programs how don't see it will have a positive >>score for black. >> >> >>I can look for more if you want. >> >>MD > >This is a bad example > >Amir Ban is correct. > >The horizon effect is effect that cause the program to play worse move because >it does not see deep enough. > >This example is not the horizon effect but only not seeing deep enough. > >Uri Note that not every case that the program play worse move because of not seeing deep enough means the horizon effect. The idea is that the program has some illusion that it can prevent some problem but only cause itself a bigger problem because it delay the problem to position that it does not see. In the example the program has an illusion that it can prevent the pawn from promotion but it does not cause it to do mistakes and sacrifice material so I do not think that it is good example. Without check extensions if the program sacrifice the rook then it can be a good example. Uri
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