Author: Reinhard Scharnagl
Date: 07:47:56 01/14/04
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On January 14, 2004 at 10:35:38, Uri Blass wrote: >On January 14, 2004 at 10:19:03, Reinhard Scharnagl wrote: > >>On January 14, 2004 at 07:52:19, Uri Blass wrote: >> >>>I think that learning can be very effective. >>> >>>An engine that does not learn may lose the same games again and again after >>>enough games. >>> >>>I use learning for matches of 4 games that are popular in Leo's tournament and >>>my learning is simply to choose a different first move after a loss. >> >>Is this real 'learning', or an escaping into a not yet refuted randomizing? >> >>>With my very small manually edited book(only few hundreds of positions) there >>>are big chances that movei will lose the same game twice if I do not do it. >>> >>>For testing I prefer to use the nunn2 match and test suites. >> >>Nevertheless that behaviour really may produce success, it is not what I would >>call learning. But you are not alone using the word 'learning' that way. >> >>Before claiming something being able to learn, please specify, what is learning. >>I still cannot do this sufficiently. >> >>Regards, Reinhard. > >Every behaviour of a program that is dependent on the history of games is >learning. Hello Uri, learning is possible from success or from failures. (And I hope not to have made you angry by the above.) Failures (in opposit to successes) mostly can be localized at a special point of history (you correctly demands that dependance). But loosing a game can be completely independent from the opening moves. Without being able to localize the probably point of error (with a lot more than low random chance) how could there be a correct implementing of experiences? Regards, Reinhard.
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