Author: Dann Corbit
Date: 16:41:19 07/15/00
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On July 15, 2000 at 19:35:34, ShaktiFire wrote: >On July 15, 2000 at 18:32:52, Mogens Larsen wrote: > >>On July 15, 2000 at 18:22:59, Ralf Elvsén wrote: >> >>>These are pretty harsh words, especially since I think Uri has a point. >>>Even if it is not correct I wouldn't call it "nonsense" or "truth distortion". >>>These judgements should be saved for more clear cases, and there has >>>certainly been some on this board in the past... >> >>No, he doesn't have a point, since you can't determine GM strength by gathering >>the results of several programs, reach GM strength within the bounds of >>uncertainty and then conclude that one of the programs are GM strength. Because >>you already know that none of programs alone are of GM strength with certainty >>due to a large ELO uncertainty, otherwise it wouldn't be necessary to add them >>together. So nonsense is the appropriate word, even though truth distortion was >>unnecessary harsh. >> >>Best wishes... >>Mogens > >Can we not make a category. Say, "commercial programs running on 500 Mhz or >higher", take performance data, for that class, and then do statisical analyses >that allow to make statements about that class. We can do anything we like, but what are we trying to model? With a large pool of data outliers are certain. Imagine a single trial by each program/machine combination. How much information do the GM's have to pick the program/machines apart? The answer (since there is only one game) is zero. Now, imagine a single machine and a single program that plays a million games against a huge pool of GM's. Will they discover more flaws in the machine's approach in this experiment or the one you designed? What will your conclusions be, mathematically? I think it would take a supercomputer to model just how to interpret the data!
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