I like that paper a lot, but I really had a difficult time swallowing the assumption that a team could be rating by summing together each individual member. The paper of course makes a disclaimer that it may not be a good assumption "all the time" but in my view it's rarely a good assumption - unless you are playing tug of war.
It may be a reasonable however if the number of features in the pattern you are comparing is the same. Then summing the ELO's of the features is exactly the same as taking the average. I don't remember if that was the case here. In sports, it's a lot more complicated. A team is generally handicapped by it's weakest member and they do combine but usually not linearly. At our local chess club I used to play non-consultation speed chess and the team was WEAKER than either member usually. The formula given is interesting but doesn't consider how features work together. An area of research may be how to combine them more realistically and locating "synergy's" (I hate that word.) Don On Tue, Apr 2, 2013 at 2:39 PM, ds <d...@physik.de> wrote: > Hi, > > I am struggling with one equation in this famous paper: > http://remi.coulom.free.fr/Amsterdam2007/MMGoPatterns.pdf > > In section 2.2 the Bradley-Terry Model is generalized. > > The gammas are the playing strength, if I understood correctly. > > The first formula in the section scales quite nice: If one multiplies > every playing strength by the same factor, the winning rate is not > changed. But the second generalization does not scale any more? > > I do not understand, why this can be correct? > > Thanks for any help > > Detlef > > _______________________________________________ > Computer-go mailing list > Computer-go@dvandva.org > http://dvandva.org/cgi-bin/mailman/listinfo/computer-go >
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