Author: Ricardo Gibert
Date: 14:01:35 01/03/01
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On January 03, 2001 at 09:52:06, José Carlos wrote: > Lately, people have been talking here about significant results. I'm not >really sure if probabilistic calculus is appropiate here, because chess games >are not stocastic events. > So, I suggest an experiment to mesure the probabilistic noise: > > -chose a random program and make it play itself. > -write down the result after 10 games, 50 games, 100 games... > > It should tend to be an even result, and it would be possible to know how many >games are needed to get a result with a certain degree of confidence. > If we try this for several programs, and the results are similar, we can draw >a conclusion, in comparison with pure probabilistic calculus. > > Does this idea make sense, or am I still sleeping? :) > > José C. You can model perfectly what will happen with a trinomial distribution. This assumes the program does not learn from past games. You can run an experiment of 1000 games and get the results of White win%, Black win% and draw%. With this you calculate whatever you want for that *particular* program, but the results will be different for different programs. That's the problem. You've measured something vary narrow in scope. How a program will perform against itself is not very interesting and if the program then gets modified for whatever reason,...then you must start from scratch :-(
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