Author: Robert Hyatt
Date: 21:00:39 01/03/01
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On January 03, 2001 at 17:50:38, José Carlos wrote: >On January 03, 2001 at 16:26:19, Robert Hyatt wrote: > >>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. >> >>It is statistically invalid. IE if you flip a coin 500 times do you _really_ >>expect to get 250 heads and 250 tails? Probability distribution says you >>won't get that very often at all. In fact, if you flip long enough, you will >>either get 500 straight heads or tails, or else prove the coin is _not_ actually >>perfectly random with 50-50 probability of getting a head or tail. > > But don't you think the more times you flip the coin, the closer the number of >head and tails (in %) will be? Maybe the coin is not the better comparison, as >it is a random event, and a chess game is not, but I still think it should work. >But I expect a different rate of "closeness" (is this word correct?) for the >same number of tries with the coin (random event) and the games (partially >random -book, pondering, ... and partially not -eval function, search algos...), >and that difference is what I want to measure. > > José C. No I don't. Suppose that 500-0 run comes _first_. How long will you have to flip to get back to even? You may _never_ get back to even. Remember this is a bell-curve shaped probability distribution. Not a single spike on the curve at the mid-point of the distribution. You probably need to play 40 forty-game matches to get the beginning of an idea of who is better.
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