Author: Ricardo Gibert
Date: 14:34:30 01/04/01
Go up one level in this thread
On January 04, 2001 at 02:38:42, Uri Blass wrote: >On January 04, 2001 at 00:00:39, Robert Hyatt wrote: > >>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. > >You replied to the sentence: >"But don't you think the more times you flip the coin, the closer the number of >head and tails (in %) will be?" Bernoulli's Theorem says yes to this question (for a fair coin). > >I think that you missed the in % > >Uri
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