Author: Ricardo Gibert
Date: 22:22:57 01/03/01
Go up one level in this thread
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. I have a vague recollection of a statistics theorem that guarantees you will cross the 50% line an infinite number of times given an infinite number of *fair* coin flips. The unlucky 500 run coming first is irrelevant. Unfortunately, I do not have a statistics book or an infinite amount of time to verify this.
This page took 0 seconds to execute
Last modified: Thu, 15 Apr 21 08:11:13 -0700
Current Computer Chess Club Forums at Talkchess. This site by Sean Mintz.