HermanHiddema wrote:topazg wrote:I'm not over-estimating it, as I said, I'd be very happy with either. I think the randombot chances are non-zero, but almost indistinguishable from 0. I think the 20k's chance is actually 0.
Yes, I understand. And I think you are over-estimating it. I do not think the 20k's chance is exactly 0.
Isn't that a case of under-estimating the 20k, rather than over-estimating the bot

From Jeff Sonas (a chess ratings statistician), a chess rating difference of 400 (equivalent of ~4 stone in go) involving master level players equates to an effective 8% chance of winning, with it falling to about 0 by 700 (somewhat extrapolated as there's very little data, but the data spread from -400 to +400 is fairly close to linear). I think the spread is slightly broader in Go, although not drastically, and I would intuitively guess that it is at least as linear due to the length and depth of a typical Go game. However, I do believe 0 and 100 would be reached well before the 19 stone strength difference, particularly involving players above a certain strength. I strongly suspect that the stronger the player, the closer the 0% mark would be, and at my strength I suspect it will be before it reaches 20k. Conversely, I feel very confident that my chance of beating a 9p active title pro to be 0% too. I also consider it impossible for a 20k to beat Lee Sedol, even though a random player by its very nature will have a finite chance of winning, even if it is infinitessimally small.
Herman, do you really think that, given enough games between Lee Sedol and a 20k, both not under the undue influence of drugs or whatever, would ever result in a 20k win, even over 10^1000 games?
FWIW, I'd much rather play the random bot 10,000 games where I have to win them all rather than a 5k in a single game, but 20k is a completely different prospect.
EDITquantumf wrote:As I see it, it's only non-zero if you allow for some external influence, e.g. topazg suffers a stroke during the game, or receives some shocking news.
I agree, and if we should model the likelihood of such things
as well as the difference in strength I would end up choosing the random bot, as the chance of an extreme external influence is many orders of magnitude higher than the chance of a loss to the random bot. However, I think this argument is to model strength alone as opposed to all the other confounding factors that could possibly apply to an actual instance of a game.
I suppose my point is that the whole exponentially formulaic predictive accuracy of a result based on rank (or actual playing strength if pedantic about it) is unsupported by any data. What little data there is for chess (I'm not aware of any data for Go) seems to argue against the exponential formulae being reliable.