All the data for cgos is available as files zipped up by month. So any kind of study is possible.
- Don On Wed, 2007-01-31 at 10:44 -0500, [EMAIL PROTECTED] wrote: > > To gain some intuition re. what level of intransitivites are > present on CGOS, it would be interesting to see the cross-scores of > all (or some...) of the bots in a big table. A less obvious refinement > is to add color coding to make it easier to read. Here's an example > from the game of Corewars. > > http://www.koth.org/lcgi-bin/hugetable.pl?hill94nop > > The numbers look a little strange and it's not symetric because > Corewars is a non-zero sum game. For CGOS, the numbers along the > edge would, presumably be the the ELO rating and the numbers/colors in > the boxes would be for percent wins. In Corewars, non-transivity is a > very big part of the game. It might be interesting to look at the > actual win percentages for each pairing against those predicted by the > ELO differences. > > - Dave Hillis > > -----Original Message----- > From: [EMAIL PROTECTED] > To: computer-go@computer-go.org > Sent: Wed, 31 Jan 2007 7:57 AM > Subject: Re: [computer-go] Is skill transitive? No. > > My basic idea, which is undeveloped is rather like this - you partition > all players into 2 (or more) broad styles. One of the variables in the > rating > tells you how much (from 0 to 1) he plays at one extreme. The rating > system itself somehow determines which style you are and it's an > abstract > quality that we don't necessarily have to understand. (sort of like > learning algorithms that build neural networks that we don't understand > but it works.) > > In chess, which I use as an example because I understand it much better, > there are kinds of playing styles that interact. You can have very > good tactical players (who love gambit play sometimes) and you have > very slow positional style. Some very good players are not > particularly > good at tactics. I don't know what conclusions you can draw about > who is expected to win matches between various styles, but I'll bet > there is a measurable non-transitive relationship somewhere there. > > Of course an outright learning algorithm, if given enough games, > might be able to predict winning expectancy better than straight > ELO. > > - Don > > > On Wed, 2007-01-31 at 05:54 -0600, Nick Apperson wrote: > > I feel that what we need essentially is a set of functions that tell > > us expected winning percentages with certain matchups. In an extreme > > example, we could imagine 3 rock, paper, scissors players. One always > > plays rock, one always scissor and one always plays paper. In this > > case, we would be able to define a ranking function as a relative > > ranking, but absolutre ranking would not exist. And this is > > consistent with our whole approach here that skill is not transitive. > > A simple 2D ranking system could work like this: > > > > let W = chance that player 1 will beat player 2 > > 1-W = chance that player 2 will beat player 1 > > > > our skill is expressed in R and T (for theta) > > > > ELO = (R1-R2)+k*sin(T1-T2) where k is some constant, R1, R2, T1, T2 > > are R of player 1 and 2, theta of player 1 and 2 respectively > > > > > > This would result in a nontransitive 2D skill map. There are many, > > more compex functions that could be worked out and this has the nice > > property that it easily collapses into a 1D map by merely setting > > everyone's theta to the same value. Essentially R is "general skill" > > and theta is a rock paper scissor type thing where one strategy is > > better against certain other types of strategies. > > > > > > On 1/31/07, Vlad Dumitrescu <[EMAIL PROTECTED]> wrote: > > Hi, > > > > On 1/30/07, Don Dailey <[EMAIL PROTECTED]> wrote: > > > It would be interesting if it would be possible to construct > > a 2 > > > dimensional > > > model statistically. A 2 dimensional system would not be a > > perfect fit > > > either, > > > but would simply be a better approximation. So in some > > way a players > > > "strength" could be expressed by 2 numbers instead of > > 1, and the 2 > > > numbers > > > together would predict your chances of beating another (2 > > dim) player > > > more accurately that a 1 dimension system could. And of > > course you > > > could > > > extend this. But I don't have a clue how one would > > construct such a > > > system > > > or if it's even possible - but it seems like more > > information should be > > > better > > > than less. > > > > Unfortunately, having more than one dimensions makes > > comparisons > > impossible - if an ordering relation is defined over the > > domain, then > > this domain is "one-dimensional" with regard to that > > relation. > > > > In other words, one can't compare vectors, just scalars. So > > the > > multi-dimensional "strength vector" has to be turned into a > > scalar (by > > for example a weighted sum) and we're back where we > > started... > > > > best regards, > > Vlad (master of the obvious :-) > > _______________________________________________ > > computer-go mailing list > > computer-go@computer-go.org > > http://www.computer-go.org/mailman/listinfo/computer-go/ > > > > _______________________________________________ > > computer-go mailing list > > computer-go@computer-go.org > > http://www.computer-go.org/mailman/listinfo/computer-go/ > > _______________________________________________ > computer-go mailing list > computer-go@computer-go.org > http://www.computer-go.org/mailman/listinfo/computer-go/ > > ______________________________________________________________________ > Check Out the new free AIM(R) Mail -- 2 GB of storage and > industry-leading spam and email virus protection. > > _______________________________________________ > computer-go mailing list > computer-go@computer-go.org > http://www.computer-go.org/mailman/listinfo/computer-go/ _______________________________________________ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/
