Hi Rémi, For a while I have considered overhauling the rating system for CGOS. My system is ad-hoc and based on gradually increasing K factor based on your opponents K in the standard ELO formula.
I don't know if your idea here is feasible for a computer server, because presumably the players are fixed in strength, but in practice I think some bots change. Anyway, I'm no expert on this but want to find something better than what I'm doing and I have considered using some kind of whole history approach (such as running bayeselo after every round on every game, which of course is not very scalable :-) - Don Rémi Coulom wrote: > Hi, > > This is my CG2008 paper, for statisticians: > > Whole-History Rating: A Bayesian Rating System for Players of > Time-Varying Strength > > Abstract: Whole-History Rating (WHR) is a new method to estimate the > time-varying strengths of players involved in paired comparisons. Like > many variations of the Elo rating system, the whole-history approach is > based on the dynamic Bradley-Terry model. But, instead of using > incremental approximations, WHR directly computes the exact maximum a > posteriori over the whole rating history of all players. This additional > accuracy comes at a higher computational cost than traditional methods, > but computation is still fast enough to be easily applied in real time > to large-scale game servers (a new game is added in less than 0.001 > second). Experiments demonstrate that, in comparison to Elo, Glicko, > TrueSkill, and decayed-history algorithms, WHR produces better > predictions. > > http://remi.coulom.free.fr/WHR/ > > Feedback is welcome. > > Rémi > > _______________________________________________ > 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/
