> Maybe other simple solutions exist, you might want to check out those distributions that magically have nice properties with respect to the bayesian integral.
they're called conjugate priors, and lots of distributions have nice, easy to calculate conjugate priors. there's a table here: http://en.wikipedia.org/wiki/Conjugate_prior multivariate gaussians are very useful, and inverse wisharts and dirichlets can be computed blindingly fast. this is useful, for instance, in the case where you're trying to sample directly from the parameter space of a hidden markov model over multivariate gaussians, for instance, where you can easily sample a huge number of trajectories to learn about the parameter space. sadly, the number of possible states in a go game is quite large. s. ____________________________________________________________________________________ Food fight? Enjoy some healthy debate in the Yahoo! Answers Food & Drink Q&A. http://answers.yahoo.com/dir/?link=list&sid=396545367 _______________________________________________ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/
