A new cool eprint has appeared:
J. Veness, et al. A Monte Carlo AIXI Approximation. eprint: 0909.0801
The question that defines the context for this article is: How should probabilities be assigned? One way, with much to recommend itself, is take them to be algorithmic probabilities or universal priors. Suppose one has observed the first N values of a discrete time series, maybe a byte stream, and wishes to predict or make a bet about the next value. Is there a general probability measure appropriate for all cases that fit this abstract setting and, if so, which one? Read the rest of this entry »
Posted by tom w 
The Metropolis Sampler 