Vitanyi, PaulLegg, ShaneHutter, Marcus2015-08-282015-08-281941-6016http://hdl.handle.net/1885/15013Algorithmic "Solomonoff" Probability (AP) assigns to objects an a priori probability that is in some sense universal. This prior distribution has theoretical applications in a number of areas, including inductive inference theory and the time complexity analysis of algorithms. Its main drawback is that it is not computable and thus can only be approximated in practice.http://www.scholarpedia.org/article/Scholarpedia:About..."all published articles contents are available under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License (please see the Terms of Use)" as at 27/08/2015algorithmic information theoryalgorithmic complexitydiscrete/continuous algorithmic probability200710.4249/scholarpedia.2572