4.10 Algorithmic Probability and the Universal Distribution
Channel: Complexity Explorer
Date: 21/08/2018

Unit 4 Module 10
Algorithmic Information Dynamics: A Computational Approach to Causality and Living Systems---From Networks to Cells
by Hector Zenil and Narsis A. Kiani

Algorithmic Dynamics Lab
www.algorithmicdynamics.net

Refs:

- R. J. Solomonoff, "A formal theory of inductive inference: Parts 1 and 2. Information and Control," 7:1--22 and 224--254, 1964.

- R. J. Solomonoff, "Algorithmic Probability\[LongDash]Its Discovery\[LongDash]Its Properties and Application to Strong AI," In H. Zenil (ed), Randomness Through Computation: Some Answers, More Questions, World Scientific, 2012.

- M. Li and P. Vitányi, An introduction to Kolmogorov complexity and its applications, 2nd edition, Springer-Verlag, Berlin, 1997.

- L.A. Levin, "Laws of information conservation (non-growth) and aspects of the foundation of probability theory," Problems Information Transmission, 10(3):206-210, 1974.

- A. K. Zvonkin and L. A. Levin, "The complexity of finite objects and the development of the concepts of information and randomness by means of the theory of algorithms," Russian Mathematical Surveys, 25(6):83--124, 1970.

- G.J. Chaitin. Algorithmic Information Theory, Cambridge University Press, Cambridge, 1987.

- A.N. Kolmogorov, "Three approaches to the quantitative definition of information," Problems of Information Transmission 1, 1-11, 1965.

- H. Zenil and F. Soler-Toscano, "Infinite Monkey Theorem", Wolfram Demonstrations Project, Published: October 22, 2013
http://demonstrations.wolfram.com/InfiniteMonkeyTheorem/