The document discusses the Infinite Monkey Theorem. It provides references to papers and authors that are relevant to the theorem, including foundational works by Solomonoff, Kolmogorov, Levin, and Chaitin on algorithmic information theory and inductive inference. The references cover the original formulation of the theorem, its properties, applications to artificial intelligence, and relationships to concepts of information, randomness, and probability theory.

1. The Infinite
Programming
Monkey
Dr. Hector Zenil

4. 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/