Algorithmic probability: Theory and applications

22Citations
Citations of this article
40Readers
Mendeley users who have this article in their library.
Get full text

Abstract

We first define Algorithmic Probability, an extremely powerful method of inductive inference. We discuss its completeness, incomputability, diversity and subjectivity and show that its incomputability in no way inhibits its use for practical prediction. Applications to Bernoulli sequence prediction and grammar discovery are described. We conclude with a note on its employment in a very strong AI system for very general problem solving. © 2009 Springer US.

Cite

CITATION STYLE

APA

Solomonoff, R. J. (2009). Algorithmic probability: Theory and applications. In Information Theory and Statistical Learning (pp. 1–23). Springer US. https://doi.org/10.1007/978-0-387-84816-7_1

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free