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.
CITATION STYLE
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
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