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arXiv · 2603.20274

Solomonoff induction

Tom F. Sterkenburg
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Abstract

This chapter discusses the Solomonoff approach to universal prediction. The crucial ingredient in the approach is the notion of computability, and I present the main idea as an attempt to meet two plausible computability desiderata for a universal predictor. This attempt is unsuccessful, which is shown by a generalization of a diagonalization argument due to Putnam. I then critically discuss purported gains of the approach, in particular it providing a foundation for the methodological principle of Occam's razor, and it serving as a theoretical ideal for the development of machine learning methods.

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Tom F. Sterkenburg. 2026-03-17. Solomonoff induction. https://arxiv.org/abs/2603.20274

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