journal article Oct 01, 2016

Solomonoff Prediction and Occam’s Razor

Abstract
Algorithmic information theory gives an idealized notion of compressibility that is often presented as an objective measure of simplicity. It is suggested at times that Solomonoff prediction, or algorithmic information theory in a predictive setting, can deliver an argument to justify Occam’s razor. This article explicates the relevant argument and, by converting it into a Bayesian framework, reveals why it has no such justificatory force. The supposed simplicity concept is better perceived as a specific inductive assumption, the assumption of effectiveness. It is this assumption that is the characterizing element of Solomonoff prediction and wherein its philosophical interest lies.
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Metrics
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Citations
49
References
Details
Published
Oct 01, 2016
Vol/Issue
83(4)
Pages
459-479
License
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Cite This Article
Tom F. Sterkenburg (2016). Solomonoff Prediction and Occam’s Razor. Philosophy of Science, 83(4), 459-479. https://doi.org/10.1086/687257
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