Solomonoff Prediction and Occam's Razor.

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....

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Detalles Bibliográficos
Publicado en:Philosophy of Science Vol. 83; no. 4; pp. 459 - 480
Autor principal: Sterkenburg, Tom F.
Formato: Artículo
Publicado: Cambridge University Press Oct2016
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Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario: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.