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No Free Lunch Theorem, Inductive Skepticism, and the Optimality of Meta-induction

Published online by Cambridge University Press:  01 January 2022

Gerhard Schurz
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Abstract

The no free lunch theorem is a radicalized version of Hume’s induction skepticism. It asserts that relative to a uniform probability distribution over all possible worlds, all computable prediction algorithms—whether ‘clever’ inductive or ‘stupid’ guessing methods (etc.)—have the same expected predictive success. This theorem seems to be in conflict with results about meta-induction. According to these results, certain meta-inductive prediction strategies may dominate other (non-meta-inductive) methods in their predictive success (in the long run). In this article this conflict is analyzed and dissolved, by means of probabilistic analysis and computer simulation.

Type
Evidence and Inference
Information
Philosophy of Science , Volume 84 , Issue 5 , December 2017 , pp. 825 - 839
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

†

This work was supported by the DFG (Deutsche Forschungsgemeinschaft), SPP 1516. For valuable help I am indebted to Paul Thorn and Ronald Ortner.

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