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

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Schurz, Gerhard
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conference paper description
The no free lunch theorem (Wolpert 1996) 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 (Schurz 2008). 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 paper this conflict is analyzed and dissolved, by means of probabilistic analysis and computer simulation.