Minds and Machines 26 (1-2):31-59 (2016)

Gerhard Schurz
Heinrich Heine University Düsseldorf
Paul D. Thorn
Heinrich Heine University Düsseldorf
According to the paradigm of adaptive rationality, successful inference and prediction methods tend to be local and frugal. As a complement to work within this paradigm, we investigate the problem of selecting an optimal combination of prediction methods from a given toolbox of such local methods, in the context of changing environments. These selection methods are called meta-inductive strategies, if they are based on the success-records of the toolbox-methods. No absolutely optimal MI strategy exists—a fact that we call the “revenge of ecological rationality”. Nevertheless one can show that a certain MI strategy exists, called “AW”, which is universally long-run optimal, with provably small short-run losses, in comparison to any set of prediction methods that it can use as input. We call this property universal access-optimality. Local and short-run improvements over AW are possible, but only at the cost of forfeiting universal access-optimality. The last part of the paper includes an empirical study of MI strategies in application to an 8-year-long data set from the Monash University Footy Tipping Competition
Keywords Prediction task  Adaptive rationality  Strategy selection  Meta-induction  Online learning
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DOI 10.1007/s11023-015-9369-7
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References found in this work BETA

Logical Foundations of Probability.Rudolf Carnap - 1950 - Chicago]University of Chicago Press.
The Logic of Reliable Inquiry.Kevin Kelly - 1996 - Oxford University Press USA.

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Citations of this work BETA

The Ecological Rationality of Explanatory Reasoning.Igor Douven - 2020 - Studies in History and Philosophy of Science Part A 79:1-14.
Optimisation in a Synchronised Prediction Setting.Christian Feldbacher-Escamilla - 2017 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 48 (3):419-437.

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