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Induction, Algorithmic Learning Theory, and Philosophy pp 157–178Cite as

Logically Reliable Inductive Inference

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Part of the book series: Logic, Epistemology, and the Unity of Science ((LEUS,volume 9))

Abstract

This paper is an overview of formal learning theory that emphasizes the philosophical motivation for the mathematical definitions. I introduce key concepts at a slow pace, comparing and contrasting with other approaches to inductive inference such as confirmation theory. A number of examples are discussed, some in detail, such as Goodman’s Riddle of Induction. I outline some important results of formal learning theory that are of philosophical interest. Finally, I discuss recent developments in this approach to inductive inference.

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Author information

Authors and Affiliations

  1. Department of Philosophy and School of Computing Science, Simon Fraser University, Burnaby, B.C. V5A 1S6, Canada

    Oliver Schulte

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  1. Oliver Schulte
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Editor information

Editors and Affiliations

  1. George Washington University, Washington, D.C, U.S.A

    Michèle Friend

  2. National University of Cordoba, Cordoba, Argentina

    Norma B. Goethe

  3. George Washington University, Washington, D.C, U.S.A

    Valentina S. Harizanov

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Schulte, O. (2007). Logically Reliable Inductive Inference. In: Friend, M., Goethe, N.B., Harizanov, V.S. (eds) Induction, Algorithmic Learning Theory, and Philosophy. Logic, Epistemology, and the Unity of Science, vol 9. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6127-1_6

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