Stanford Encyclopedia of Philosophy (2008)

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Formal learning theory is the mathematical embodiment of a normative epistemology. It deals with the question of how an agent should use observations about her environment to arrive at correct and informative conclusions. Philosophers such as Putnam, Glymour and Kelly have developed learning theory as a normative framework for scientific reasoning and inductive inference.
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References found in this work BETA

Modal Logic: An Introduction.Brian F. Chellas - 1980 - Cambridge University Press.
Dynamic Epistemic Logic.Hans van Ditmarsch, Wiebe van der Hoek & Barteld Kooi - 2016 - Internet Encyclopedia of Philosophy.
Logics of Public Communications.Jan Plaza - 2007 - Synthese 158 (2):165 - 179.
The Foundations of Statistics.Leonard J. Savage - 1956 - Philosophy of Science 23 (2):166-166.

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Citations of this work BETA

Confirmation and Induction.Franz Huber - 2007 - Internet Encyclopedia of Philosophy.

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Logically Reliable Inductive Inference.Oliver Schulte - 2007 - In Michele Friend, Norma B. Goethe & Valentina Harizanov (eds.), Induction, algorithmic learning theory, and philosophy. Springer. pp. 157-178.
Agency and Interaction What We Are and What We Do in Formal Epistemology.Jeffrey Helzner & Vincent Hendricks - 2010 - Journal of the Indian Council of Philosophical Research 27 (2).
The Logic of Reliable and Efficient Inquiry.Oliver Schulte - 1999 - Journal of Philosophical Logic 28 (4):399-438.
Formal Learning Theory and the Philosophy of Science.Kevin T. Kelly - 1988 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1988:413 - 423.

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