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Springer - Induction, Algorithmic Learning Theory, and Philosophy

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Description

This volume from the Logic, Epistemology, and the Unity of Science series explores the intersection of algorithmic learning theory, philosophy, and mathematics. The content originated from a series of talks by Frank Stephan and John Case held at the George Washington University Mathematics Department. This work facilitates a specialized exchange of ideas between philosophers, mathematicians, and computer scientists. By bringing together these distinct disciplines, the text addresses developments in algorithmic learning theory through a multi-disciplinary lens. It serves as a significant contribution to the study of induction and its relationship to computational and philosophical frameworks.

Key Features

Published by Springer as part of the Logic, Epistemology, and the Unity of Science series, volume 9.

Integrates perspectives from philosophers, mathematicians, and computer scientists regarding algorithmic learning theory.

Based on academic talks delivered by Frank Stephan and John Case at George Washington University.

Provides a specialized exploration of induction and algorithmic learning developments.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
25 November 2010
Listed Since
20 September 2010

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