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Mathematical Understanding

Avigad, Jeremy (2026) Mathematical Understanding. [Preprint]

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Abstract

The philosophy of mathematics has traditionally been concerned with questions about the proper justification of claims to knowledge. The goals of mathematics, however, are not limited to making true mathematical statements; ultimately, we look to mathematics for understanding. This chapter considers the ways we talk about mathematical understanding in our assessments of historical and contemporary mathematical results, in our discussions of computers in mathematics, and in mathematics education. It argues that a theory of mathematical understanding should be a theory of abilities to think and reason mathematically, and that such a theory should inform, and be informed by, practical applications. It also situates models of reasoning and understanding in the context of symbolic and neural AI, which offer complementary perspectives.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Avigad, Jeremyavigad@cmu.edu0000-0003-1275-315X
Keywords: philosophy of mathematics, artificial intelligence
Subjects: Specific Sciences > Mathematics > Epistemology
Specific Sciences > Mathematics > History
Specific Sciences > Mathematics > Practice
Specific Sciences > Mathematics > Values
Specific Sciences > Artificial Intelligence > Classical AI
Specific Sciences > Cognitive Science
Specific Sciences > Artificial Intelligence
Specific Sciences > Cognitive Science > Concepts and Representations
Specific Sciences > Artificial Intelligence > Machine Learning
Specific Sciences > Mathematics
Depositing User: Prof. Jeremy Avigad
Date Deposited: 02 Jan 2026 16:13
Last Modified: 02 Jan 2026 16:13
Item ID: 27708
Subjects: Specific Sciences > Mathematics > Epistemology
Specific Sciences > Mathematics > History
Specific Sciences > Mathematics > Practice
Specific Sciences > Mathematics > Values
Specific Sciences > Artificial Intelligence > Classical AI
Specific Sciences > Cognitive Science
Specific Sciences > Artificial Intelligence
Specific Sciences > Cognitive Science > Concepts and Representations
Specific Sciences > Artificial Intelligence > Machine Learning
Specific Sciences > Mathematics
Date: 1 January 2026
URI: https://philsci-archive.pitt.edu/id/eprint/27708

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