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Formal Epistemology

Wheeler, Gregory (2011) Formal Epistemology. [Preprint]

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Abstract

Narrowly construed, formal epistemology is a methodological approach to traditional analytic epistemology. According to this view, the aim of formal epistemology is to harness the power of formal methods to bring rigor and clarity to philosophical analysis.

Yet, in broader terms, formal epistemology is not merely a methodological tool for epistemologists, but a discipline in its own right. On this programmatic view, formal epistemology is an interdisciplinary research program that covers work by philosophers, mathematicians, computer scientists, statisticians, psychologists, operations researchers, and economists who aim to give mathematical and sometimes computational representations of, along with sound strategies for reasoning about, knowledge, belief, judgment and decision making.

This essay presents a two-pronged argument for formal epistemology. The first part addresses the general question of why anyone should bother with formal methods by illustrating, through a historical example, the role that formal models can play in inquiry. The second part describes two specific examples of recent work within formal epistemology, one that addresses a longstanding issue within traditional epistemology—namely, what to make of coherentist justification—and another addressing a fallacy of probabilistic reasoning which has implications across a wide range of disciplines, and thereby making a case for a broader, programmatic view. Finally, we close with a methodological proposal for epistemology, one that incorporates formal, experimental, and traditional approaches into one program.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Wheeler, Gregorygregory.r.wheeler@gmail.com
Subjects: General Issues > Confirmation/Induction
Specific Sciences > Probability/Statistics
Depositing User: Gregory Wheeler
Date Deposited: 12 Sep 2011 11:42
Last Modified: 12 Sep 2011 11:42
Item ID: 8780
Subjects: General Issues > Confirmation/Induction
Specific Sciences > Probability/Statistics
Date: September 2011
URI: https://philsci-archive.pitt.edu/id/eprint/8780

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