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Towards a Bayesian theory of second-order uncertainty: lessons from non- standard logics

Hosni, Hykel (2014) Towards a Bayesian theory of second-order uncertainty: lessons from non- standard logics. In: Hansson, Sven Ove, (ed.) David Makinson on Classical Methods for Non-Classical Problems. Outstanding Contributions to Logic (3). Springer Dordrecht Heidelberg, New York, USA, pp. 195-221. ISBN 9789400777590

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Identification Number: 10.1007/978-94-007-7759-0


Second-order uncertainty, also known as model uncertainty and Knightian uncertainty, arises when decision-makers can (partly) model the parameters of their decision problems. It is widely believed that subjective probability, and more generally Bayesian theory, are ill-suited to represent a number of interesting second-order uncertainty features, especially “ignorance” and “ambiguity”. This failure is sometimes taken as an argument for the rejection of the whole Bayesian approach, triggering a Bayes vs anti-Bayes debate which is in many ways analogous to what the classical vs non-classical debate used to be in logic. This paper attempts to unfold this analogy and suggests that the development of non-standard logics offers very useful lessons on the contextualisation of justified norms of rationality. By putting those lessons to work I will flesh out an epistemological framework suitable for extending the expressive power of standard Bayesian norms of rationality to second- order uncertainty in a way which is both formally and foundationally conservative. Contents

Item Type: Book Section
Official URL:
Additional Information: © 2014 Springer Science+Business Media Dordrecht
Divisions: CPNSS
Subjects: B Philosophy. Psychology. Religion > BC Logic
JEL classification: D - Microeconomics > D8 - Information, Knowledge, and Uncertainty
Date Deposited: 07 May 2014 09:05
Last Modified: 20 Oct 2021 00:36

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