Landes, Jürgen, Williamson, Jon (2015) Justifying Objective Bayesianism on Predicate Languages. Entropy, 17 (4). pp. 2459-2543. ISSN 1099-4300. (doi:10.3390/e17042459) (KAR id:48289)
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Official URL: http://doi.org/10.3390/e17042459 |
Abstract
Objective Bayesianism says that the strengths of one’s beliefs ought to be probabilities, calibrated to physical probabilities insofar as one has evidence of them, and otherwise sufficiently equivocal. These norms of belief are often explicated using the maximum entropy principle. In this paper we investigate the extent to which one can provide a unified justification of the objective Bayesian norms in the case in which the background language is a first-order predicate language, with a view to applying the resulting formalism to inductive logic. We show that the maximum entropy principle can be motivated largely in terms of minimising worst-case expected loss.
Item Type: | Article |
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DOI/Identification number: | 10.3390/e17042459 |
Subjects: |
B Philosophy. Psychology. Religion > B Philosophy (General) B Philosophy. Psychology. Religion > BC Logic Q Science > QA Mathematics (inc Computing science) > QA273 Probabilities |
Divisions: | Divisions > Division of Arts and Humanities > School of Culture and Languages |
Depositing User: | Jon Williamson |
Date Deposited: | 07 May 2015 15:30 UTC |
Last Modified: | 14 Dec 2022 00:31 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/48289 (The current URI for this page, for reference purposes) |
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