Towards the entropy-limit conjecture

The maximum entropy principle is widely used to determine non-committal probabilities on a finite domain, subject to a set of constraints, but its application to continuous domains is notoriously problematic. This paper concerns an intermediate case, where the domain is a first-order predicate langu...

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Published inAnnals of pure and applied logic Vol. 172; no. 2; p. 102870
Main Authors Landes, Jürgen, Rafiee Rad, Soroush, Williamson, Jon
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.02.2021
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ISSN0168-0072
DOI10.1016/j.apal.2020.102870

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Abstract The maximum entropy principle is widely used to determine non-committal probabilities on a finite domain, subject to a set of constraints, but its application to continuous domains is notoriously problematic. This paper concerns an intermediate case, where the domain is a first-order predicate language. Two strategies have been put forward for applying the maximum entropy principle on such a domain: (i) applying it to finite sublanguages and taking the pointwise limit of the resulting probabilities as the size n of the sublanguage increases; (ii) selecting a probability function on the language as a whole whose entropy on finite sublanguages of size n is not dominated by that of any other probability function for sufficiently large n. The entropy-limit conjecture says that, where these two approaches yield determinate probabilities, the two methods yield the same probabilities. If this conjecture is found to be true, it would provide a boost to the project of seeking a single canonical inductive logic—a project which faltered when Carnap's attempts in this direction succeeded only in determining a continuum of inductive methods. The truth of the conjecture would also boost the project of providing a canonical characterisation of normal or default models of first-order theories. Hitherto, the entropy-limit conjecture has been verified for languages which contain only unary predicate symbols and also for the case in which the constraints can be captured by a categorical statement of Σ1 quantifier complexity. This paper shows that the entropy-limit conjecture also holds for categorical statements of Π1 complexity, for various non-categorical constraints, and in certain other general situations.
AbstractList The maximum entropy principle is widely used to determine non-committal probabilities on a finite domain, subject to a set of constraints, but its application to continuous domains is notoriously problematic. This paper concerns an intermediate case, where the domain is a first-order predicate language. Two strategies have been put forward for applying the maximum entropy principle on such a domain: (i) applying it to finite sublanguages and taking the pointwise limit of the resulting probabilities as the size n of the sublanguage increases; (ii) selecting a probability function on the language as a whole whose entropy on finite sublanguages of size n is not dominated by that of any other probability function for sufficiently large n. The entropy-limit conjecture says that, where these two approaches yield determinate probabilities, the two methods yield the same probabilities. If this conjecture is found to be true, it would provide a boost to the project of seeking a single canonical inductive logic—a project which faltered when Carnap's attempts in this direction succeeded only in determining a continuum of inductive methods. The truth of the conjecture would also boost the project of providing a canonical characterisation of normal or default models of first-order theories. Hitherto, the entropy-limit conjecture has been verified for languages which contain only unary predicate symbols and also for the case in which the constraints can be captured by a categorical statement of Σ1 quantifier complexity. This paper shows that the entropy-limit conjecture also holds for categorical statements of Π1 complexity, for various non-categorical constraints, and in certain other general situations.
ArticleNumber 102870
Author Landes, Jürgen
Rafiee Rad, Soroush
Williamson, Jon
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  surname: Williamson
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  organization: University of Kent, Canterbury, United Kingdom
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Issue 2
Keywords 03A10
03B42
60A05
03B60
Objective Bayesianism
Probabilistic constraints on predicate languages
Inductive logic
Normal models
Default models
Maximum entropy
Language English
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Snippet The maximum entropy principle is widely used to determine non-committal probabilities on a finite domain, subject to a set of constraints, but its application...
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SubjectTerms Default models
Inductive logic
Maximum entropy
Normal models
Objective Bayesianism
Probabilistic constraints on predicate languages
Title Towards the entropy-limit conjecture
URI https://dx.doi.org/10.1016/j.apal.2020.102870
Volume 172
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