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  1. Empiricism, Probability, and Knowledge of Arithmetic.Sean Walsh - 2014 - Journal of Applied Logic 12 (3):319–348.
    The topic of this paper is our knowledge of the natural numbers, and in particular, our knowledge of the basic axioms for the natural numbers, namely the Peano axioms. The thesis defended in this paper is that knowledge of these axioms may be gained by recourse to judgements of probability. While considerations of probability have come to the forefront in recent epistemology, it seems safe to say that the thesis defended here is heterodox from the vantage point of traditional philosophy (...)
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  • The principle of signature exchangeability.Tahel Ronel & Alena Vencovská - 2016 - Journal of Applied Logic 15:16-45.
  • Six Problems in Pure Inductive Logic.J. B. Paris & A. Vencovská - 2019 - Journal of Philosophical Logic 48 (4):731-747.
    We present six significant open problems in Pure Inductive Logic, together with their background and current status, with the intention of raising awareness and leading ultimately to their resolution.
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  • A Note on Irrelevance in Inductive Logic.Jeff B. Paris & Alena Vencovská - 2011 - Journal of Philosophical Logic 40 (3):357 - 370.
    We consider two formalizations of the notion of irrelevance as a rationality principle within the framework of (Carnapian) Inductive Logic: Johnson's Sufficientness Principle, JSP, which is classically important because it leads to Carnap's influential Continuum of Inductive Methods and the recently proposed Weak Irrelevance Principle, WIP. We give a complete characterization of the language invariant probability functions satisfying WIP which generalizes the Nix-Paris Continuum. We argue that the derivation of two very disparate families of inductive methods from alternative perceptions of (...)
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  • Some Aspects of Polyadic Inductive Logic.Jürgen Landes, Jeff Paris & Alena Vencovská - 2008 - Studia Logica 90 (1):3-16.
    We give a brief account of some de Finetti style representation theorems for probability functions satisfying Spectrum Exchangeability in Polyadic Inductive Logic, together with applications to Non-splitting, Language Invariance, extensions with Equality and Instantial Relevance.
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  • A survey of some recent results on Spectrum Exchangeability in Polyadic Inductive Logic.J. Landes, J. B. Paris & A. Vencovská - 2011 - Synthese 181 (S1):19 - 47.
    We give a unified account of some results in the development of Polyadic Inductive Logic in the last decade with particular reference to the Principle of Spectrum Exchangeability, its consequences for Instantial Relevance, Language Invariance and Johnson's Sufficientness Principle, and the corresponding de Finetti style representation theorems.
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  • A characterization of the language invariant families satisfying spectrum exchangeability in polyadic inductive logic.Jürgen Landes, Jeff B. Paris & Alena Vencovská - 2010 - Annals of Pure and Applied Logic 161 (6):800-811.
    A necessary and sufficient condition in terms of a de Finetti style representation is given for a probability function in Polyadic Inductive Logic to satisfy being part of a Language Invariant family satisfying Spectrum Exchangeability. This theorem is then considered in relation to the unary Carnap and Nix–Paris Continua.
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  • An examination of the SEP candidate analogical inference rule within pure inductive logic.E. Howarth, J. B. Paris & A. Vencovská - 2016 - Journal of Applied Logic 14:22-45.
  • The Counterpart Principle of Analogical Support by Structural Similarity.Alexandra Hill & Jeffrey Bruce Paris - 2014 - Erkenntnis 79 (S6):1-16.
    We propose and investigate an Analogy Principle in the context of Unary Inductive Logic based on a notion of support by structural similarity which is often employed to motivate scientific conjectures.
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  • Statistics as Inductive Inference.Jan-Willem Romeijn - unknown
    An inductive logic is a system of inference that describes the relation between propositions on data, and propositions that extend beyond the data, such as predictions over future data, and general conclusions on all possible data. Statistics, on the other hand, is a mathematical discipline that describes procedures for deriving results about a population from sample data. These results include predictions on future samples, decisions on rejecting or accepting a hypothesis about the population, the determination of probability assignments over such (...)
     
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