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Assigning Probabilities to Logical Formulas

In Jaakko Hintikka (ed.), Aspects of inductive logic. Amsterdam,: North Holland Pub. Co.. pp. 219 -- 264 (1967)

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  1. Is Causal Reasoning Harder Than Probabilistic Reasoning?Milan Mossé, Duligur Ibeling & Thomas Icard - 2024 - Review of Symbolic Logic 17 (1):106-131.
    Many tasks in statistical and causal inference can be construed as problems of entailment in a suitable formal language. We ask whether those problems are more difficult, from a computational perspective, for causal probabilistic languages than for pure probabilistic (or “associational”) languages. Despite several senses in which causal reasoning is indeed more complex—both expressively and inferentially—we show that causal entailment (or satisfiability) problems can be systematically and robustly reduced to purely probabilistic problems. Thus there is no jump in computational complexity. (...)
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  • Timothy Williamson’s Coin-Flipping Argument: Refuted Prior to Publication?Colin Howson - 2019 - Erkenntnis 86 (3):575-583.
    In a well-known paper, Timothy Williamson claimed to prove with a coin-flipping example that infinitesimal-valued probabilities cannot save the principle of Regularity, because on pain of inconsistency the event ‘all tosses land heads’ must be assigned probability 0, whether the probability function is hyperreal-valued or not. A premise of Williamson’s argument is that two infinitary events in that example must be assigned the same probability because they are isomorphic. It was argued by Howson that the claim of isomorphism fails, but (...)
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  • A Note on Binary Inductive Logic.C. J. Nix & J. B. Paris - 2007 - Journal of Philosophical Logic 36 (6):735-771.
    We consider the problem of induction over languages containing binary relations and outline a way of interpreting and constructing a class of probability functions on the sentences of such a language. Some principles of inductive reasoning satisfied by these probability functions are discussed, leading in turn to a representation theorem for a more general class of probability functions satisfying these principles.
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  • Philosophy as conceptual engineering: Inductive logic in Rudolf Carnap's scientific philosophy.Christopher F. French - 2015 - Dissertation, University of British Columbia
    My dissertation explores the ways in which Rudolf Carnap sought to make philosophy scientific by further developing recent interpretive efforts to explain Carnap’s mature philosophical work as a form of engineering. It does this by looking in detail at his philosophical practice in his most sustained mature project, his work on pure and applied inductive logic. I, first, specify the sort of engineering Carnap is engaged in as involving an engineering design problem and then draw out the complications of design (...)
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  • Representation and Invariance of Scientific Structures.Patrick Suppes - 2002 - CSLI Publications (distributed by Chicago University Press).
    An early, very preliminary edition of this book was circulated in 1962 under the title Set-theoretical Structures in Science. There are many reasons for maintaining that such structures play a role in the philosophy of science. Perhaps the best is that they provide the right setting for investigating problems of representation and invariance in any systematic part of science, past or present. Examples are easy to cite. Sophisticated analysis of the nature of representation in perception is to be found already (...)
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  • Probability, logic, and probability logic.Alan Hójek - 2001 - In Lou Goble (ed.), The Blackwell Guide to Philosophical Logic. Malden, Mass.: Wiley-Blackwell. pp. 362--384.
    ‘Probability logic’ might seem like an oxymoron. Logic traditionally concerns matters immutable, necessary and certain, while probability concerns the uncertain, the random, the capricious. Yet our subject has a distinguished pedigree. Ramsey begins his classic “Truth and Probability” with the words: “In this essay the Theory of Probability is taken as a branch of logic. … “speaks of “the logic of the probable.” And more recently, regards probabilities as estimates of truth values, and thus probability theory as a natural outgrowth (...)
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  • (1 other version)Interpretations of probability.Alan Hájek - 2007 - Stanford Encyclopedia of Philosophy.
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  • Uncertainty, Rationality, and Agency.Wiebe van der Hoek - 2006 - Dordrecht, Netherland: Springer.
    This volume concerns Rational Agents - humans, players in a game, software or institutions - which must decide the proper next action in an atmosphere of partial information and uncertainty. The book collects formal accounts of Uncertainty, Rationality and Agency, and also of their interaction. It will benefit researchers in artificial systems which must gather information, reason about it and then make a rational decision on which action to take.
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  • Quantifier probability logic and the confirmation paradox.Theodore Hailperin - 2007 - History and Philosophy of Logic 28 (1):83-100.
    Exhumation and study of the 1945 paradox of confirmation brings out the defect of its formulation. In the context of quantifier conditional-probability logic it is shown that a repair can be accomplished if the truth-functional conditional used in the statement of the paradox is replaced with a connective that is appropriate to the probabilistic context. Description of the quantifier probability logic involved in the resolution of the paradox is presented in stages. Careful distinction is maintained between a formal logic language (...)
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  • (2 other versions)First-order classical modal logic.Horacio Arló-Costa & Eric Pacuit - 2006 - Studia Logica 84 (2):171 - 210.
    The paper focuses on extending to the first order case the semantical program for modalities first introduced by Dana Scott and Richard Montague. We focus on the study of neighborhood frames with constant domains and we offer in the first part of the paper a series of new completeness results for salient classical systems of first order modal logic. Among other results we show that it is possible to prove strong completeness results for normal systems without the Barcan Formula (like (...)
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  • Repelling a Prussian charge with a solution to a paradox of Dubins.Colin Howson - 2018 - Synthese 195 (1).
    Pruss uses an example of Lester Dubins to argue against the claim that appealing to hyperreal-valued probabilities saves probabilistic regularity from the objection that in continuum outcome-spaces and with standard probability functions all save countably many possibilities must be assigned probability 0. Dubins’s example seems to show that merely finitely additive standard probability functions allow reasoning to a foregone conclusion, and Pruss argues that hyperreal-valued probability functions are vulnerable to the same charge. However, Pruss’s argument relies on the rule of (...)
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  • A Continuum-Valued Logic of Degrees of Probability.Colin Howson - 2014 - Erkenntnis 79 (5):1001-1013.
    Leibniz seems to have been the first to suggest a logical interpretation of probability, but there have always seemed formidable mathematical and interpretational barriers to implementing the idea. De Finetti revived it only, it seemed, to reject it in favour of a purely decision-theoretic approach. In this paper I argue that not only is it possible to view (Bayesian) probability as a continuum-valued logic, but that it has a very close formal kinship with classical propositional logic.
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  • Finite additivity, another lottery paradox and conditionalisation.Colin Howson - 2014 - Synthese 191 (5):1-24.
    In this paper I argue that de Finetti provided compelling reasons for rejecting countable additivity. It is ironical therefore that the main argument advanced by Bayesians against following his recommendation is based on the consistency criterion, coherence, he himself developed. I will show that this argument is mistaken. Nevertheless, there remain some counter-intuitive consequences of rejecting countable additivity, and one in particular has all the appearances of a full-blown paradox. I will end by arguing that in fact it is no (...)
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  • Probability logic in the twentieth century.Theodore Hailperin - 1991 - History and Philosophy of Logic 12 (1):71-110.
    This essay describes a variety of contributions which relate to the connection of probability with logic. Some are grand attempts at providing a logical foundation for probability and inductive inference. Others are concerned with probabilistic inference or, more generally, with the transmittance of probability through the structure (logical syntax) of language. In this latter context probability is considered as a semantic notion playing the same role as does truth value in conventional logic. At the conclusion of the essay two fully (...)
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  • Logic and probabilistic systems.Franco Montagna, Giulia Simi & Andrea Sorbi - 1996 - Archive for Mathematical Logic 35 (4):225-261.
    Following some ideas of Roberto Magari, we propose trial and error probabilistic functions, i.e. probability measures on the sentences of arithmetic that evolve in time by trial and error. The set ℐ of the sentences that get limit probability 1 is a Π3—theory, in fact ℐ can be a Π3—complete set. We prove incompleteness results for this setting, by showing for instance that for every k > 0 there are true Π3—sentences that get limit probability less than 1/2k. No set (...)
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  • (1 other version)A p‐adic probability logic.Angelina Ilić-Stepić, Zoran Ognjanović, Nebojša Ikodinović & Aleksandar Perović - 2012 - Mathematical Logic Quarterly 58 (4-5):263-280.
    In this article we present a p-adic valued probabilistic logic equation image which is a complete and decidable extension of classical propositional logic. The key feature of equation image lies in ability to formally express boundaries of probability values of classical formulas in the field equation image of p-adic numbers via classical connectives and modal-like operators of the form Kr, ρ. Namely, equation image is designed in such a way that the elementary probability sentences Kr, ρα actually do have their (...)
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  • Quantum logic as a fragment of independence-friendly logic.Jaakko Hintikka - 2002 - Journal of Philosophical Logic 31 (3):197-209.
    The working assumption of this paper is that noncommuting variables are irreducibly interdependent. The logic of such dependence relations is the author's independence-friendly (IF) logic, extended by adding to it sentence-initial contradictory negation ¬ over and above the dual (strong) negation ∼. Then in a Hilbert space ∼ turns out to express orthocomplementation. This can be extended to any logical space, which makes it possible to define the dimension of a logical space. The received Birkhoff and von Neumann "quantum logic" (...)
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  • A first-order probabilistic logic with approximate conditional probabilities.N. Ikodinovi, M. Ra Kovi, Z. Markovi & Z. Ognjanovi - 2014 - Logic Journal of the IGPL 22 (4):539-564.
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  • Modelling uncertain inference.Colin Howson - 2012 - Synthese 186 (2):475-492.
    Kyburg’s opposition to the subjective Bayesian theory, and in particular to its advocates’ indiscriminate and often questionable use of Dutch Book arguments, is documented and much of it strongly endorsed. However, it is argued that an alternative version, proposed by both de Finetti at various times during his long career, and by Ramsey, is less vulnerable to Kyburg’s misgivings. This is a logical interpretation of the formalism, one which, it is argued, is both more natural and also avoids other, widely-made (...)
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  • Naive Probability: Model‐Based Estimates of Unique Events.Sangeet S. Khemlani, Max Lotstein & Philip N. Johnson-Laird - 2015 - Cognitive Science 39 (6):1216-1258.
    We describe a dual-process theory of how individuals estimate the probabilities of unique events, such as Hillary Clinton becoming U.S. President. It postulates that uncertainty is a guide to improbability. In its computer implementation, an intuitive system 1 simulates evidence in mental models and forms analog non-numerical representations of the magnitude of degrees of belief. This system has minimal computational power and combines evidence using a small repertoire of primitive operations. It resolves the uncertainty of divergent evidence for single events, (...)
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  • Non-additive degrees of belief.Rolf Haenni - 2009 - In Franz Huber & Christoph Schmidt-Petri (eds.), Degrees of belief. London: Springer. pp. 121--159.
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  • Epistemic Probability and Coherent Degrees of Belief.Colin Howson - 2009 - In Franz Huber & Christoph Schmidt-Petri (eds.), Degrees of belief. London: Springer. pp. 97--119.
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  • (1 other version)Probability Logic and Borel's Denumerable Probability.Theodore Hailperin - 2008 - History and Philosophy of Logic 29 (2):147-165.
    Borel's concept of denumerable probability is described by means of three of his illustrative problems and their solution. These problems are then reformulated in contemporary terms and solved from the viewpoint of probability logic. A section compares Kolmogorov set-theoretic probability with probability logic. The concluding section describes a highly adverse criticism of Borel's conception for its not using something like Kolmogorov theory and, in support of Borel, this criticism is countered from the standpoint of quantifier probability logic.
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  • States on Polyadic MV-algebras.George Georgescu - 2010 - Studia Logica 94 (2):231-243.
    This paper is a contribution to the algebraic logic of probabilistic models of Łukasiewicz predicate logic. We study the MV-states defined on polyadic MV-algebras and prove an algebraic many-valued version of Gaifman’s completeness theorem.
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  • A Logic For Inductive Probabilistic Reasoning.Manfred Jaeger - 2005 - Synthese 144 (2):181-248.
    Inductive probabilistic reasoning is understood as the application of inference patterns that use statistical background information to assign (subjective) probabilities to single events. The simplest such inference pattern is direct inference: from “70% of As are Bs” and “a is an A” infer that a is a B with probability 0.7. Direct inference is generalized by Jeffrey’s rule and the principle of cross-entropy minimization. To adequately formalize inductive probabilistic reasoning is an interesting topic for artificial intelligence, as an autonomous system (...)
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  • Paraconsistent conjectural deduction based on logical entropy measures I: C-systems as non-standard inference framework.Paola Forcheri & Paolo Gentilini - 2005 - Journal of Applied Non-Classical Logics 15 (3):285-319.
    A conjectural inference is proposed, aimed at producing conjectural theorems from formal conjectures assumed as axioms, as well as admitting contradictory statements as conjectural theorems. To this end, we employ Paraconsistent Informational Logic, which provides a formal setting where the notion of conjecture formulated by an epistemic agent can be defined. The paraconsistent systems on which conjectural deduction is based are sequent formulations of the C-systems presented in Carnielli-Marcos [CAR 02b]. Thus, conjectural deduction may also be considered to be a (...)
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  • Probabilities defined on standard and non-standard cylindric set algebras.Miklós Ferenczi - 2015 - Synthese 192 (7):2025-2033.
    Cylindric set algebras are algebraizations of certain logical semantics. The topic surveyed here, i.e. probabilities defined on cylindric set algebras, is closely related, on the one hand, to probability logic (to probabilities defined on logical formulas), on the other hand, to measure theory. The set algebras occuring here are associated, in particular, with the semantics of first order logic and with non-standard analysis. The probabilities introduced are partially continous, they are continous with respect to so-called cylindric sums.
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  • Towards a Model Theory of Statistical Theories.Tomáš Havránek - 1977 - Synthese 36 (4):441-458.
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  • Reviews. [REVIEW]Ilkka Niiniluoto & Ronald Giere - 1975 - Synthese 31 (1):161-199.
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