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Square of opposition under coherence

In M. B. Ferraro, P. Giordani, B. Vantaggi, M. Gagolewski, P. Grzegorzewski, O. Hryniewicz & María Ángeles Gil (eds.), Soft Methods for Data Science. pp. 407-414 (2017)

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  1. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.Judea Pearl - 1988 - Morgan Kaufmann.
    The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
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  • (2 other versions)Counterfactuals.David Lewis - 1973 - Foundations of Language 13 (1):145-151.
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  • (2 other versions)Counterfactuals.David Lewis - 1973 - Philosophy of Science 42 (3):341-344.
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  • (1 other version)On the logic of theory change: Partial meet contraction and revision functions.Carlos E. Alchourrón, Peter Gärdenfors & David Makinson - 1985 - Journal of Symbolic Logic 50 (2):510-530.
    This paper extends earlier work by its authors on formal aspects of the processes of contracting a theory to eliminate a proposition and revising a theory to introduce a proposition. In the course of the earlier work, Gardenfors developed general postulates of a more or less equational nature for such processes, whilst Alchourron and Makinson studied the particular case of contraction functions that are maximal, in the sense of yielding a maximal subset of the theory (or alternatively, of one of (...)
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  • Bayesian Rationality: The Probabilistic Approach to Human Reasoning.Mike Oaksford & Nick Chater - 2007 - Oxford University Press.
    Are people rational? This question was central to Greek thought and has been at the heart of psychology and philosophy for millennia. This book provides a radical and controversial reappraisal of conventional wisdom in the psychology of reasoning, proposing that the Western conception of the mind as a logical system is flawed at the very outset. It argues that cognition should be understood in terms of probability theory, the calculus of uncertain reasoning, rather than in terms of logic, the calculus (...)
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  • A Mathematical Theory of Evidence.Glenn Shafer - 1976 - Princeton University Press.
    Degrees of belief; Dempster's rule of combination; Simple and separable support functions; The weights of evidence; Compatible frames of discernment; Support functions; The discernment of evidence; Quasi support functions; Consonance; Statistical evidence; The dual nature of probable reasoning.
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  • Statistical Reasoning with Imprecise Probabilities.Peter Walley - 1991 - Chapman & Hall.
    An examination of topics involved in statistical reasoning with imprecise probabilities. The book discusses assessment and elicitation, extensions, envelopes and decisions, the importance of imprecision, conditional previsions and coherent statistical models.
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  • On conditionals.Dorothy Edgington - 1995 - Mind 104 (414):235-329.
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  • General Propositions and Causality.Frank Plumpton Ramsey - 1925 - In The Foundations of Mathematics and Other Logical Essays. London, England: Routledge & Kegan Paul. pp. 237-255.
    This article rebuts Ramsey's earlier theory, in 'Universals of Law and of Fact', of how laws of nature differ from other true generalisations. It argues that our laws are rules we use in judging 'if I meet an F I shall regard it as a G'. This temporal asymmetry is derived from that of cause and effect and used to distinguish what's past as what we can know about without knowing our present intentions.
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  • Syntax and semantics of questions.Lauri Karttunen - 1977 - Linguistics and Philosophy 1 (1):3--44.
    W. Labov's & T. Labov's findings concerning their child grammar acquisition ("Learning the Syntax of Questions" in Recent Advances in the Psychology of Language, Campbell, R. & Smith, P. Eds, New York: Plenum Press, 1978) are interpreted in terms of different semantics of why & other wh-questions. Z. Dubiel.
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  • (1 other version)Knowledge in Flux. Modeling the Dynamics of Epistemic States.Peter Gärdenfors - 1988 - Studia Logica 49 (3):421-424.
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  • Questions in montague english.Charles L. Hamblin - 1973 - Foundations of Language 10 (1):41-53.
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  • Erratum: Probabilities of Conditionals and Conditional Probabilities.David Lewis - 1976 - Philosophical Review 85 (4):561.
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  • Probability, Induction and Statistics: The Art of Guessing.Bruno De Finetti - 1972 - New York: John Wiley.
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  • Likelihood.Anthony William Fairbank Edwards - 1972 - Cambridge [Eng.]: University Press.
    Dr Edwards' stimulating and provocative book advances the thesis that the appropriate axiomatic basis for inductive inference is not that of probability, with its addition axiom, but rather likelihood - the concept introduced by Fisher as a measure of relative support amongst different hypotheses. Starting from the simplest considerations and assuming no more than a modest acquaintance with probability theory, the author sets out to reconstruct nothing less than a consistent theory of statistical inference in science.
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  • (1 other version)The Logic of Conditionals.Ernest Adams, Ernest W. Adams, Jaakko Hintikka & Patrick Suppes - 1965 - Journal of Symbolic Logic 39 (3):609-611.
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  • (1 other version)Unended Quest: An Intellectual Autobiography.Karl Raimund Popper - 1976 - New York: Routledge.
    At the age of eight, Karl Popper was puzzling over the idea of infinity and by fifteen was beginning to take a keen interest in his father's well-stocked library of books. Unended Quest recounts these moments and many others in the life of one of the most influential thinkers of the twentieth century, providing an indispensable account of the ideas that influenced him most. As an introduction to Popper's philosophy, Unended Quest also shines. Popper lucidly explains the central ideas in (...)
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  • (2 other versions)A Philosophical Guide to Conditionals.Jonathan Bennett - 2003 - Tijdschrift Voor Filosofie 66 (2):379-380.
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  • (2 other versions)A Philosophical Guide to Conditionals.Jonathan Bennett - 2005 - Philosophical Quarterly 55 (220):524-526.
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  • Conditionals.Angelika Kratzer - 1986 - Chicago Linguistics Society 22 (2):1–15.
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  • Questions.C. L. Hamblin - 1958 - Australasian Journal of Philosophy 36 (3):159 – 168.
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  • Probabilities of Conditionals.Bas van Fraassen - 1975 - In C. Hooker (ed.), Foundations of probability theory, statistical inference, and statistical theories of science. Springer.
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  • Subjective Probability and Expected Utility without Additivity.David Schmeidler - 1989 - Econometrica 57:571-589.
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  • On the logic of iterated belief revision.Adnan Darwiche & Judea Pearl - 1997 - Artificial Intelligence 89 (1-2):1-29.
    We show in this paper that the AGM postulates are too weak to ensure the rational preservation of conditional beliefs during belief revision, thus permitting improper responses to sequences of observations. We remedy this weakness by proposing four additional postulates, which are sound relative to a qualitative version of probabilistic conditioning. Contrary to the AGM framework, the proposed postulates characterize belief revision as a process which may depend on elements of an epistemic state that are not necessarily captured by a (...)
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  • Propositional knowledge base revision and minimal change.Hirofumi Katsuno & Alberto O. Mendelzon - 1991 - Artificial Intelligence 52 (3):263-294.
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  • Conditional probabilities and compounds of conditionals.Vann McGee - 1989 - Philosophical Review 98 (4):485-541.
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  • Betting on conditionals.Jean Baratgin, David E. Over & Guy Politzer - 2010 - Thinking and Reasoning 16 (3):172-197.
    A study is reported testing two hypotheses about a close parallel relation between indicative conditionals, if A then B , and conditional bets, I bet you that if A then B . The first is that both the indicative conditional and the conditional bet are related to the conditional probability, P(B|A). The second is that de Finetti's three-valued truth table has psychological reality for both types of conditional— true , false , or void for indicative conditionals and win , lose (...)
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  • The Adams family.Igor Douven & Sara Verbrugge - 2010 - Cognition 117 (3):302-318.
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  • New paradigm psychology of reasoning.David E. Over - 2009 - Thinking and Reasoning 15 (4):431-438.
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  • Description Logic Handbook.Franz Baader (ed.) - 2003 - Cambridge University Press.
    The Description Logic Handbook covers all aspects of the research in the field of knowledge representation. Written by some of the most prominent researchers in the field, and covering the basic technical material and implementational aspects, it is both a unique reference and a self-study guide.
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  • Uncertainty and the de Finetti tables.Jean Baratgin, David E. Over & Guy Politzer - 2013 - Thinking and Reasoning 19 (3-4):308-328.
    The new paradigm in the psychology of reasoning adopts a Bayesian, or prob- abilistic, model for studying human reasoning. Contrary to the traditional binary approach based on truth functional logic, with its binary values of truth and falsity, a third value that represents uncertainty can be introduced in the new paradigm. A variety of three-valued truth table systems are available in the formal literature, including one proposed by de Finetti. We examine the descriptive adequacy of these systems for natural language (...)
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  • Reasoning About Uncertain Conditionals.Niki Pfeifer - 2014 - Studia Logica 102 (4):849-866.
    There is a long tradition in formal epistemology and in the psychology of reasoning to investigate indicative conditionals. In psychology, the propositional calculus was taken for granted to be the normative standard of reference. Experimental tasks, evaluation of the participants’ responses and psychological model building, were inspired by the semantics of the material conditional. Recent empirical work on indicative conditionals focuses on uncertainty. Consequently, the normative standard of reference has changed. I argue why neither logic nor standard probability theory provide (...)
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  • (1 other version)Vagueness. An exercise in logical analysis.Max Black - 1937 - Philosophy of Science 4 (4):427-455.
    It is a paradox, whose importance familiarity fails to diminish, that the most highly developed and useful scientific theories are ostensibly expressed in terms of objects never encountered in experience. The line traced by a draughtsman, no matter how accurate, is seen beneath the microscope as a kind of corrugated trench, far removed from the ideal line of pure geometry. And the “point-planet” of astronomy, the “perfect gas” of thermodynamics, or the “pure species” of genetics are equally remote from exact (...)
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  • The new psychology of reasoning: A mental probability logical perspective.Niki Pfeifer - 2013 - Thinking and Reasoning 19 (3-4):329-345.
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  • The Probabilities of Conditionals Revisited.Igor Douven & Sara Verbrugge - 2013 - Cognitive Science 37 (4):711-730.
    According to what is now commonly referred to as “the Equation” in the literature on indicative conditionals, the probability of any indicative conditional equals the probability of its consequent of the conditional given the antecedent of the conditional. Philosophers widely agree in their assessment that the triviality arguments of Lewis and others have conclusively shown the Equation to be tenable only at the expense of the view that indicative conditionals express propositions. This study challenges the correctness of that assessment by (...)
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  • The computational complexity of probabilistic inference using bayesian belief networks.Gregory F. Cooper - 1990 - Artificial Intelligence 42 (2-3):393-405.
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  • Probabilities of conditionals in context.Justin Khoo - 2016 - Linguistics and Philosophy 39 (1):1-43.
    The Ramseyan thesis that the probability of an indicative conditional is equal to the corresponding conditional probability of its consequent given its antecedent is both widely confirmed and subject to attested counterexamples (e.g., McGee 2000, Kaufmann 2004). This raises several puzzling questions. For instance, why are there interpretations of conditionals that violate this Ramseyan thesis in certain contexts, and why are they otherwise very rare? In this paper, I raise some challenges to Stefan Kaufmann's account of why the Ramseyan thesis (...)
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  • Bayesian reasoning with ifs and ands and ors.Nicole Cruz, Jean Baratgin, Mike Oaksford & David E. Over - 2015 - Frontiers in Psychology 6.
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  • Framing human inference by coherence based probability logic.Niki Pfeifer & Gernot D. Kleiter - 2009 - Journal of Applied Logic 7 (2):206--217.
    We take coherence based probability logic as the basic reference theory to model human deductive reasoning. The conditional and probabilistic argument forms are explored. We give a brief overview of recent developments of combining logic and probability in psychology. A study on conditional inferences illustrates our approach. First steps towards a process model of conditional inferences conclude the paper.
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  • Coherent choice functions under uncertainty.Teddy Seidenfeld, Mark J. Schervish & Joseph B. Kadane - 2010 - Synthese 172 (1):157-176.
    We discuss several features of coherent choice functions—where the admissible options in a decision problem are exactly those that maximize expected utility for some probability/utility pair in fixed set S of probability/utility pairs. In this paper we consider, primarily, normal form decision problems under uncertainty—where only the probability component of S is indeterminate and utility for two privileged outcomes is determinate. Coherent choice distinguishes between each pair of sets of probabilities regardless the “shape” or “connectedness” of the sets of probabilities. (...)
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  • The traditional square of opposition.Terence Parsons - 2008 - Stanford Encyclopedia of Philosophy.
    This entry traces the historical development of the Square of Opposition, a collection of logical relationships traditionally embodied in a square diagram. This body of doctrine provided a foundation for work in logic for over two millenia. For most of this history, logicians assumed that negative particular propositions ("Some S is not P") are vacuously true if their subjects are empty. This validates the logical laws embodied in the diagram, and preserves the doctrine against modern criticisms. Certain additional principles ("contraposition" (...)
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  • The hypothesis of the conditional construal of conditional probability.Alan Hájek & N. Hall - 1994 - In Ellery Eells & Brian Skyrms (eds.), Probability and Conditionals: Belief Revision and Rational Decision. New York: Cambridge University Press. pp. 75.
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  • Conditional Random Quantities and Compounds of Conditionals.Angelo Gilio & Giuseppe Sanfilippo - 2014 - Studia Logica 102 (4):709-729.
    In this paper we consider conditional random quantities (c.r.q.’s) in the setting of coherence. Based on betting scheme, a c.r.q. X|H is not looked at as a restriction but, in a more extended way, as \({XH + \mathbb{P}(X|H)H^c}\) ; in particular (the indicator of) a conditional event E|H is looked at as EH + P(E|H)H c . This extended notion of c.r.q. allows algebraic developments among c.r.q.’s even if the conditioning events are different; then, for instance, we can give a (...)
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  • Conditioning against the grain.Stefan Kaufmann - 2004 - Journal of Philosophical Logic 33 (6):583-606.
    This paper discusses counterexamples to the thesis that the probabilities of conditionals are conditional probabilities. It is argued that the discrepancy is systematic and predictable, and that conditional probabilities are crucially involved in the apparently deviant interpretations. Furthermore, the examples suggest that such conditionals have a less prominent reading on which their probability is in fact the conditional probability, and that the two readings are related by a simple step of abductive inference. Central to the proposal is a distinction between (...)
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  • Conditionals Right and Left: Probabilities for the Whole Family.Stefan Kaufmann - 2009 - Journal of Philosophical Logic 38 (1):1-53.
    The fact that the standard probabilistic calculus does not define probabilities for sentences with embedded conditionals is a fundamental problem for the probabilistic theory of conditionals. Several authors have explored ways to assign probabilities to such sentences, but those proposals have come under criticism for making counterintuitive predictions. This paper examines the source of the problematic predictions and proposes an amendment which corrects them in a principled way. The account brings intuitions about counterfactual conditionals to bear on the interpretation of (...)
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  • How people interpret conditionals: Shifts towards the conditional event.A. J. B. Fugard, Niki Pfeifer, B. Mayerhofer & Gernot D. Kleiter - 2011 - Journal of Experimental Psychology 37 (3):635-648.
    We investigated how people interpret conditionals and how stable their interpretation is over a long series of trials. Participants were shown the colored patterns on each side of a six-sided die, and were asked how sure they were that a conditional holds of the side landing upwards when the die is randomly thrown. Participants were presented with 71 trials consisting of all combinations of binary dimensions of shape (e.g., circles and squares) and color (e.g., blue and red) painted onto the (...)
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  • New normative standards of conditional reasoning and the dual-source model.Henrik Singmann, Karl Christoph Klauer & David Over - 2014 - Frontiers in Psychology 5.
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  • Fuzzy Sets.Lofti A. Zadeh - 1965 - Information and Control 8 (1):338--53.
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  • The Psychology of Uncertainty and Three-Valued Truth Tables.Jean Baratgin, Guy Politzer, David E. Over & Tatsuji Takahashi - 2018 - Frontiers in Psychology 9:394374.
    Psychological research on people’s understanding of natural language connectives has traditionally used truth table tasks, in which participants evaluate the truth or falsity of a compound sentence given the truth or falsity of its components in the framework of propositional logic. One perplexing result concerned the indicative conditional if A then C which was often evaluated as true when A and C are true, false when A is true and C is false but irrelevant“ (devoid of value) when A is (...)
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  • The conditional in mental probability logic.Niki Pfeifer & G. D. Kleiter - 2010 - In Mike Oaksford & Nick Chater (eds.), Cognition and Conditionals: Probability and Logic in Human Thought. Oxford University Press. pp. 153--173.
    The present chapter describes a probabilistic framework of human reasoning. It is based on probability logic. While there are several approaches to probability logic, we adopt the coherence based approach.
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