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Contemporary syllogistics: Comparative and quantitative syllogisms

In Günther Kreuzbauer & Georg Dorn (eds.), Argumentation in Theorie Und Praxis: Philosophie Und Didaktik des Argumentierens. Lit. pp. 57--71 (2006)

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  1. A System of Relational Syllogistic Incorporating Full Boolean Reasoning.Nikolay Ivanov & Dimiter Vakarelov - 2012 - Journal of Logic, Language and Information 21 (4):433-459.
    We present a system of relational syllogistic, based on classical propositional logic, having primitives of the following form: $$\begin{array}{ll}\mathbf{Some}\, a \,{\rm are} \,R-{\rm related}\, {\rm to}\, \mathbf{some} \,b;\\ \mathbf{Some}\, a \,{\rm are}\,R-{\rm related}\, {\rm to}\, \mathbf{all}\, b;\\ \mathbf{All}\, a\, {\rm are}\,R-{\rm related}\, {\rm to}\, \mathbf{some}\, b;\\ \mathbf{All}\, a\, {\rm are}\,R-{\rm related}\, {\rm to}\, \mathbf{all} \,b.\end{array}$$ Such primitives formalize sentences from natural language like ‘ All students read some textbooks’. Here a, b denote arbitrary sets (of objects), and R denotes an (...)
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  • Mental probability logic.Niki Pfeifer & Gernot D. Kleiter - 2009 - Behavioral and Brain Sciences 32 (1):98-99.
    We discuss O&C's probabilistic approach from a probability logical point of view. Specifically, we comment on subjective probability, the indispensability of logic, the Ramsey test, the consequence relation, human nonmonotonic reasoning, intervals, generalized quantifiers, and rational analysis.
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  • Square of opposition under coherence.Niki Pfeifer & Giuseppe Sanfilippo - 2017 - 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.
    Various semantics for studying the square of opposition have been proposed recently. So far, only [14] studied a probabilistic version of the square where the sentences were interpreted by (negated) defaults. We extend this work by interpreting sentences by imprecise (set-valued) probability assessments on a sequence of conditional events. We introduce the acceptability of a sentence within coherence-based probability theory. We analyze the relations of the square in terms of acceptability and show how to construct probabilistic versions of the square (...)
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  • Probabilistic semantics for categorical syllogisms of Figure II.Niki Pfeifer & Giuseppe Sanfilippo - 2018 - In D. Ciucci, G. Pasi & B. Vantaggi (eds.), Scalable Uncertainty Management. pp. 196-211.
    A coherence-based probability semantics for categorical syllogisms of Figure I, which have transitive structures, has been proposed recently (Gilio, Pfeifer, & Sanfilippo [15]). We extend this work by studying Figure II under coherence. Camestres is an example of a Figure II syllogism: from Every P is M and No S is M infer No S is P. We interpret these sentences by suitable conditional probability assessments. Since the probabilistic inference of ~????|???? from the premise set {????|????, ~????|????} is not informative, (...)
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  • Probability Semantics for Aristotelian Syllogisms.Niki Pfeifer & Giuseppe Sanfilippo - manuscript
    We present a coherence-based probability semantics for (categorical) Aristotelian syllogisms. For framing the Aristotelian syllogisms as probabilistic inferences, we interpret basic syllogistic sentence types A, E, I, O by suitable precise and imprecise conditional probability assessments. Then, we define validity of probabilistic inferences and probabilistic notions of the existential import which is required, for the validity of the syllogisms. Based on a generalization of de Finetti's fundamental theorem to conditional probability, we investigate the coherent probability propagation rules of argument forms (...)
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  • AWide-Reflective-Equilibrium Conception of Reconstructive Formalization.Winfried Löffler - 2014 - History of Philosophy & Logical Analysis 17 (1):130-151.
    I propose that a logical formalization of a natural language text may be regarded as adequate if the following three groups of beliefs can be integrated into a wide reflective equilibrium: our initial, spontaneous beliefs about the structure and logical quality of the text; our beliefs about its structure and logical quality as reflected in the proposed formalization, and our background beliefs about the original text’s author, his thought and other contextually relevant factors. Unlike a good part of the literature, (...)
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  • Probability propagation rules for Aristotelian syllogisms.Niki Pfeifer & Giuseppe Sanfilippo - 2024 - Annals of Pure and Applied Logic 175 (9):103340.
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  • Conditionals, Counterfactuals, and Rational Reasoning: An Experimental Study on Basic Principles.Leena Tulkki & Niki Pfeifer - 2017 - Minds and Machines 27 (1):119-165.
    We present a unified approach for investigating rational reasoning about basic argument forms involving indicative conditionals, counterfactuals, and basic quantified statements within coherence-based probability logic. After introducing the rationality framework, we present an interactive view on the relation between normative and empirical work. Then, we report a new experiment which shows that people interpret indicative conditionals and counterfactuals by coherent conditional probability assertions and negate conditionals by negating their consequents. The data support the conditional probability interpretation of conditionals and the (...)
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  • Transitivity in coherence-based probability logic.Angelo Gilio, Niki Pfeifer & Giuseppe Sanfilippo - 2016 - Journal of Applied Logic 14:46-64.
    We study probabilistically informative (weak) versions of transitivity by using suitable definitions of defaults and negated defaults in the setting of coherence and imprecise probabilities. We represent p-consistent sequences of defaults and/or negated defaults by g-coherent imprecise probability assessments on the respective sequences of conditional events. Moreover, we prove the coherent probability propagation rules for Weak Transitivity and the validity of selected inference patterns by proving p-entailment of the associated knowledge bases. Finally, we apply our results to study selected probabilistic (...)
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