Probability Propagation in Selected Aristotelian Syllogisms

Giuseppe Sanfilippo, Niki Pfeifer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


This paper continues our work on a coherence-based probability semantics for Aristotelian syllogisms (Gilio, Pfeifer, and Sanfilippo, 2016; Pfeifer and Sanfilippo, 2018) by studying Figure III under coherence. We interpret the syllogistic sentence types by suitable conditional probability assessments. Since the probabilistic inference of $P|S$ from the premise set ${P|M, S|M}$ is not informative, we add $p(M|(S ee M))>0$ as a probabilistic constraint (i.e., an ``existential import assumption'') to obtain probabilistic informativeness. We show how to propagate the assigned premise probabilities to the conclusion. Thereby, we give a probabilistic meaning to all syllogisms of Figure~III. We discuss applications like generalised quantifiers (like Most $S$ are $P$) and (negated) defaults
Original languageEnglish
Title of host publicationSymbolic and Quantitative Approaches to Reasoning with Uncertainty 15th European Conference, ECSQARU 2019 Belgrade, Serbia, September 18–20, 2019 Proceedings
Number of pages13
Publication statusPublished - 2019

Publication series


All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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