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A Fuzzy Syllogistic Reasoning Schema for Generalized Quantifiers

Artificial Intelligence 2014-11-27 v1

Abstract

In this paper, a new approximate syllogistic reasoning schema is described that expands some of the approaches expounded in the literature into two ways: (i) a number of different types of quantifiers (logical, absolute, proportional, comparative and exception) taken from Theory of Generalized Quantifiers and similarity quantifiers, taken from statistics, are considered and (ii) any number of premises can be taken into account within the reasoning process. Furthermore, a systematic reasoning procedure to solve the syllogism is also proposed, interpreting it as an equivalent mathematical optimization problem, where the premises constitute the constraints of the searching space for the quantifier in the conclusion.

Keywords

Cite

@article{arxiv.1411.7149,
  title  = {A Fuzzy Syllogistic Reasoning Schema for Generalized Quantifiers},
  author = {M. Pereira-Fariña and Juan C. Vidal and F. Díaz-Hermida and A. Bugarín},
  journal= {arXiv preprint arXiv:1411.7149},
  year   = {2014}
}

Comments

22 pages, 6 figures, journal paper

R2 v1 2026-06-22T07:12:48.359Z