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Communication Dans Un Congrès Année : 2013

The Logic of Typical and Atypical Instances (LTA)

Jean-Pierre Desclés
  • Fonction : Auteur
Anca Pascu
  • Fonction : Auteur

Résumé

The difference between typical instances and atypical instances in a natural categorization process has been introduced by E. Rosh and studied by cognitive psychology and AI. A lot of the knowledge representation systems are expressed in using fuzzy concepts but a degree of membership raises some problem for natural categorizations (especially to classification problems in anthropology, ethnology, archeology, linguistics but also in ontologies), but atypical instances of a concept cannot be apprehended adequately by different degrees from a prototype. Other formal approaches, as paraconsistent logics or non monotonic logics, conceptualize often atypical objects as exceptions. It had yet been developed an alternative way with the logics of determination of the objects (LDO). In this paper, we present the logics of typical and atypical (LTA) in order to give directly a logical approach of typicality / atypicality associated to a concept by a more common way than in LDO, in using only classes and not determination operators. It is introduced a distinction between predicative property and concept defined with its intension and its essence, a part of intension. A typical instance of a concept inherits all properties of intension; a typical instance inherits only properties of essence but it is a full member of the category associated to a concept and not a member with a weak degree of membership. In natural categorization, there are often instances (the exceptions) which do not inherit some properties of the essence; they cannot be considered as atypical instance and belong to the boundary of the category.
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Dates et versions

hal-01216530 , version 1 (16-10-2015)

Identifiants

  • HAL Id : hal-01216530 , version 1

Citer

Jean-Pierre Desclés, Anca Pascu, Christophe Jouis. The Logic of Typical and Atypical Instances (LTA). The Twenty-Sixth International Florida Artificial Intelligence Research Society Conference, FLAIRS13, May 2013, Miami, United States. pp.321-326. ⟨hal-01216530⟩
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