Abstract

Is rigor always strictly related to precision and accuracy? This is a fundamentalquestion in the realm of Fuzzy Logic; the first instinct would be to answerin the positive, but the question is much more complex than it appears, as true rigoris obtained also by a careful examination of the context, and limiting to a mechanicaltransfer of techniques, procedures and conceptual attitudes from one domain toanother, such as from the pure engineering feats or the ones of mathematical logicto the study of human reasoning, does not guarantee optimal results. Starting fromthis question, we discuss some implications of going back to the very concept of reasoningas it is used in natural language and in everyday life. Taking into account thepresence—from the start—of uncertainty and approximation in one of its possibleforms seems to indicate the need of a different approach from the simple extensionof tools and concepts from mathematical logic.
Lingua originaleEnglish
Titolo della pubblicazione ospiteSoft Methods for Data Science
Pagine471-478
Numero di pagine8
Stato di pubblicazionePublished - 2017

Serie di pubblicazioni

NomeADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

Cita questo

Termini, S., & Tabacchi, M. (2017). Back to “Reasoning”. In Soft Methods for Data Science (pagg. 471-478). (ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING).