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A LOGIC OF ARGUMENTATION FOR REASONING UNDER UNCERTAINTY
Author(s) -
Krause Paul,
Ambler Simon,
ElvangGoransson Morten,
Fox John
Publication year - 1995
Publication title -
computational intelligence
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.353
H-Index - 52
eISSN - 1467-8640
pISSN - 0824-7935
DOI - 10.1111/j.1467-8640.1995.tb00025.x
Subject(s) - argumentation theory , semantics (computer science) , representation (politics) , artificial intelligence , computer science , mathematics , non monotonic logic , syntax , theoretical computer science , natural language processing , epistemology , programming language , philosophy , politics , political science , law
We present the syntax and proof theory of a logic of argumentation, LA. We also outline the development of a category theoretic semantics for LA. LA is the core of a proof theoretic model for reasoning under uncertainty. In this logic, propositions are labeled with a representation of the arguments which support their validity. Arguments may then be aggregated to collect more information about the potential validity of the propositions of interest. We make the notion of aggregation primitive to the logic, and then define strength mappings from sets of arguments to one of a number of possible dictionaries. This provides a uniform framework which incorporates a number of numerical and symbolic techniques for assigning subjective confidences to propositions on the basis of their supporting arguments. These aggregation techniques are also described with examples.