On Warranted Inference in Possibilistic Defeasible Logic Programming

Authors:
Carlos Chesòevar;Guillermo Simari;Lluís Godo;Teresa Alsinet
Affiliations:
Department of Computer Science. University of Lleida, SPAIN;Dept. of Computer Science & Eng. Universidad Nacional del Sur, ARGENTINA;Artificial Intelligence Research Institute (IIIA-CSIC), Bellaterra, SPAIN;Department of Computer Science. University of Lleida, SPAIN
Venue:
Proceedings of the 2005 conference on Artificial Intelligence Research and Development
Year:
2005

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Abstract

Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating as well the treatment of possibilistic uncertainty and fuzzy knowledge at object-language level. Defeasible argumentation in general and P-DeLP in particular provide a way of modelling non-monotonic inference. From a logical viewpoint, capturing defeasible inference relationships for modelling argument and warrant is particularly important, as well as the study of their logical properties. This paper analyzes a non-monotonic operator for P-DeLP which models the expansion of a given program P by adding new weighed facts associated with warranted literals. Different logical properties are studied and contrasted with a traditional SLD-based Horn logic, providing useful comparison criteria that can be extended and applied to other argumentation frameworks.