TitleOn Warranted Inference in Possibilistic Defeasible Logic Programming
Publication TypeBook Chapter
Year of Publication2005
AuthorsChesñevar C., Simari G., Godo L, Alsinet T
EditorLópez B., Meléndez J., Radeva P., Vitrià J.
Book TitleArtificial Intelligence Reseach and Development. Frontiers in Artificial Intelligence and Applications.
Pagination265 - 272
PublisherIOS Press

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 two non-monotonic operators for P-DeLP which model the expansion of a given program program by adding new weighed facts associated with argument conclusions and warranted literals, resp. Different logical properties for the proposed expansion operators are studied and contrasted with a traditional SLD-based Horn logic. We will show that this analysis provides useful comparison criteria that can be extended and applied to other argumentation frameworks.