Expansion Operators for Modelling Agent Reasoning in Possibilistic Defeasible Logic Programming
نویسندگان
چکیده
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. When modelling intelligent agents, 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 specialized non-monotonic operators for P-DeLP which model the expansion of a given program P by adding new weighed facts associated with argument conclusions and warranted literals. Different logical properties are studied and analyzed, providing useful comparison criteria that can be extended and applied to other argumentation frameworks.
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