A Logic Programming Framework for Possibilistic Argumentation with Vague Knowledge
This work addresses the problem of reasoning with incomplete and inconsistent knowledge in AI and logic programming, but it is incremental as it builds upon existing DeLP frameworks.
The authors tackled the limitation of Defeasible Logic Programming (DeLP) in handling explicit uncertainty and vague knowledge by introducing P-DeLP, a new logic programming language that extends DeLP with possibilistic uncertainty and fuzzy knowledge based on PGL, resulting in enhanced qualitative reasoning capabilities.
Defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning from incomplete and potentially inconsistent knowledge. Defeasible Logic Programming (DeLP) is a defeasible argumentation formalism based on an extension of logic programming. Although DeLP has been successfully integrated in a number of different real-world applications, DeLP cannot deal with explicit uncertainty, nor with vague knowledge, as defeasibility is directly encoded in the object language. This paper introduces P-DeLP, a new logic programming language that extends original DeLP capabilities for qualitative reasoning by incorporating the treatment of possibilistic uncertainty and fuzzy knowledge. Such features will be formalized on the basis of PGL, a possibilistic logic based on Godel fuzzy logic.