The Stable Model Semantics Of Normal Fuzzy Linguistic Logic Programs

Fuzzy linguistic logic programming is a framework for representing and reasoning with linguistically-expressed human knowledge. It is well known that allowing the representation and the manipulation of negation is an important feature for many real-world applications. In this work, we extend the framework by allowing negation connectives to occur in rule bodies, resulting in normal fuzzy linguistic logic programs, and study the stable model semantics of such logic programs.