Teresa Alsinet

Learn More
In the last decade defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning. The logic programming paradigm has shown to be particularly useful for developing different argument-based frameworks on the basis of different variants of logic programming which incorporate defeasible rules. Most(More)
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(More)
In this paper we present a propositional logic programming language for reasoning under possibilistic uncertainty and represent­ ing vague knowledge. Formulas are repre­ sented by pairs (ip, a), where ip is a many­ valued proposition and a E [0, 1] is a lower bound on the belief on ip in terms of necessity measures. Belief states are modeled by pos­(More)
We present a new branch and bound algorithm for weighted Max-SAT, called 1 Lazy which incorporates original data structures and inference rules, as well as a lower 2 bound of better quality. We provide experimental evidence that our solver is very competi3 tive and outperforms some of the best performing Max-SAT and weighted Max-SAT solvers 4 on a wide(More)
Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at the object-language level. In spite of its expressive power, an important limitation in P-DeLP is that imprecise, fuzzy information cannot be(More)
inconsistent Recently a syntactical extension of rst order Possibilistic logic called PLFC dealing with fuzzy constants and fuzzily re stricted quanti ers has been proposed In this paper we present steps towards both the formalization of PLFC itself and an auto mated deduction system for it by i provid ing a formal semantics ii de ning a sound resolution(More)
PLFC is a 0rst-order possibilistic logic dealing with fuzzy constants and fuzzily restricted quanti0ers. The refutation proof method in PLFC is mainly based on a generalized resolution rule which allows an implicit graded uni0cation among fuzzy constants. However, uni0cation for precise object constants is classical. In order to use PLFC for(More)