Add to ORKGDefault Logic and Logic Programming with stable model se-mantics are recognized as powerful frameworks for incom-plete information representation. Their expressive power are suitable for non monotonic reasoning, but the counterpart is their very high level of theoretical complexity. The purpose of this paper is to show how heuristics issued from combina-torial optimization and operation research can be used to built non monotonic reasonning systems
In this paper we present and compare some classical problem solving methods for computing the stable...
We present a definition of stable generated models for extended generalized logic programs (EGLP) wh...
Over the past few decades, non-monotonic reasoning has developed to be one of the most important top...
Default Logic and Logic Programming with stable model semantics are recognized as powerful framework...
Default Logic is recognized as a powerful framework for knowledge representation and incomplete info...
In Artificial Intelligence, Default Logic is recognized as a powerful framework for knowledge repres...
Introduction Nonmonotonic logics were introduced in the late 70s as knowledge representation formal...
In Artificial Intelligence, Default Logic is recognized as a powerful framework for knowledge repres...
In the last years computational logic, and particularly non-monotonic reasoning, was introduced as a...
We define a model-theoretic reasoning formal-ism that is naturally implemented on sym-metric neural ...
AbstractDefault logic was proposed by Reiter as a knowledge representation tool. In this paper, we p...
W.C. Rounds and G.-Q. Zhang have recently proposed to study a form of disjunctive logic programming ...
We present the proof theory and the model theory of a monotonic framework for default reasoning, and...
Our purpose is to exhibit a modular systematic method of representing nonmonotonic reasoning problem...
In this paper we present and compare some classical problem solving methods for computing the stable...
In this paper we present and compare some classical problem solving methods for computing the stable...
We present a definition of stable generated models for extended generalized logic programs (EGLP) wh...
Over the past few decades, non-monotonic reasoning has developed to be one of the most important top...
Default Logic and Logic Programming with stable model semantics are recognized as powerful framework...
Default Logic is recognized as a powerful framework for knowledge representation and incomplete info...
In Artificial Intelligence, Default Logic is recognized as a powerful framework for knowledge repres...
Introduction Nonmonotonic logics were introduced in the late 70s as knowledge representation formal...
In Artificial Intelligence, Default Logic is recognized as a powerful framework for knowledge repres...
In the last years computational logic, and particularly non-monotonic reasoning, was introduced as a...
We define a model-theoretic reasoning formal-ism that is naturally implemented on sym-metric neural ...
AbstractDefault logic was proposed by Reiter as a knowledge representation tool. In this paper, we p...
W.C. Rounds and G.-Q. Zhang have recently proposed to study a form of disjunctive logic programming ...
We present the proof theory and the model theory of a monotonic framework for default reasoning, and...
Our purpose is to exhibit a modular systematic method of representing nonmonotonic reasoning problem...
In this paper we present and compare some classical problem solving methods for computing the stable...
In this paper we present and compare some classical problem solving methods for computing the stable...
We present a definition of stable generated models for extended generalized logic programs (EGLP) wh...
Over the past few decades, non-monotonic reasoning has developed to be one of the most important top...