Introduction to Default Logic
Skeptical Query-Answering in Constrained Default Logic
FAPR '96 Proceedings of the International Conference on Formal and Applied Practical Reasoning
Adding Priorities and Specificity to Default Logic
JELIA '94 Proceedings of the European Workshop on Logics in Artificial Intelligence
A Query Answering Algorithm for Lukaszewicz' General Open Default Theory
JELIA '96 Proceedings of the European Workshop on Logics in Artificial Intelligence
A Theorem Prover for Lukaszewicz` Open Default Theory
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
XRay: A Prolog Technology Theorem Prover for Default Reasoning: A System Description
CADE-13 Proceedings of the 13th International Conference on Automated Deduction: Automated Deduction
Learning Non-Monotonic Logic Programs: Learning Exceptions
ECML '95 Proceedings of the 8th European Conference on Machine Learning
Integrating explanatory and descriptive learning in ILP
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 1
Learning extended logic programs
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
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This paper proposes a method to learn from a set of examples a theory expressed in default logic, more precisely in Lukaszewicz'default logic. The main characteristic of our method is to deal with theories where the definitions of a predicate p and definitions for its negation ¬p are explicitly and simultaneously learned. This method relies on classical generalization techniques proposed in the field of Inductive Logic Programming and on the notion of credulous/skeptical theorem in Default Logic.