Explanation and prediction: an architecture for default and abductive reasoning
Computational Intelligence
Abductive inference models for diagnostic problem-solving
Abductive inference models for diagnostic problem-solving
Abduction versus closure in causal theories
Artificial Intelligence
Preferred answer sets for extended logic programs
Artificial Intelligence
A survey of paraconsistent semantics for logic programs
Handbook of defeasible reasoning and uncertainty management systems
Prioritized logic programming and its application to commonsense reasoning
Artificial Intelligence
Answer set programming and plan generation
Artificial Intelligence
Extending and implementing the stable model semantics
Artificial Intelligence
Knowledge Representation, Reasoning, and Declarative Problem Solving
Knowledge Representation, Reasoning, and Declarative Problem Solving
Logic programs with stable model semantics as a constraint programming paradigm
Annals of Mathematics and Artificial Intelligence
Smodels - An Implementation of the Stable Model and Well-Founded Semantics for Normal LP
LPNMR '97 Proceedings of the 4th International Conference on Logic Programming and Nonmonotonic Reasoning
Logic programming with ordered disjunction
Eighteenth national conference on Artificial intelligence
The Diagnosis Frontend of the dlv system
AI Communications
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
LPOD answer sets and nash equilibria
ASIAN'04 Proceedings of the 9th Asian Computing Science conference on Advances in Computer Science: dedicated to Jean-Louis Lassez on the Occasion of His 5th Cycle Birthday
The consistency extractor system: Answer set programs for consistent query answering in databases
Data & Knowledge Engineering
Preference-based query answering in datalog+/- ontologies
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Preferences play a major role in many AI applications. We give a brief overview of methods for adding qualitative preferences to answer set programming, a promising declarative programming paradigm. We show how these methods can be used in a variety of different applications such as configuration, abduction, diagnosis, inconsistency handling and game theory.