Proceedings of the eleventh international conference on Logic programming
Solving the frame problem: a mathematical investigation of the common sense law of inertia
Solving the frame problem: a mathematical investigation of the common sense law of inertia
Extending and implementing the stable model semantics
Artificial Intelligence
Logic programs with stable model semantics as a constraint programming paradigm
Annals of Mathematics and Artificial Intelligence
ASSAT: computing answer sets of a logic program by SAT solvers
Artificial Intelligence - Special issue on nonmonotonic reasoning
A generalization of the Lin-Zhao theorem
Annals of Mathematics and Artificial Intelligence
Achieving compositionality of the stable model semantics for smodels programs1
Theory and Practice of Logic Programming
A reductive semantics for counting and choice in answer set programming
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
What is answer set programming?
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
A new perspective on stable models
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Modularity aspects of disjunctive stable models
LPNMR'07 Proceedings of the 9th international conference on Logic programming and nonmonotonic reasoning
Stable models and circumscription
Artificial Intelligence
Relevance-Driven Evaluation of Modular Nonmonotonic Logic Programs
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
System f2lp --- Computing Answer Sets of First-Order Formulas
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
Translating first-order causal theories into answer set programming
JELIA'10 Proceedings of the 12th European conference on Logics in artificial intelligence
Stable models and circumscription
Artificial Intelligence
Translating first-order theories into logic programs
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Fundamenta Informaticae - Logic, Language, Information and Computation
Journal of Artificial Intelligence Research
Module theorem for the general theory of stable models
Theory and Practice of Logic Programming
Relating constraint answer set programming languages and algorithms
Artificial Intelligence
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Splitting a logic program allows us to reduce the task of computing its stable models to similar tasks for smaller programs. This idea is extended here to the general theory of stable models that replaces traditional logic programs by arbitrary first-order sentences and distinguishes between intensional and extensional predicates. We discuss two kinds of splitting: a set of intensional predicates can be split into subsets, and a formula can be split into its conjunctive terms.