Towards a theory of declarative knowledge
Foundations of deductive databases and logic programming
On the declarative semantics of deductive databases and logic programs
Foundations of deductive databases and logic programming
A Machine-Oriented Logic Based on the Resolution Principle
Journal of the ACM (JACM)
Minimal Model Generation with Positive Unit Hyper-Resolution Tableaux
TABLEAUX '96 Proceedings of the 5th International Workshop on Theorem Proving with Analytic Tableaux and Related Methods
A Tableau Calculus for Minimal Model Reasoning
TABLEAUX '96 Proceedings of the 5th International Workshop on Theorem Proving with Analytic Tableaux and Related Methods
Tableaux for Diagnosis Applications
TABLEAUX '97 Proceedings of the International Conference on Automated Reasoning with Analytic Tableaux and Related Methods
SATCHMO: A Theorem Prover Implemented in Prolog
Proceedings of the 9th International Conference on Automated Deduction
Non-Horn Magic Sets to Incorporate Top-down Inference into Bottom-up Theorem Proving
CADE-14 Proceedings of the 14th International Conference on Automated Deduction
On the Relationship Between Non-Horn Magic Sets and Relevancy Testing
CADE-15 Proceedings of the 15th International Conference on Automated Deduction: Automated Deduction
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This paper presents a way to improve minimal model generation for clausal theories. It works by breaking up the model generation process into several steps according to several parts of the given theory. It is shown that elimination of non-minimal or duplicate models can be performed after each step, which reduces the overall search space. An even stronger reduction of the search space is possible if we are interested only in certain parts of the models to be generated. The techniques are applicable to any method for the generation of minimal Herbrand models. The paper goes into some detail how they can be integrated tightly into the PUHR tableau method.