Principles of artificial intelligence
Principles of artificial intelligence
A Prolog technology theorem prover: implementation by an extended Prolog computer
Journal of Automated Reasoning
Non-horn clause logic programming without contrapositives
Journal of Automated Reasoning
A Prolog technology theorem prover: a new exposition and implementation in Prolog
Theoretical Computer Science - Selected papers on theoretical issues of design and implementation of symbolic computation systems
Simplification by Cooperating Decision Procedures
ACM Transactions on Programming Languages and Systems (TOPLAS)
Symbolic Logic and Mechanical Theorem Proving
Symbolic Logic and Mechanical Theorem Proving
First-Order Automation for Higher-Order-Logic Theorem Proving
Proceedings of the 7th International Workshop on Higher Order Logic Theorem Proving and Its Applications
Combining Decision Procedures in the HOL System
Proceedings of the 8th International Workshop on Higher Order Logic Theorem Proving and Its Applications
Deciding Combinations of Theories
Proceedings of the 6th Conference on Automated Deduction
CAAP '83 Proceedings of the 8th Colloquium on Trees in Algebra and Programming
Model Elimination Without Contrapositives
CADE-12 Proceedings of the 12th International Conference on Automated Deduction
CADE-14 Proceedings of the 14th International Conference on Automated Deduction
Integration of Automated and Interactive Theorem Proving in ILP
CADE-14 Proceedings of the 14th International Conference on Automated Deduction
A Practical Integration of First-Order Reasoning and Decision Procedures
CADE-14 Proceedings of the 14th International Conference on Automated Deduction
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We present a method for automated theorem proving in a combination of theories with disjoint signatures. The Nelson-Oppen combination technique for decision procedures is used to combine separate theorem provers in different theories. The provers being combined are based on the Prolog Technology Theorem Proving method and they use the SLD resolution (alternatively Model Elimination) as an inference system. Our approach enables to tune up the provers for different theories separately and increases the efficiency of automated theorem proving in a combination of theories.