Automated theorem-proving in non-classical logics
Automated theorem-proving in non-classical logics
Automatic Theorem Proving With Renamable and Semantic Resolution
Journal of the ACM (JACM)
Symbolic Logic and Mechanical Theorem Proving
Symbolic Logic and Mechanical Theorem Proving
Towards Semantic Goal-Directed Forward Reasoning in Resolution
AIMSA '02 Proceedings of the 10th International Conference on Artificial Intelligence: Methodology, Systems, and Applications
PTTP+GLiDeS: Guiding Linear Deductions with Semantics
AI '99 Proceedings of the 12th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
An Application of Model Building in a Resolution Decision Procedure for Guarded Formulas
CL '00 Proceedings of the First International Conference on Computational Logic
Emphasizing Human Techniques in Automated Geometry Theorem Proving: A Practical Realization
ADG '00 Revised Papers from the Third International Workshop on Automated Deduction in Geometry
A Logic for Approximate First-Order Reasoning
CSL '01 Proceedings of the 15th International Workshop on Computer Science Logic
IJCAR '01 Proceedings of the First International Joint Conference on Automated Reasoning
Geometric resolution: a proof procedure based on finite model search
IJCAR'06 Proceedings of the Third international joint conference on Automated Reasoning
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SCOTT (Semantically Constrained Otter) is a resolution-based automatic theorem prover for first order logic. It is based on the high performance prover OTTER by W. McCune and also incorporates a model generator. This finds finite models which SCOTT is able to use in a variety of ways to direct its proof search. Clauses generated by the prover are in turn used as axioms of theories to be modelled. Thus prover and model generator inform each other dynamically. This paper describes the algorithm and some sample results.