Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Journal of Automated Reasoning
Logic for applications
Mechanical Theorem-Proving by Model Elimination
Journal of the ACM (JACM)
Symbolic Logic and Mechanical Theorem Proving
Symbolic Logic and Mechanical Theorem Proving
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
Ordered Semantic Hyper-Linking
Journal of Automated Reasoning
Positive Unit Hyperresolution Tableaux and Their Application to Minimal Model Generation
Journal of Automated Reasoning
Duality for Goal-Driven Query Processing in Disjunctive Deductive Databases
Journal of Automated Reasoning
SATCHMO: A Theorem Prover Implemented in Prolog
Proceedings of the 9th 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
FDPLL - A First Order Davis-Putnam-Longeman-Loveland Procedure
CADE-17 Proceedings of the 17th International Conference on Automated Deduction
DCTP - A Disconnection Calculus Theorem Prover - System Abstract
IJCAR '01 Proceedings of the First International Joint Conference on Automated Reasoning
SATCHMOREBID: SATCHMO(RE) with BIDirectional relevancy
New Generation Computing
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Theorem proving and semantic trees.
Theorem proving and semantic trees.
Automated theorem proving: A logical basis (Fundamental studies in computer science)
Automated theorem proving: A logical basis (Fundamental studies in computer science)
SATCHMOREBID: SATCHMO(RE) with BIDirectional relevancy
New Generation Computing
The 3rd IJCAR Automated Theorem Proving Competition
AI Communications
SRASS - A Semantic Relevance Axiom Selection System
CADE-21 Proceedings of the 21st international conference on Automated Deduction: Automated Deduction
MaLARea SG1 - Machine Learner for Automated Reasoning with Semantic Guidance
IJCAR '08 Proceedings of the 4th international joint conference on Automated Reasoning
Divvy: An ATP Meta-system Based on Axiom Relevance Ordering
CADE-22 Proceedings of the 22nd International Conference on Automated Deduction
Sine Qua non for large theory reasoning
CADE'11 Proceedings of the 23rd international conference on Automated deduction
Reasoning in the OWL 2 full ontology language using first-order automated theorem proving
CADE'11 Proceedings of the 23rd international conference on Automated deduction
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Identifying relevant clauses before attempting a proof may lead to more efficient automated theorem proving. Relevance is here defined relative to a given set of clauses S and one or more distinguished sets of support T. The role of a set of support T can be played by the negation of the theorem to be proved or the query to be answered in S which gives the refutation search goal orientation. The concept of relevance distance between two clauses C and D of S is defined using various metrics based on the properties of paths connecting C to D. This concept is extended to define relevance distance between a clause and a set (or multiple sets) of support. Informally, the relevance distance reflects how closely two clauses are related. The relevance distance to one or more support sets is used to compute a relevance set R, a subset of S that is unsatisfiable if and only if S is unsafisfiable. R is computed as the set of clauses of S at distance less than n from one or more support sets: if n is sufficiently large then R is unsatisfiable if S is. If R is much smaller than S, a refutation from R may be obtainable in much less time than a refutation from S. R must be efficiently computable to achieve an overall efficiency improvement. Different relevance metrics are defined, characterized and related. The tradeoffs between the amount of effort invested in computing a relevance set and the resulting gains in finding a refutation are addressed. Relevance sets may be utilized with arbitrary complete theorem proving strategies in a completeness-preserving manner. The potential of the advanced relevance techniques for various applications of theorem proving is discussed