Logic for computer science: foundations of automatic theorem proving
Logic for computer science: foundations of automatic theorem proving
Logical foundations of artificial intelligence
Logical foundations of artificial intelligence
Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
New Generation Computing - Selected papers from the international workshop on algorithmic learning theory,1990
Symbolic Logic and Mechanical Theorem Proving
Symbolic Logic and Mechanical Theorem Proving
Inductive Logic Programming: Derivations, Successes and Shortcomings
ECML '93 Proceedings of the European Conference on Machine Learning
Generalization of clauses under implication
Journal of Artificial Intelligence Research
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Plotkin‘s notions of relative &thetas;-subsumptionand relative least general generalization of clauses are defined for full clauses, and they are defined in terms of a kind of resolution derivations called C-derivations. Techniques for generalization of clauses relative to a theory, based on the V-operators or saturation in its original form, have primarily been developed for Horn clauses. We show that these techniques are incomplete for full clauses, which is due to the restricted form of resolution derivations considered. We describe a technique for generalization of clauses relative to a theory, which is based on a generalization of the original saturation technique. We prove that our technique properly inverts C-derivations, and that it is complete for full clauses w.r.t. relative &thetas;-subsumption.