Enhancing Global SLS-Resolution with Loop Cutting and Tabling Mechanisms

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dc.creatorShen, Yi-Dong
dc.creatorYou, Jia-Huai
dc.creatorYuan, Li-Yan
dc.date2005-07-14
dc.date.accessioned2026-07-07T03:23:13Z
dc.date.available2026-07-07T03:23:13Z
dc.descriptionGlobal SLS-resolution is a well-known procedural semantics for top-down computation of queries under the well-founded model. It inherits from SLDNF-resolution the {\em linearity} property of derivations, which makes it easy and efficient to implement using a simple stack-based memory structure. However, like SLDNF-resolution it suffers from the problem of infinite loops and redundant computations. To resolve this problem, in this paper we develop a new procedural semantics, called {\em SLTNF-resolution}, by enhancing Global SLS-resolution with loop cutting and tabling mechanisms. SLTNF-resolution is sound and complete w.r.t. the well-founded semantics for logic programs with the bounded-term-size property, and is superior to existing linear tabling procedural semantics such as SLT-resolution.
dc.identifierhttps://arxiv.org/abs/cs/0507035
dc.identifierhttp://arxiv.org/abs/cs/0507035
dc.identifierTheoretical Computer Science 328(3):271-287, 2004
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/32858
dc.subjectLogic in Computer Science
dc.subjectArtificial Intelligence
dc.titleEnhancing Global SLS-Resolution with Loop Cutting and Tabling Mechanisms
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