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SLT-Resolution for the Well-Founded Semantics | | Yi-Dong Shen
; Li-Yan Yuan
; Jia-Huai You
; | | Date: |
27 Feb 2000 | | Journal: | Journal of Automated Reasoning 28(1):53-97, 2002 | | Subject: | Artificial Intelligence; Programming Languages ACM-class: D.3.1; F.4.1; I.2.3 | cs.AI cs.PL | | Abstract: | Global SLS-resolution and SLG-resolution are two representative mechanisms for top-down evaluation of the well-founded semantics of general logic programs. Global SLS-resolution is linear for query evaluation but suffers from infinite loops and redundant computations. In contrast, SLG-resolution resolves infinite loops and redundant computations by means of tabling, but it is not linear. The principal disadvantage of a non-linear approach is that it cannot be implemented using a simple, efficient stack-based memory structure nor can it be easily extended to handle some strictly sequential operators such as cuts in Prolog. In this paper, we present a linear tabling method, called SLT-resolution, for top-down evaluation of the well-founded semantics. SLT-resolution is a substantial extension of SLDNF-resolution with tabling. Its main features include: (1) It resolves infinite loops and redundant computations while preserving the linearity. (2) It is terminating, and sound and complete w.r.t. the well-founded semantics for programs with the bounded-term-size property with non-floundering queries. Its time complexity is comparable with SLG-resolution and polynomial for function-free logic programs. (3) Because of its linearity for query evaluation, SLT-resolution bridges the gap between the well-founded semantics and standard Prolog implementation techniques. It can be implemented by an extension to any existing Prolog abstract machines such as WAM or ATOAM. | | Source: | arXiv, cs.AI/0002016 | | Services: | Forum | Review | PDF | Favorites | |
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