Tabling for non‐monotonic programming
 Terrance Swift
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Non‐monotonic extensions add power to logic programs. However, the main logic programming language, Prolog, is widely recognized as inadequate to implement these extensions due to its weak termination and complexity properties. By extending Prolog’s SLD resolution with tabling, Prolog can be improved in several ways. Tabling can allow a logic programming system to compute the well‐founded semantics for programs with bounded term depth, and to do so with polynomial data complexity. By exploiting these properties, tabling allows a variety of non‐monotonic extensions to be efficiently implemented, and used to solve practical problems. In this paper we describe tabling as it is implemented in the XSB system and show how it can be used to construct meta‐interpreters (or preprocessors) for two sample formalisms: the Well‐Founded Semantics with Explicit Negation, and Generalized Annotated Logic Programs. We also describe how non‐monotonic extensions are used in practical applications such as psychiatric diagnosis, extraction of information from poorly structured textual data, and model checking.
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 Title
 Tabling for non‐monotonic programming
 Journal

Annals of Mathematics and Artificial Intelligence
Volume 25, Issue 34 , pp 201240
 Cover Date
 19991101
 DOI
 10.1023/A:1018990308362
 Print ISSN
 10122443
 Online ISSN
 15737470
 Publisher
 Kluwer Academic Publishers
 Additional Links
 Topics
 Industry Sectors
 Authors

 Terrance Swift ^{(1)}
 Author Affiliations

 1. Department of Computer Science, SUNY at Stony Brook, Stony Brook, NY, 11794‐4400, USA