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Logic Programming and Negation: A Survey
 JOURNAL OF LOGIC PROGRAMMING
, 1994
"... We survey here various approaches which were proposed to incorporate negation in logic programs. We concentrate on the prooftheoretic and modeltheoretic issues and the relationships between them. ..."
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Cited by 250 (8 self)
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We survey here various approaches which were proposed to incorporate negation in logic programs. We concentrate on the prooftheoretic and modeltheoretic issues and the relationships between them.
Logic Programming and Knowledge Representation
 Journal of Logic Programming
, 1994
"... In this paper, we review recent work aimed at the application of declarative logic programming to knowledge representation in artificial intelligence. We consider exten sions of the language of definite logic programs by classical (strong) negation, disjunc tion, and some modal operators and sh ..."
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Cited by 233 (21 self)
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In this paper, we review recent work aimed at the application of declarative logic programming to knowledge representation in artificial intelligence. We consider exten sions of the language of definite logic programs by classical (strong) negation, disjunc tion, and some modal operators and show how each of the added features extends the representational power of the language.
The Alternating Fixpoint of Logic Programs with Negation
, 1995
"... The alternating fixpoint of a logic program with negation is defined constructively. The underlying idea is monotonically to build up a set of negative conclusions until the least fixpoint is reached, using a transformation related to the one that defines stable models. From a fixed set of negative ..."
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Cited by 216 (2 self)
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The alternating fixpoint of a logic program with negation is defined constructively. The underlying idea is monotonically to build up a set of negative conclusions until the least fixpoint is reached, using a transformation related to the one that defines stable models. From a fixed set of negative conclusions, the positive conclusions follow (without deriving any further negative ones), by traditional Horn clause semantics. The union of positive and negative conclusions is called the alternating xpoint partial model. The name "alternating" was chosen because the transformation runs in two passes; the first pass transforms an underestimate of the set of negative conclusions into an (intermediate) overestimate; the second pass transforms the overestimate into a new underestimate; the composition of the two passes is monotonic. The principal contributions of this work are (1) that the alternating fixpoint partial model is identical to the wellfounded partial model, and (2) that alternating xpoint logic is at least as expressive as xpoint logic on all structures. Also, on finite structures, fixpoint logic is as expressive as alternating fixpoint logic.
Stable Semantics for Disjunctive Programs
 New Generation Computing
, 1991
"... We introduce the stable model semantics for disjunctive logic programs and deductive databases, which generalizes the stable model semantics, defined earlier for normal (i.e., nondisjunctive) programs. Depending on whether only total (2valued) or all partial (3valued) models are used we obtain th ..."
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Cited by 160 (2 self)
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We introduce the stable model semantics for disjunctive logic programs and deductive databases, which generalizes the stable model semantics, defined earlier for normal (i.e., nondisjunctive) programs. Depending on whether only total (2valued) or all partial (3valued) models are used we obtain the disjunctive stable semantics or the partial disjunctive stable semantics, respectively. The proposed semantics are shown to have the following properties: ffl For normal programs, the disjunctive (respectively, partial disjunctive) stable semantics coincides with the stable (respectively, partial stable) semantics. ffl For normal programs, the partial disjunctive stable semantics also coincides with the wellfounded semantics. ffl For locally stratified disjunctive programs both (total and partial) disjunctive stable semantics coincide with the perfect model semantics. ffl The partial disjunctive stable semantics can be generalized to the class of all disjunctive logic programs. ffl B...
WellFounded Semantics Coincides with ThreeValued Stable Semantics
 Fundamenta Informaticae
, 1990
"... We introduce 3valued stable models which are a natural generalization of standard (2valued) stable models. We show that every logic program P has at least one 3valued stable model and that the wellfounded model of any program P [VGRS90] coincides with the smallest 3valued stable model of P. We c ..."
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Cited by 139 (15 self)
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We introduce 3valued stable models which are a natural generalization of standard (2valued) stable models. We show that every logic program P has at least one 3valued stable model and that the wellfounded model of any program P [VGRS90] coincides with the smallest 3valued stable model of P. We conclude that the wellfounded semantics of an arbitrary logic program coincides with the 3valued stable model semantics. The 3valued stable semantics is closely related to nonmonotonic formalisms in AI. Namely, every program P can be translated into a suitable autoepistemic (resp. default) theory P so that the 3valued stable semantics of P coincides with the (3valued) autoepistemic (resp. default) semantics of P . Similar results hold for circumscription and CWA. Moreover, it can be shown that the 3valued stable semantics has a natural extension to the class of all disjunctive logic programs and deductive databases. The author acknowledges support from the National Science Foundat...
Stationary Semantics for Normal and Disjunctive Logic Programs
 Annals of Mathematics and Artificial Intelligence
, 1991
"... this paper we show, however, that stationary expansions can be equivalently defined in terms of classical, 2valued logic. As a byproduct, we obtain a simpler and more natural description of stationary expansions. ..."
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Cited by 73 (15 self)
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this paper we show, however, that stationary expansions can be equivalently defined in terms of classical, 2valued logic. As a byproduct, we obtain a simpler and more natural description of stationary expansions.
On Logic Program Semantics with Two Kinds of Negation
 Int. Joint Conf. and Symp. on LP
, 1992
"... Recently several authors have stressed and showed the importance of having a second kind of negation in logic programs for use in deductive databases, knowledge representation, and nonmonotonic reasoning [6, 7, 8, 9, 13, 14, 15, 24]. Different semantics for logic programs extended with :negation ( ..."
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Cited by 49 (16 self)
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Recently several authors have stressed and showed the importance of having a second kind of negation in logic programs for use in deductive databases, knowledge representation, and nonmonotonic reasoning [6, 7, 8, 9, 13, 14, 15, 24]. Different semantics for logic programs extended with :negation (extended logic programs) have appeared [1, 4, 6, 9, 11, 12, 17, 19, 24] but, contrary to what happens with semantics for normal logic programs, there is no general comparison among them, specially in what concerns the use and meaning of the newly introduced :negation. The goal of this paper is to contrast a variety of these semantics in what concerns their use and meaning of :negation, and its relation to classical negation and to the default negation of normal programs, here denoted by not : To this purpose we define a parametrizeable schema to encompass and characterize a diversity of proposed semantics for extended logic programs, where the parameters are two: one the axioms AX: defin...
Diagnosis and Debugging as Contradiction Removal
 PROCEEDINGS OF THE 2ND INTERNATIONAL WORKSHOP ON LOGIC PROGRAMMING AND NONMONOTONIC REASONING
, 1993
"... ..."
A NestedGraph Model for the Representation and Manipulation of Complex Objects
 ACM Transactions on Information Systems
, 1994
"... this paper we report upon a graphbased approach to such an integration. Our use of graphs has two key advantages : firstly, graphs are formally defined, wellunderstood structures; secondly, it is widely accepted that graphbased formalisms considerably enhance the usability of complex systems [19] ..."
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Cited by 37 (4 self)
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this paper we report upon a graphbased approach to such an integration. Our use of graphs has two key advantages : firstly, graphs are formally defined, wellunderstood structures; secondly, it is widely accepted that graphbased formalisms considerably enhance the usability of complex systems [19]. Graphs have been used in conjunction with a number of conventional data models, for example the hierarchical and network models [35], the entityrelationship model [9] and a recent extension thereof for complex objects [27], and various semantic data models [16, 20, 31]. Graphs or hypergraphs [6] have also been used more recently in [12, 17, 23, 25, 33, 36] as a data modelling tool in their own right. We give a comparison between this recent work and our own approach in Section 4 of the paper. Directed graphs have also been the foundation of Hypertext databases [11, 33]. Such databases are graphs consisting of nodes which refer to units of stored information (typically text) and of named links. Each link connects two nodes, the "source" and the "destination". Links are traversed either forwards (from source to destination) or backwards (from destination to source). The process of traversing named links and examining the text associated with nodes is called
Antitonic Logic Programs
, 2001
"... In a previous work we have de ned Monotonic Logic Programs which extend definite logic programming to arbitrary complete lattices of truthvalues with an appropriate notion of implication. We have shown elsewhere that this framework is general enough to capture Generalized Annotated Logic Programs, ..."
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Cited by 36 (10 self)
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In a previous work we have de ned Monotonic Logic Programs which extend definite logic programming to arbitrary complete lattices of truthvalues with an appropriate notion of implication. We have shown elsewhere that this framework is general enough to capture Generalized Annotated Logic Programs, Probabilistic Deductive Databases, Possibilistic Logic Programming, Hybrid Probabilistic Logic Programs and Fuzzy Logic Programming [3, 4]. However, none of these semantics define a form of nonmonotonic negation, which is fundamental for several knowledge representation applications. In the spirit of our previous work, we generalise our framework of Monotonic Logic Programs to allow for rules with arbitrary antitonic bodies over general complete lattices, of which normal programs are a special case. We then show that all the standard logic programming theoretical results carry over to Antitonic Logic Programs, defining Stable Model and Wellfounded Model alike semantics.