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Splitting a Logic Program
 Principles of Knowledge Representation
, 1994
"... In many cases, a logic program can be divided into two parts, so that one of them, the \bottom " part, does not refer to the predicates de ned in the \top " part. The \bottom " rules can be used then for the evaluation of the predicates that they de ne, and the computed va ..."
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Cited by 294 (16 self)
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In many cases, a logic program can be divided into two parts, so that one of them, the \bottom &quot; part, does not refer to the predicates de ned in the \top &quot; part. The \bottom &quot; rules can be used then for the evaluation of the predicates that they de ne, and the computed values can be used to simplify the \top &quot; de nitions. We discuss this idea of splitting a program in the context of the answer set semantics. The main theorem shows how computing the answer sets for a program can be simpli ed when the program is split into parts. The programs covered by the theorem may use both negation as failure and classical negation, and their rules may have disjunctive heads. The usefulness of the concept of splitting for the investigation of answer sets is illustrated by several applications. First, we show that a conservative extension theorem by Gelfond and Przymusinska and a theorem on the closed world assumption by Gelfond and Lifschitz are easy consequences of the splitting theorem. Second, (locally) strati ed programs are shown to have a simple characterization in terms of splitting. The existence and uniqueness of an answer set for such a program can be easily derived from this characterization. Third, we relate the idea of splitting to the notion of orderconsistency. 1
A Novel Combination of Answer Set Programming with Description Logics for the Semantic Web
 IN PROC. KR2004
, 2004
"... Abstract. We present a novel combination of disjunctive logic programs under the answer set semantics with description logics for the Semantic Web. The combination is based on a wellbalanced interface between disjunctive logic programs and description logics, which guarantees the decidability of th ..."
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Cited by 288 (60 self)
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Abstract. We present a novel combination of disjunctive logic programs under the answer set semantics with description logics for the Semantic Web. The combination is based on a wellbalanced interface between disjunctive logic programs and description logics, which guarantees the decidability of the resulting formalism without assuming syntactic restrictions. We show that the new formalism has very nice semantic properties. In particular, it faithfully extends both disjunctive programs and description logics. Furthermore, we describe algorithms for reasoning in the new formalism, and we give a precise picture of its computational complexity. We also provide a special case with polynomial data complexity. 1
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 273 (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.
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 244 (3 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.
Delegation Logic: A Logicbased Approach to Distributed Authorization
 ACM Transactions on Information and System Security
, 2000
"... We address the problem of authorization in largescale, open... ..."
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Cited by 243 (14 self)
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We address the problem of authorization in largescale, open...
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 242 (20 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.
XSB as an Efficient Deductive Database Engine
 In Proceedings of the ACM SIGMOD International Conference on the Management of Data
, 1994
"... This paper describes the XSB system, and its use as an inmemory deductive database engine. XSB began from a Prolog foundation, and traditional Prolog systems are known to have serious deficiencies when used as database systems. Accordingly, XSB has a fundamental bottomup extension, introduced thro ..."
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Cited by 236 (32 self)
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This paper describes the XSB system, and its use as an inmemory deductive database engine. XSB began from a Prolog foundation, and traditional Prolog systems are known to have serious deficiencies when used as database systems. Accordingly, XSB has a fundamental bottomup extension, introduced through tabling (or memoing) [5], which makes it appropriate as an underlying query engine for deductive database systems. Because it eliminates redundant computation, the tabling extension makes XSB able to compute all modularly stratified datalog programs finitely and with polynomial data complexity. For nonstratified programs, a metainterpreter with the same properties is provided. In addition XSB significantly extends and improves the indexing capabilities over those of standard Prolog. Finally, its syntactic basis in HiLog [2], lends it flexibility for data modelling. The implementation of XSB derives from the WAM, the most common Prolog engine. XSB inherits the WAM's efficiency and can ta...
Answer Set Planning
"... In "answer set programming," solutions to a problem are represented by answer sets, and not by answer substitutions produced in response to a query, as in conventional logic programming. Instead of Prolog, answer set programming uses software systems capable of computing answer sets. This ..."
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Cited by 171 (6 self)
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In "answer set programming," solutions to a problem are represented by answer sets, and not by answer substitutions produced in response to a query, as in conventional logic programming. Instead of Prolog, answer set programming uses software systems capable of computing answer sets. This paper is about applications of this idea to planning.
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 169 (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...