Results 1  10
of
34
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 ..."
Abstract

Cited by 208 (2 self)
 Add to MetaCart
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 ..."
Abstract

Cited by 159 (2 self)
 Add to MetaCart
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...
Every Logic Program Has a Natural Stratification And an Iterated Least Fixed Point Model (Extended Abstract)
, 1989
"... 1 Introduction The perfect model semantics [ABW88, VG89b, Prz88a, Prz89b] provides an attractive alternative to the traditionally used semantics of logic programs based on Clark's completion of the program [Cla78, Llo84, Fit85, Kun87]. Perfect models are minimal models of the program, which can be ..."
Abstract

Cited by 137 (12 self)
 Add to MetaCart
1 Introduction The perfect model semantics [ABW88, VG89b, Prz88a, Prz89b] provides an attractive alternative to the traditionally used semantics of logic programs based on Clark's completion of the program [Cla78, Llo84, Fit85, Kun87]. Perfect models are minimal models of the program, which can be equivalently described as iterated least fixed points of natural operators [ABW88, VG89b], as iterated least models of the program [ABW88, VG89b] or as preferred models with respect to a natural priority relation [Prz88a, Prz89b]. As a result, the perfect model semantics is not only very intuitive, but it also has been proven equivalent to suitable forms of all four major formalizations of nonmonotonic reasoning in AI (see [Prz88b]) and is used in existing database [Zan88] and truth maintenance systems. Additionally, the perfect model semantics eliminates some serious drawbacks of Clark's semantics [Prz89b] and admits a natural sound and complete procedural mechanism, called SLSresolution [...
What you always wanted to know about Datalog (and never dared to ask
 IEEE Transactions Knowledge and Data Engineering
, 1989
"... AbstractDatalog is a database query language based on the logic programming paradigm; it has been designed and intensively studied over the last five years. We present the syntax and semantics of Datalog and its use for querying a relational database. Then, we classify optimization methods for achi ..."
Abstract

Cited by 136 (1 self)
 Add to MetaCart
AbstractDatalog is a database query language based on the logic programming paradigm; it has been designed and intensively studied over the last five years. We present the syntax and semantics of Datalog and its use for querying a relational database. Then, we classify optimization methods for achieving efficient evaluations of Datalog queries, and present the most relevant methods. Finally, we discuss various exhancements of Datalog, currently under study, and indicate what is still needed in order to extend Datalogâ€™s applicability to the solution of reallife problems. The aim of this paper is to provide a survey of research performed on Datalog, also addressed to those members of the database community who are not too familiar with logic programming concepts. Zndex TermsDeductive databases, logic programming, recursive queries, relational databases, query optimization. I.
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 ..."
Abstract

Cited by 135 (15 self)
 Add to MetaCart
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...
SSemantics Approach: Theory and Applications
, 1994
"... The paper is a general overview of an approach to the semantics of logic programs whose aim is finding notions of models which really capture the operational semantics, and are therefore useful for defining program equivalences and for semanticsbased program analysis. The approach leads to the intr ..."
Abstract

Cited by 115 (26 self)
 Add to MetaCart
The paper is a general overview of an approach to the semantics of logic programs whose aim is finding notions of models which really capture the operational semantics, and are therefore useful for defining program equivalences and for semanticsbased program analysis. The approach leads to the introduction of extended interpretations which are more expressive than Herbrand interpretations. The semantics in terms of extended interpretations can be obtained as a result of both an operational (topdown) and a fixpoint (bottomup) construction. It can also be characterized from the modeltheoretic viewpoint, by defining a set of extended models which contains standard Herbrand models. We discuss the original construction modeling computed answer substitutions, its compositional version and various semantics modeling more concrete observables. We then show how the approach can be applied to several extensions of positive logic programs. We finally consider some applications, mainly in the area of semanticsbased program transformation and analysis.
A Survey of Research on Deductive Database Systems
 JOURNAL OF LOGIC PROGRAMMING
, 1993
"... The area of deductive databases has matured in recent years, and it now seems appropriate to re ect upon what has been achieved and what the future holds. In this paper, we provide an overview of the area and briefly describe a number of projects that have led to implemented systems. ..."
Abstract

Cited by 100 (6 self)
 Add to MetaCart
The area of deductive databases has matured in recent years, and it now seems appropriate to re ect upon what has been achieved and what the future holds. In this paper, we provide an overview of the area and briefly describe a number of projects that have led to implemented systems.
The expressive powers of logic programming semantics
 Abstract in Proc. PODS 90
, 1995
"... We study the expressive powers of two semantics for deductive databases and logic programming: the wellfounded semantics and the stable semantics. We compare them especially to two older semantics, the twovalued and threevalued program completion semantics. We identify the expressive power of the ..."
Abstract

Cited by 84 (5 self)
 Add to MetaCart
We study the expressive powers of two semantics for deductive databases and logic programming: the wellfounded semantics and the stable semantics. We compare them especially to two older semantics, the twovalued and threevalued program completion semantics. We identify the expressive power of the stable semantics, and in fairly general circumstances that of the wellfounded semantics. In particular, over infinite Herbrand universes, the four semantics all have the same expressive power. We discuss a feature of certain logic programming semantics, which we call the Principle of Stratification, a feature allowing a program to be built easily in modules. The threevalued program completion and wellfounded semantics satisfy this principle. Over infinite Herbrand models, we consider a notion of translatability between the threevalued program completion and wellfounded semantics which is in a sense uniform in the strata. In this sense of uniform translatability we show the wellfounded semantics to be more expressive than the threevalued program completion. The proof is a corollary of our result that over nonHerbrand infinite models, the wellfounded semantics is more expressive than the threevalued program completion semantics. 1
Specifications Are (Preferably) Executable
, 1992
"... ion of the Specification Borrowing a saying of Einstein's, I maintain that specifications should be as abstract as possible, but not more abstract. I see three limitations to the degree of abstraction. First, a specification as an adequate formalization of the requirements cannot be more abstract t ..."
Abstract

Cited by 60 (0 self)
 Add to MetaCart
ion of the Specification Borrowing a saying of Einstein's, I maintain that specifications should be as abstract as possible, but not more abstract. I see three limitations to the degree of abstraction. First, a specification as an adequate formalization of the requirements cannot be more abstract than the requirements themselves. If a specific algorithm is required, this algorithm must be specified. This argument applies as well to nonfunctional requirements constraining possible implementations. Some constraints can appear as comments in specifications, e.g. the requirement that a specific language should be used for the implementation. Other constraints, however, must be concretely specified, e.g. the requirement that the future software system has to adhere to the data structures of a given interface. The second limitation to abstraction arises when we make formal specifications executable. Even if the degree of abstraction of the data structures and the algorithms stays the same,...