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Description Logic Programs: Combining Logic Programs with Description Logic

by Benjamin N. Grosof, Ian Horrocks , 2002
"... We show how to interoperate, semantically and inferentially, between the leading Semantic Web approaches to rules (RuleML Logic Programs) and ontologies (OWL/DAML+OIL Description Logic) via analyzing their expressive intersection. To do so, we define a new intermediate knowledge representation (KR) ..."
Abstract - Cited by 529 (46 self) - Add to MetaCart
) contained within this intersection: Description Logic Programs (DLP), and the closely related Description Horn Logic (DHL) which is an expressive fragment of first-order logic (FOL). DLP provides a significant degree of expressiveness, substantially greater than the RDFSchema fragment of Description Logic.

Constraint Logic Programming: A Survey

by Joxan Jaffar, Michael J. Maher
"... Constraint Logic Programming (CLP) is a merger of two declarative paradigms: constraint solving and logic programming. Although a relatively new field, CLP has progressed in several quite different directions. In particular, the early fundamental concepts have been adapted to better serve in differe ..."
Abstract - Cited by 869 (25 self) - Add to MetaCart
Constraint Logic Programming (CLP) is a merger of two declarative paradigms: constraint solving and logic programming. Although a relatively new field, CLP has progressed in several quite different directions. In particular, the early fundamental concepts have been adapted to better serve

Abduction in Logic Programming

by Marc Denecker, Antonis Kakas
"... Abduction in Logic Programming started in the late 80s, early 90s, in an attempt to extend logic programming into a framework suitable for a variety of problems in Artificial Intelligence and other areas of Computer Science. This paper aims to chart out the main developments of the field over th ..."
Abstract - Cited by 624 (77 self) - Add to MetaCart
Abduction in Logic Programming started in the late 80s, early 90s, in an attempt to extend logic programming into a framework suitable for a variety of problems in Artificial Intelligence and other areas of Computer Science. This paper aims to chart out the main developments of the field over

Learning Stochastic Logic Programs

by Stephen Muggleton , 2000
"... Stochastic Logic Programs (SLPs) have been shown to be a generalisation of Hidden Markov Models (HMMs), stochastic context-free grammars, and directed Bayes' nets. A stochastic logic program consists of a set of labelled clauses p:C where p is in the interval [0,1] and C is a first-order r ..."
Abstract - Cited by 1194 (81 self) - Add to MetaCart
Stochastic Logic Programs (SLPs) have been shown to be a generalisation of Hidden Markov Models (HMMs), stochastic context-free grammars, and directed Bayes' nets. A stochastic logic program consists of a set of labelled clauses p:C where p is in the interval [0,1] and C is a first-order

The Semantics Of Constraint Logic Programs

by Joxan Jaffar, Michael Maher, Kim Marriott, Peter Stuckey - JOURNAL OF LOGIC PROGRAMMING , 1996
"... This paper presents for the first time the semantic foundations of CLP in a self-contained and complete package. The main contributions are threefold. First, we extend the original conference paper by presenting definitions and basic semantic constructs from first principles, giving new and comp ..."
Abstract - Cited by 872 (14 self) - Add to MetaCart
This paper presents for the first time the semantic foundations of CLP in a self-contained and complete package. The main contributions are threefold. First, we extend the original conference paper by presenting definitions and basic semantic constructs from first principles, giving new

Markov Logic Networks

by Matthew Richardson, Pedro Domingos - MACHINE LEARNING , 2006
"... We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge base with a weight attached to each formula (or clause). Together with a set of constants representing objects in the ..."
Abstract - Cited by 816 (39 self) - Add to MetaCart
learned from relational databases by iteratively optimizing a pseudo-likelihood measure. Optionally, additional clauses are learned using inductive logic programming techniques. Experiments with a real-world database and knowledge base in a university domain illustrate the promise of this approach.

Higher-Order Abstract Syntax

by Frank Pfenning, Conal Elliott
"... We describe motivation, design, use, and implementation of higher-order abstract syntax as a central representation for programs, formulas, rules, and other syntactic objects in program manipulation and other formal systems where matching and substitution or syntax incorporates name binding informat ..."
Abstract - Cited by 357 (17 self) - Add to MetaCart
We describe motivation, design, use, and implementation of higher-order abstract syntax as a central representation for programs, formulas, rules, and other syntactic objects in program manipulation and other formal systems where matching and substitution or syntax incorporates name binding

The Stable Model Semantics For Logic Programming

by Michael Gelfond, Vladimir Lifschitz , 1988
"... We propose a new declarative semantics for logic programs with negation. Its formulation is quite simple; at the same time, it is more general than the iterated fixed point semantics for stratied programs, and is applicable to some useful programs that are not stratified. ..."
Abstract - Cited by 1847 (63 self) - Add to MetaCart
We propose a new declarative semantics for logic programs with negation. Its formulation is quite simple; at the same time, it is more general than the iterated fixed point semantics for stratied programs, and is applicable to some useful programs that are not stratified.

Dynamic Logic

by David Harel, Dexter Kozen, Jerzy Tiuryn - Handbook of Philosophical Logic , 1984
"... ed to be true under the valuation u iff there exists an a 2 N such that the formula x = y is true under the valuation u[x=a], where u[x=a] agrees with u everywhere except x, on which it takes the value a. This definition involves a metalogical operation that produces u[x=a] from u for all possibl ..."
Abstract - Cited by 1012 (7 self) - Add to MetaCart
possible values a 2 N. This operation becomes explicit in DL in the form of the program x := ?, called a nondeterministic or wildcard assignment. This is a rather unconventional program, since it is not effective; however, it is quite useful as a descriptive tool. A more conventional way to obtain a

A Framework for Defining Logics

by Robert Harper , Furio Honsell, Gordon Plotkin - JOURNAL OF THE ASSOCIATION FOR COMPUTING MACHINERY , 1993
"... The Edinburgh Logical Framework (LF) provides a means to define (or present) logics. It is based on a general treatment of syntax, rules, and proofs by means of a typed -calculus with dependent types. Syntax is treated in a style similar to, but more general than, Martin-Lof's system of ariti ..."
Abstract - Cited by 795 (42 self) - Add to MetaCart
conditions and leads to a uniform treatment of rules and proofs whereby rules are viewed as proofs of higher-order judgements and proof checking is reduced to type checking. The practical benefit of our treatment of formal systems is that logic-independent tools such as proof editors and proof checkers
Results 1 - 10 of 97,112