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Automating FirstOrder Relational Logic
, 2000
"... An analysis is described that can automatically find models of firstorder formulas with relational operators and scalar quantifiers. The formula is translated to a quantifierfree boolean formula that has a model exactly when the original formula has a model within a given scope (that is, involving ..."
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Cited by 143 (23 self)
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An analysis is described that can automatically find models of firstorder formulas with relational operators and scalar quantifiers. The formula is translated to a quantifierfree boolean formula that has a model exactly when the original formula has a model within a given scope (that is
Learning logical definitions from relations
 MACHINE LEARNING
, 1990
"... This paper describes FOIL, a system that learns Horn clauses from data expressed as relations. FOIL is based on ideas that have proved effective in attributevalue learning systems, but extends them to a firstorder formalism. This new system has been applied successfully to several tasks taken fro ..."
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Cited by 935 (8 self)
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This paper describes FOIL, a system that learns Horn clauses from data expressed as relations. FOIL is based on ideas that have proved effective in attributevalue learning systems, but extends them to a firstorder formalism. This new system has been applied successfully to several tasks taken
Markov Logic Networks
 MACHINE LEARNING
, 2006
"... We propose a simple approach to combining firstorder logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a firstorder knowledge base with a weight attached to each formula (or clause). Together with a set of constants representing objects in the ..."
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Cited by 816 (39 self)
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We propose a simple approach to combining firstorder logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a firstorder knowledge base with a weight attached to each formula (or clause). Together with a set of constants representing objects
Description Logic Programs: Combining Logic Programs with Description Logic
, 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) ..."
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Cited by 529 (46 self)
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) contained within this intersection: Description Logic Programs (DLP), and the closely related Description Horn Logic (DHL) which is an expressive fragment of firstorder logic (FOL). DLP provides a significant degree of expressiveness, substantially greater than the RDFSchema fragment of Description Logic.
An Analysis of FirstOrder Logics of Probability
 Artificial Intelligence
, 1990
"... : We consider two approaches to giving semantics to firstorder logics of probability. The first approach puts a probability on the domain, and is appropriate for giving semantics to formulas involving statistical information such as "The probability that a randomly chosen bird flies is greater ..."
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Cited by 314 (17 self)
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: We consider two approaches to giving semantics to firstorder logics of probability. The first approach puts a probability on the domain, and is appropriate for giving semantics to formulas involving statistical information such as "The probability that a randomly chosen bird flies
The Semantics of Predicate Logic as a Programming Language
 JOURNAL OF THE ACM
, 1976
"... Sentences in firstorder predicate logic can be usefully interpreted as programs In this paper the operational and fixpoint semantics of predicate logic programs are defined, and the connections with the proof theory and model theory of logic are investigated It is concluded that operational seman ..."
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Cited by 808 (18 self)
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Sentences in firstorder predicate logic can be usefully interpreted as programs In this paper the operational and fixpoint semantics of predicate logic programs are defined, and the connections with the proof theory and model theory of logic are investigated It is concluded that operational
Learning Stochastic Logic Programs
, 2000
"... Stochastic Logic Programs (SLPs) have been shown to be a generalisation of Hidden Markov Models (HMMs), stochastic contextfree 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 firstorder r ..."
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Cited by 1194 (81 self)
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Stochastic Logic Programs (SLPs) have been shown to be a generalisation of Hidden Markov Models (HMMs), stochastic contextfree 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 firstorder
Constraint Logic Programming: A Survey
"... 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 ..."
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Cited by 869 (25 self)
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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
Dynamic Predicate Logic
, 1990
"... This paper is devoted to the formulation and investigation of a dynamic semantic interpretation of the language of firstorder predicate logic. The resulting system, which will be referred to as `dynamic predicate logic', is intended as a first step towards a compositional, nonrepresentational ..."
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Cited by 462 (2 self)
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This paper is devoted to the formulation and investigation of a dynamic semantic interpretation of the language of firstorder predicate logic. The resulting system, which will be referred to as `dynamic predicate logic', is intended as a first step towards a compositional, non
Nonmonotonic Reasoning, Preferential Models and Cumulative Logics
, 1990
"... Many systems that exhibit nonmonotonic behavior have been described and studied already in the literature. The general notion of nonmonotonic reasoning, though, has almost always been described only negatively, by the property it does not enjoy, i.e. monotonicity. We study here general patterns of ..."
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Cited by 626 (14 self)
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of nonmonotonic reasoning and try to isolate properties that could help us map the field of nonmonotonic reasoning by reference to positive properties. We concentrate on a number of families of nonmonotonic consequence relations, defined in the style of Gentzen [13]. Both prooftheoretic and semantic points
Results 1  10
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