Yunsong Meng

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We provide reformulations and generalizations of both the semantics of logic programs by Faber, Leone and Pfeifer and its extension to arbitrary propositional formulas by Truszczyński. Unlike the previous definitions, our generalizations refer neither to grounding nor to fixpoints, and apply to firstorder formulas containing aggregate expressions. In the(More)
Lin and Zhao’s theorem on loop formulas states that in the propositional case the stable model semantics of a logic program can be completely characterized by propositional loop formulas, but this result does not fully carry over to the first-order case. We investigate the precise relationship between the first-order stable model semantics and first-order(More)
The advent of emerging technologies such as Web services, service-oriented architecture, and cloud computing has enabled us to perform business services more efficiently and effectively. However, we still suffer from unintended security leakages by unauthorized services while providing more convenient services to Internet users through such a cutting-edge(More)
Recently Ferraris, Lee and Lifschitz proposed a new definition of stable models that does not refer to grounding, which applies to the syntax of arbitrary first-order sentences. We show its relation to the idea of loop formulas with variables by Chen, Lin, Wang and Zhang, and generalize their loop formulas to disjunctive programs and to arbitrary(More)
Answer Set Programming Modulo Theories is a new framework of tight integration of answer set programming (ASP) and satisfiability modulo theories (SMT). Similar to the relationship between first-order logic and SMT, it is based on a recent proposal of the functional stable model semantics by fixing interpretations of background theories. Analogously to a(More)
We introduce the language LP that extends logic programs under the stable model semantics to allow weighted rules similar to the way Markov Logic considers weighted formulas. LP is a proper extension of the stable model semantics to enable probabilistic reasoning, providing a way to handle inconsistency in answer set programming. We also show that the(More)
We provide reformulations and generalizations of both the semantics of logic programs by Faber, Leone and Pfeifer and its extension to arbitrary propositional formulas by Truszczyński. Unlike the previous definitions, our generalizations refer neither to grounding nor to fixpoints, and apply to first-order formulas containing aggregate expressions. Similar(More)
Applications of answer set programming motivated various extensions of the stable model semantics, for instance, to allow aggregates or to facilitate interface with external ontology descriptions. We present a uniform, reductive view on these extensions by viewing them as special cases of formulas with generalized quantifiers. This is done by extending the(More)