We equip ordered logic programs with negation as failure, using a simple generalization of the preferred answer set semantics for ordered programs. This extension supports a conven...
Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integratio...
In this paper we propose a type-based framework for using logic programming for XML processing. We transform XML documents into terms and DTDs into regular types. We implemented a ...
We present a system, BLF, that combines an authorization logic based on the Binder language with a logical framework, LF, able to express semantic properties of programs. BLF is a...
We pursue the program of exposing the intrinsic mathematical structure of the “space of proofs” of a logical system [AJ94b]. We study the case of Multiplicative-Additive Linea...