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With the technology of the time, Kowalski's seminal 1974 paper Predicate Logic as a Programming Language was a breakthrough for the use of logic in computer science. It introduced two fundamental ideas: on the declarative side, the use of the Horn clause logic fragment of classical logic, which was soon extended with negation as failure, on the procedural… (More)

- Maurice Bruynooghe, Hendrik Blockeel, Bart Bogaerts, Broes de Cat, Stef De Pooter, Joachim Jansen +4 others
- TPLP
- 2015

This paper provides a gentle introduction to problem solving with the IDP3 system. The core of IDP3 is a finite model generator that supports first order logic enriched with types, inductive definitions, aggregates and partial functions. It offers its users a modeling language that is a slight extension of predicate logic and allows them to solve a wide… (More)

Finding satisfying assignments for the variables involved in a set of constraints can be cast as a (bounded) model generation problem: search for (bounded) models of a theory in some logic. The state-of-the-art approach for bounded model generation for rich knowledge representation languages like Answer Set Programming (ASP) and FO(·) and a CSP modeling… (More)

The traditional approach to Model Expansion (MX) is to reduce the theory to a propositional language and apply a search algorithm to the resulting theory. Function symbols are typically replaced by predicate symbols representing the graph of the function, an operation that blows up the reduced theory. In this paper, we present an improved approach to handle… (More)

Ground-and-solve methods used in state-of-the-art Answer Set Programming and model expansion systems proceed by rewriting the problem specification into a ground format and afterwards applying search. A disadvantage of such approaches is that the rewriting step blows up the original specification for large input domains and is unfeasible in case of infinite… (More)

Dynamic systems play a central role in fields such as planning, verification, and databases. Fragmented throughout these fields, we find a multitude of languages to formally specify dynamic systems and a multitude of systems to reason on such specifications. Often, such systems are bound to one specific language and one specific inference task. It is… (More)

- Maurice Bruynooghe, Broes De Cat, Jochen Drijkoningen, Daan Fierens, Jan Goos, Bernd Gut +18 others
- 2009

We report on two exercises in modeling, inference and learning with seven statistical re-lational learning systems and use this as a basis for a simple and preliminary comparison between these systems.

For constraint programming, many well performing dynamic symmetry breaking techniques have been devised. For propositional satisfiability solving, dynamic symmetry breaking is still either slower or less general than static symmetry breaking. This paper presents Symmetry Propagation, which is an improvement to Lightweight Dynamic Symmetry Breaking, a… (More)

- Hendrik Blockeel, Bart Bogaerts, Maurice Bruynooghe, Broes de Cat, Stef De Pooter, Marc Denecker +3 others
- ICLP
- 2012

This paper reports on the use of the FO(·) language and the IDP framework for modeling and solving some machine learning and data mining tasks. The core component of a model in the IDP framework is an FO(·) theory consisting of formulas in first order logic and definitions; the latter are basically logic programs where clause bodies can have arbitrary first… (More)