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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)
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)
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)
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)
Data mining tasks and algorithms are often categorized as belonging to one of a few specific types: clustering , association rule discovery, probabilistic modeling, etc. For some time now, it has been recognized that concrete tasks do not always fit nicely in this categorization. The concepts of constraint-based data mining and inductive querying have been(More)
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)
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)