Knowledge Representation and Reasoning Group

Research Topics


The Knowledge Representation and Reasoning group at the KU Leuven university is focussed on the advancement of theory, practice and applications that study the formalization of domain knowledge and reason on this knowledge. Specifically, the study involves knowledge bases and follows the knowledge base paradigm.

Knowledge representation and reasoning is devoted to representing information about the world in a form that can be utilized to solve complex tasks. A Knowledge Base System works towards that goal by allowing one to have a single representation of the information about a problem domain and to use it to solve a wide range of tasks.

Languages

Expressive logic constructs are needed to formulate many forms of knowledge. The current system supports first order logic extended with inductive definitions, types, arithmetic, aggregates and partial functions. For some problem domains, more is needed such as constructed types, or higher order logic.

Solvers and Inference Methods

Solving a wide range of tasks using a single logic based representation requires a powerful solver that supports many forms of inference, that can invoke existing solvers (constraint programming, mixed integer programming, ...) and that can interact with a procedural environment.

Applications

Many search problems have a succinct representation within IDP3. The system has been successfully applied on a number of machine learning and data mining problems.

Semantic theory

How can we formalize the meaning of the knowledge that we write down. Any knowledge representation language must strive to formalize as truthful as possible the already existing informal semantics. Using semantical frameworks such as model semantics and Approximation Fixpoint Theory, we can formalize statements.

Highlighted publications


The following list of publications gives an overview of the most important papers published by (co-)authors within our research group. For a full overview, we refer to the DTAI overview page.

  • Certified Symmetry and Dominance Breaking for Combinatorial Optimisation. Bart Bogaerts, Stephan Gocht, Ciaran McCreesh and Jakob Nordström. 36th AAAI Conference on Artificial Intelligence, 2022.
  • Improved Static Symmetry Breaking for SAT. Jo Devriendt, Bart Bogaerts, Maurice Bruynooghe, Marc Denecker. Lecture Notes in Computer Science, 2016.
  • Predicate Logic as a Modelling Language: The IDP System. Broes De Cat, Bart Bogaerts, Maurice Bruynooghe, Gerda Janssens, Marc Denecker. Declarative Logic Programming, 2018.
  • A logic of nonmonotone inductive definitions. Marc Denecker, Eugenia Ternovska. ACM Transactions on Computational Logic, 2008.
  • Grounding FO and FO(ID) with bounds. Johan Wittocx, Maarten Mariën, Marc Denecker. The Journal of Artificial Research, 2010.
  • Ultimate approximation and its application in nonmonotonic knowledge representation systems. Marc Denecker, Victor Marek, Miroslaw Truszczynski. Information and computation, 2004.

Awards and news