The group uses different techniques for rule learning from examples: neural networks, inductive logic, genetic algorithms, etc. With these as a starting point, they study the theoretical conditions for the development of learning algorithms in uncertain, imprecise and/or incomplete environments. Furthermore, they work on classification systems in uncertain and/or imprecise environments; knowledge acquisition systems based on validation and refinement; systems integration based on interviews and inductive systems, and based on validation and refinement.