Provides an introduction to general problem solving methods used in artificial intelligence and knowledge-based systems. The course presents a variety of search approaches as well as modern knowledge representation and reasoning systems implementing them.

Classroom instructions mixed with practical exercises. The teaching language is English or German depending on the preferences of the audience. The slides are in English.

Covered topics include:Uninformed and informed search methodsOverview of incomplete (local) approaches to solving hard problemsKnowledge representation and reasoning with constraints programmingMiniZinc programming language   Game playing          

Algorithms and data structures

Nothing 

Stuart Russell and Peter Norvig: Artificial Intelligence: A modern approach. Prentice Hall, 2009Rina Dechter: Constraint Processing. Morgan Kaufmann Publishers, 2003Stefan Edelkamp and Stefan Schrödl: Heuristic search: theory and applications. Elsevier, 2011

Written exam (end of semester), short tests (during the semester), active participation (bonus)

Topics covered in the module, but in particular logic, planning, constraint satisfaction, heuristic search, uncertain reasoning.

Points obtained from short tests, the exam and active participation will be incorporated in the final grade. A possible scheme (subject to appropriate calibration) is to add together up to3 x 20 points for short tests210 points for the examactive participation points (e.g., demonstration of exercise solutions)Then grade 1 will match between 180 and 200 points, grade 4 between 100 and 120 points, and the other grades gradually distributed between the top and the bottom.