Learning outcomes

The class presents problems, methods and systems in automated reasoning. The treatment combines theoretical foundations with algorithmic and practical issues, emphasizing mechanization throughout. The student learns how to design, apply and evaluate methods and systems for automated reasoning, with attention to applications in fields such as analysis, verification, and synthesis of systems, artificial intelligence, mathematics, robotics.

Program

Foundations of automated reasoning: theorem proving and model building. Inference systems, e.g.: instance-based (e.g., hyper-linking), ordering-based (e.g., completion), subgoal-reduction based (e.g., model elimination). Search plans. Algorithmic reasoning in specific fields, e.g.: decision procedures for satisfiability modulo theories (SMT); constraint-based reasoning. Design and use of general-purpose or special-purpose reasoners.

Examination Methods

The grade is given by 30% C1 + 30% C2 + 40% P, where C1 is a written test (midterm exam), C2 is a written test (final exam) and P is a project. The grade thus generated is registered at the first exam session in February.
Alternatively, the grade is given by 100% E, where E is a written test, hard enough to match the difficulty of C1 + C2 + P.
Registration: it is not possible to reject a grade and all grades are registered. Withdrawal: Students may withdraw by informing the instructor. All tests and projects are individual work. Cheating is strictly forbidden and will determine lowering of grades for all students involved.