After successful completion of the course, students are able to analyze and classify computational problems, mainly located in the area of logic-based AI, with tools from computational complexity theory.

Problem solving methods whith are connected with intelligent systems, via methods of complexity theory. Design of efficient algorithms starting from the analysis of the complexity of problems on exemplaric intelligent systems.

ECTS breakdown: 3 ECTS = 75 Hours

• Lecture presentation 0.5h
• Lecture 17.5h
• Further reading 25h
• Discussion of the exercises 1.5h
• Solving the exercises 30h
• Oral exam (if applicable) 0.5h

computational complexiy theory, mathematical analysis, formal proofs, use cases, problem solving heuristics

course in block form, April - May/June, according to the TU regulations in Distance Learning Mode.

• Lecture recordings, slides made available
• Questions and Answers (Q+A) sessions
• Discussion of exercises

In case physical attendence meetings would be possible, a hybrid mode could be imagined (consensual with the course participants).

• original class schedule: Friday morning, 9:00 -12:30,
• Q+A Sessions (one per lecture, 1.5h each): Friday morning resp. by agreement

First Meeting: Friday, April 16, 2021, 9:15h

Further information will be released in due time.

• exercises (exercise part);
• take-home exam with optional oral exam, respectively oral follow-up questions to check the plausibility of answers.

Technical requirements:

•  exercises / take home exam (open book): email / file upload
• oral exam / follow-up questions: intenet connection, webcam, browser, audio-set. In case physical meetings are possible, this is not needed.

Specific details will be given in due time.

basic knowledge of concepts in theoretical computer science (Turing machine model, computation, algorithms) and logic (Boolean logic)