184.215 Complexity Analysis
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2024S, VU, 2.0h, 3.0EC, to be held in blocked form
TUWEL

Properties

  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VU Lecture and Exercise
  • Format: Online

Learning outcomes

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.

Subject of course

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

Teaching methods

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

Mode of examination

Written

Additional information

Course in block form April - May, planned for physical attendance.

If physical meetings will not be possible, for Distance Learning the plan would be:

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

Class schedule (tentative)

  • Mon morning, 9:00 -12:45  (Apr 8, 15)
  • Fri morning, 9:00 -12:45 (Apr 19, 26, May 3)

First Meeting: Monday, April 8, 2024

Further information by TISS-notifications in due time.

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Mon09:00 - 13:0004.03.2024 - 24.06.2024Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Fri09:00 - 13:0019.04.2024 - 03.05.2024Seminarraum FAV 01 A (Seminarraum 183/2) Complexity Analysis
Fri09:00 - 13:0010.05.2024Seminarraum FAV EG B (Seminarraum von Neumann) VU Complexity Analysis
Complexity Analysis - Single appointments
DayDateTimeLocationDescription
Mon04.03.202409:00 - 13:00Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Mon11.03.202409:00 - 13:00Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Mon18.03.202409:00 - 13:00Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Mon08.04.202409:00 - 13:00Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Mon15.04.202409:00 - 13:00Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Fri19.04.202409:00 - 13:00Seminarraum FAV 01 A (Seminarraum 183/2) Complexity Analysis
Mon22.04.202409:00 - 13:00Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Fri26.04.202409:00 - 13:00Seminarraum FAV 01 A (Seminarraum 183/2) Complexity Analysis
Mon29.04.202409:00 - 13:00Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Fri03.05.202409:00 - 13:00Seminarraum FAV 01 A (Seminarraum 183/2) Complexity Analysis
Mon06.05.202409:00 - 13:00Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Fri10.05.202409:00 - 13:00Seminarraum FAV EG B (Seminarraum von Neumann) VU Complexity Analysis
Mon13.05.202409:00 - 13:00Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Mon27.05.202409:00 - 13:00Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Mon03.06.202409:00 - 13:00Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Mon10.06.202409:00 - 13:00Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Mon17.06.202409:00 - 13:00Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Mon24.06.202409:00 - 13:00Seminarraum FAV EG C (Seminarraum Gödel) Lecture
Course is held blocked

Examination modalities

  • 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.

Course registration

Begin End Deregistration end
13.02.2024 20:00 24.05.2024 11:00 24.05.2024 22:00

Curricula

Literature

Previous knowledge

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

Miscellaneous

  • Attendance Required!

Language

English