After successful completion of the course, students are able to master the following competences.
Fachliche und methodische Kompetenzen: Stochastic foundations of cyber-physical systems, artificial intelligence, and robotics.
Kognitive und praktische Kompetenzen:
Soziale Kompetenzen und Selbstkompetenzen: Apprehension of and experience in applying theory for solving practical problems.
Didactic concept: Topics are tought in the lectures and practiced in exercises including programming exercises, simulation and application on real-world mobile robots.
Weekly lecture with continually accompanying home-work assignments, deepening the understanding of the module content and increasing the individual problem-solving competence in CPS modelling, analysis, and control. Hand-written or Latex solutions, possibly their mutual peer reviewing, accompanying reading of a book.
Vorlesungen finden hybrid an der TU Wien und online per Zoom statt: https://tuwien.zoom.us/j/94311633591?pwd=eU1DdURuUDVjNmR0bTdRVDQ5RTBkUT09Falls Sie vor Ort teilnehmen möchten, müssen Sie die Sicherheits- und Schutzmaßnahmen an der TU Wien einhalten.
Lectures start s.t.
ECTS-Breakdown 3 ECTS = 150 hours:
Lecture part:
Exercise part:
Homework/project assignments and oral examination.
Registration to the course via TISS. You will be added to the TUWEL course, where the rest of the course will be organized.
S. Russel and P. Norvig, Artificial Intelligence - A Modern Approach, 3rd ed., Upper Saddle River, New Jersey: Pearson Education, 2010.
R.S. Sutton and A.G. Barto - Reinforcement Learning An Introduction second edition. The MIT Press Cambridge, Massachusetts London, England, 2018.
Mandatory prerequisites: None. The following prerequisites are helpful but not mandatory.
Fachliche und methodische Kompetenzen: Probability theory, stochastic signals, control theory, discrete mathematics.
Kognitive und praktische Kompetenzen: Mathematical reasoning and implementation skills.
Soziale Kompetenzen und Selbstkompetenzen: Independent work, interest in combining theory and practice.
These prerequisites are provided in the following modules: Wahrscheinlichkeitstheorie und Stochastische Prozesse, Signale und Systeme, Modellbildung und Regelungstechnik, Discrete Mathematics