182.763 Stochastic Foundations of Cyber-Physical Systems
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2019W, VU, 4.0h, 6.0EC

Properties

  • Semester hours: 4.0
  • Credits: 6.0
  • Type: VU Lecture and Exercise

Learning outcomes

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:

  • Ability to learn stochastic models of CPS. 
  • Ability to perform stochastic analysis of CPS 
  • Ability to design optimal controllers for CPS. 

Soziale Kompetenzen und Selbstkompetenzen: Apprehension of and experience in applying theory for solving practical problems.

Subject of course

  • Probabilistic interpretation of uncertainty.
  • Rational agents as smart cyber-physical systems (CPS).
  • Static (sBN) and dynamic (dBN) Bayesian networks (BN).
  • Uncertain environments as sBN and dBN.
  • Exact and approximate inference in BN.
  • Machine learning (supervised) of sBN and dBN.
  • Decision making and optimal control for Markov Decision Processes.
  • Supervised (sML) and reinforcement (rML) learning.
  • Machine learning (sML and rML) with deep neural networks.
  • Speech-recognition and robotics.

Didactic concept: Topics are tought in the lectures and practiced in exercises including programming exercises, simulation and application on real-world mobile robots.

Teaching methods

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

Mode of examination

Written and oral

Additional information


Lectures start s.t.

ECTS-Breakdown 3 ECTS = 150 hours:

Lecture part:

  • 0.5h  lecture introduction
  • 54h (18 lectures, 2h per lecture + 1h pre/postprocessing)
  • 20h exam preparation
  • 0.5h  oral exam
    ----
    75h

Exercise part:

  • 75h exercises

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Tue10:00 - 12:0001.10.2019 - 28.01.2020 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Thu10:00 - 12:0003.10.2019 - 30.01.2020 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Stochastic Foundations of Cyber-Physical Systems - Single appointments
DayDateTimeLocationDescription
Tue01.10.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Thu03.10.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Tue08.10.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Thu10.10.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Tue15.10.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Thu17.10.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Tue22.10.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Thu24.10.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Tue29.10.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Thu31.10.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Tue05.11.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Thu07.11.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Tue12.11.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Thu14.11.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Tue19.11.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Thu21.11.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Tue26.11.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Thu28.11.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Tue03.12.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class
Thu05.12.201910:00 - 12:00 CPS Library (Treitlstrasse 1, 3rd Floor)CPS-Stochastic Foundation Class

Examination modalities

Homework/project assignments and oral examination.

Course registration

Begin End Deregistration end
23.09.2019 23:59 14.10.2019 23:59 14.10.2019 23:59

Registration modalities:

Registration to the course via TISS. You will be added to the TUWEL course, where the rest of the course will be organized.

Curricula

Study CodeSemesterPrecon.Info
066 938 Computer Engineering

Literature

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.

Previous knowledge

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

Continuative courses

Language

English