inf338 - Design of Autonomous Systems (Course overview)

inf338 - Design of Autonomous Systems (Course overview)

Department of Computing Science 6 KP
Module components Semester courses Summer semester 2025 Examination
Lecture
  • Limited access 2.01.358 - Engineering Self-Adaptive Systems Show lecturers
    • M. Sc. Ali Torbati
    • Prof. Dr. Verena Klös

    Wednesday: 10:00 - 12:00, weekly (from 09/04/25), Location: V03 3-S326
    Thursday: 10:00 - 12:00, weekly (from 17/04/25), Location: S 2-204
    Self-adaptive systems adapt their behaviour or their architecture to changing conditions in their operating context. They provide the flexibility necessary for coping with design time uncertainties. In this course you will learn about: - the motivation for self-adaptation - the basic principles and conceptual model of self-adaptation - how to engineer self-adaptive software systems - how to ensure quality of those systems - the notion of uncertainty in self-adaptive systems and how to tame it - typical application domains for self-adaptive systems
Exercises
  • Limited access 2.01.358 - Engineering Self-Adaptive Systems Show lecturers
    • M. Sc. Ali Torbati
    • Prof. Dr. Verena Klös

    Wednesday: 10:00 - 12:00, weekly (from 09/04/25), Location: V03 3-S326
    Thursday: 10:00 - 12:00, weekly (from 17/04/25), Location: S 2-204
    Self-adaptive systems adapt their behaviour or their architecture to changing conditions in their operating context. They provide the flexibility necessary for coping with design time uncertainties. In this course you will learn about: - the motivation for self-adaptation - the basic principles and conceptual model of self-adaptation - how to engineer self-adaptive software systems - how to ensure quality of those systems - the notion of uncertainty in self-adaptive systems and how to tame it - typical application domains for self-adaptive systems
Notes on the module
Prerequisites

No participant requirements
Prüfungszeiten

Second half of semester
Module examination

Presentation
Skills to be acquired in this module

Professional competences
The students

  • are enabled to analyze and build autonomous systems.

Methodological competences
The students

  • know examples of existing autonomous systems, understand the elements involved in their architectural design and the rationale behind decomposing the problem into obligations for the respective system components.
  • analyze existing architectures for autonomous systems with respect to their performance and safety.
  • learn how to decompose a problem of designing an autonomous system into an architecture
  • are able to derive design obligations for its components, and can structure a pertinent safety case.
  • understand the software and hardware components necessary for achieving system autonomy and are able to design or instantiate these.

Social competences
The students

  • acquire hands-on experience in designing components for autonomous systems in small teams and present the underlying theory, their particular design decisions, and their personal evaluation to fellow students.

Self-competences
The students

  • can judge adequacy of their methodological skills for designing particular autonomous solutions
  • are able to assess the safety impact of such a solution and are therefore able to develop a personal ethical stance towards its realization