Explainable Cyber-Physical systems
Explainable Cyber-Physical systems
Welcome to the course "Explainable Cyber-Physical Systems"
Are you curious to find out more about what to expect from this course?
Autonomous systems and robots are becoming increasingly important in daily life, from transportation and industry to smart homes. These systems often perform safety-critical tasks and collaborate closely with humans. For such collaboration to be effective, humans need to understand what the system is doing, why it is doing it, and when. Without explainability, trust and usability are limited.
This course introduces the emerging research area of Explainability in cyber-physical systems (CPS), covering applications such as autonomous vehicles, robotics, Industry 4.0/5.0, and smart environments. While not a pure XAI course, it provides a holistic overview of explainability: what it means, why it matters, what and when to explain, how to design self-explaining systems, and how to generate and present explanations effectively.
The course is structured into three main components:
- Lectures – Cover fundamental concepts from CPS and Industry 4.0/5.0 to explainability, transparency, trust, and methods for generating and evaluating explanations.
- Exercises – Hands-on activities and discussions to deepen understanding of specific aspects of explainability.
- Project Work – Development of integration of explanations and explanation generation into an existing CPS. Students present intermediate ideas, showcase final results, and submit a short report documenting their design process, implementation, and lessons learned.
By the end of the course, students will gain both theoretical and practical insights into designing and evaluating not only explanations but also self-explaining cyber-physical systems.