Modelling, Verification, Performance Analysis, Refinement, Synthesis and Machine Learning for Cyber Physical Systems (2024)
Enrolment options
Welcome to Modelling, Verification, Performance Analysis, Refinement, Synthesis and Machine ...
Welcome to Modelling, Verification, Performance Analysis, Refinement, Synthesis and Machine Learning for Cyber Physical Systems
Organizer: Kim Guldstrand Larsen
Lecturers: Kim Guldstrand Larsen, Marius Mikucionis
ECTS: 3
Date/Time: 2, 3, 4, 5, 6, 9, 10 December 2024
Venue: Cassiopaia, Selma Lagerlöfsvej 300, 9220, Room 0.2.90.
Deadline: 11 November 2024
Max no. Of participants: 30
Description: Timed automata and games, priced timed automata and energy automata have emerged as useful formalisms for modeling real-time and energy-aware systems as found in several embedded and cyber-physical systems. During the last 20 years the real-time model checker UPPAAL has been developed allowing for efficient verification of hard timing constraints of timed automata. Moreover a number of significant branches exists, e.g. UPPAAL CORA providing efficient support for optimization, and UPPAAL TIGA allowing for automatic synthesis of strategies for given safety and liveness objectives, and ECDAR supports refinement and compositional development of real-time systems. Also the branch UPPAAL SMC, provides a highly scalable new engine supporting (distributed) statistical model checking of stochastic hybrid automata, and most recently the new branch UPPAAL STRATEGO supporting safe and optimal strategies for stochastic hybrid games by combining symbolic methods with machine learning. The course will review the various branches of UPPAAL, the corresponding modeling formalisms as well as the symbolic or statistical algorithms applied. Also, examples on applications of the tools suite will be given to a range of real-time and cyber-physical examples including schedulability and performance evaluation of mixed criticality systems, modeling and analysis of biological systems, energy-aware wireless sensor networks, smart grids and smart houses and battery scheduling.
Prerequisites: A general background in computer science or a related engineering discipline with basic knowledge about finite-state automata, probability theory and ordinary differential equations. Some basic programming skills are needed.
Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.