Dynamic Modelling for Socially Aware Systems - Period 1 STEM in Amsterdam Program Fall 2020 Semester - Amsterdam

Intelligent systems usually encode specific information about the context in which the system executes, e.g. the users, the physical environment and the task environment in which it is used. This information does not only cover environmental states, but also information on the various processes in the environment. Dynamic models are a useful way to encode these processes. In this intense 8-week bachelor course, the students will learn how to develop dynamic models based on literature about process related to human functioning. The course considers methodological aspects of modelling, such as: the collection and specification of relevant knowledge, the definition of relevant ontologies, the definition of simulation experiments and the validation of the results obtained from the modelling process. The course also considers fundamental aspects of dynamical modelling methods, including: defining causal relationships and using causal graphs, defining/using executable specifications, differentiating and integrating quantitative and qualitative models. In addition, a methodology will be taught on how to use such dynamic models as basis for intelligent, human-centered systems. Based on realistic examples from psychology (where emotions or moods are modelled), bio-medicine (where physiological models of the body are used to measure intoxication), or sociology, it is shown how dynamic models of such a domain can be incorporated to derive conclusions about the current situation (assessment) or to decide on relevant actions (support).

During the course, student will combine the completion of weekly assignments based on lectures with the results of constructing models that study self-selected problems. The latter models will be validated via software systems that support analysis and simulation. The student will be challenged to relate the models to relevant external input information (including, where appropriate, sensor-based inputs).

Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.