Dynamic Modelling for Human-Centered Systems

Course

URL study guide

https://studiegids.vu.nl/en/courses/2024-2025/XB_0036

Course Objective

At the end of the course, the student has knowledge and understanding of: the role that dynamic models can play in systems aiming to understand and support human behaviour; the steps required to develop a dynamic model; different representations and implementations that can be used for dynamic models. The student is able to apply this knowledge and understanding to: build dynamic models based on a textual description of a process in a domain (e.g. psychology); integrate a dynamic model in an intelligent system to derive conclusions about the state of the environment and/or user; integrate a dynamic model in an intelligent system to decide on relevant actions. The student is able to make judgments about: the appropriate representation for a dynamic model; the validity of a dynamic model based on simulation results; the ethical application of behaviour support systems. The student has acquired communication skills to: report in a scientific and precise manner about the design and the evaluation of a dynamic model. The student has acquired learning skills to: read and interpret semi-scientific texts from other domains (e.g. psychology, sociology).

Course Content

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 7-week bachelor course, the students will learn how to develop dynamic models based on descriptions of processes related to human functioning. The course considers methodological aspects of modelling, such as: the collection and specification of relevant knowledge, the specification of the model, the definition of simulation experiments and the validation of the results obtained from the modelling process. In addition, a methodology will be taught on how to use such dynamic models as basis for intelligent, human-centered systems that interprets and supports human behaviour. 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 do weekly assignments based on lectures and construct models. The models are implemented in Excel and later in Python.

Teaching Methods

Lectures and practical sessions.

Method of Assessment

Group assignments (in total 50% of the grade) and an individual final exam (50% of the grade). Both elements should be graded with at least a 5.5. There is a resit for the exam. At most one assignment can be redone if the average of the assignments is below 5.5.

Literature

A reader is available via Canvas.

Target Audience

Bachelor Artificial Intelligence (year 1)

Recommended background knowledge

Python programming.
Academic year1/09/2431/08/25
Course level6.00 EC

Language of Tuition

  • English

Study type

  • Premaster
  • Bachelor