Dynamic Modelling for Socially Aware Systems


Course Objective

At the end of the course, the student has knowledge and understanding
of: the Agile development methodology; the terminology that is used in
this methodology and the artifacts that play a role.

The student is able to apply this knowledge and understanding to: work
on a joint project via the agile method in a dynamic environment with
different stakeholders; to integrate dynamic modelling techniques in an
intelligent system to interpret data and/or decide on relevant actions.

The student is able to making judgments about: the amount of work
related to different tasks defined in the project; the priority of tasks
in relation to the resources and the interests of the different

The student has acquired communication skills that are essential to the
Agile methodology: reflection on the collaboration in an open and safe

Course Content

This course challenges students to apply the knowledge that they have
gained in other courses to build a working prototype of an intelligent,
socially-aware system. The system should use some of the techniques that
you have seen in Introduction to Modelling and Simulation (IMS), e.g.
prediction of the effect of actions or assessment of a situation. The
system should use real-world of real time data from the physical
environment as input and generate actual output. The application can
make use of Arduino sensors and actuators. In addition to the dynamical
modelling techniques learned in IMS, you will learn to develop, design
and implement adaptive parameter models.

In this course we adopt an Agile software development approach, under
which requirements and solutions evolve through collaborative effort of
self-organizing and cross-functional teams and their customers / end
users / stakeholders.

Students work in groups of 3 to 4. In the first week, a proposal for the
application has to be made, which will be presented plenary. The further
development of the system is organized in 3 sprints of 2 weeks. In the
first sprint a Minimal Viable Product has to be delivered.

The course consist of a few plenary sessions with lectures, student
presentations, and group exercises with the Agile methodology. In
addition, students can work on their project and get help and support
during a weekly "workshop". The course is concluded with a plenary
presentation of the developed systems.

Teaching Methods

Lectures and practical sessions (workshops). Work in this project is
done in groups of 3 or 4 students.

Method of Assessment

Lab assignments, final reports and a final presentation.
1. Final Project Product Report* 70%
2. Agile Project Management Report* 20%
3. Final Presentation* 10%
*all must be at least 5,5 to pass the course

Entry Requirements

Introduction to Modelling and Simulation.


Online study guide.

Target Audience

B Artificial Intelligence year 2

General Information

Course Code XB_0023
Credits 6 EC
Period P1
Course Level 200
Language of Tuition English
Faculty Faculty of Science
Course Coordinator dr. M.C.A. Klein
Examiner dr. M.C.A. Klein
Teaching Staff dr. M.C.A. Klein

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Computer lab, Lecture
Target audiences

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