Entry requirements

General entry requirements + English 6. Or: English level 2

Main field

CTDVA Computer Science

Progression level in relation to degree requirements

The course is offered as a standalone course

Course contents

The course aims for students to develop knowledge of agent-based modelling and simulation, including planning and conducting simulation experiments and developing simulation models to study social systems consisting of interactions between individuals, groups, and institutions.
Agent-based modelling simulates human behaviour using intelligent agents, enabling the creation of artificial populations for studying complex phenomena in social systems.
Students are introduced to theoretical and practical aspects including abstraction of real systems, modelling decision-making and actions, data collection, implementation of models, planning and conducting experiments, and analysis and interpretation of results.
Applications include logistics, economics, and social sciences where simulation supports decision-making.

The course consists of the following components:

• Introduction to modelling and simulation
• Discrete-event simulation
• Agent-based modelling
• Modelling and simulation of social systems
• Design of simulation experiments
• Analysis and interpretation of simulation results
• Applications of agent-based modelling and simulation
• Implementation of simulation models

Learning outcomes

Knowledge and understanding

Upon completion of the course, the student shall be able to:

1. describe fundamental concepts of agent-based modelling and simulation

2. explain how such models are used for simulating social systems

Skills and abilities

Upon completion of the course, the student shall be able to:

3. implement agent-based models using simulation frameworks

4. plan and conduct simulation experiments.

Judgement and approach

5. discuss applications of agent-based modelling and simulation

6. evaluate and interpret simulation results

Learning activities

Lectures, laboratory sessions, seminars, project work, and self-study

Assessment

To recieve a Pass:

• Assignments, 4,5 credits (U/G) (Intended Learning Outcomes 1, 2 and 5)
• Project work, 3 credits (U/VG) (Intended Learning Outcomes 3, 4 and 6)

The final grade is based on the project work.

Course literature

Recommended literature:

• Railsback, S. F., & Grimm, V. (2019). Agent-based and individual-based modeling: a practical introduction. Princeton university press.
• Law, A. (2014). Simulation Modeling and Analysis. McGraw Hill.
• Banks, J., Carson, J. S., Nelson, B. L. & Nicol D. M. (2013). Discrete-Event System Simulation. Pearson Education
• Gilbert, N., & Troitzsch, K. (2005). Simulation for the social scientist. McGraw-Hill Education (UK).

In addition to the literature listed above, a collection of scientific articles will be included.

Course evaluation

Malmö University provides students who participate in, or who have completed a course, with the opportunity to express their opinions and describe their experiences of the course by completing a course evaluation administered by the University. The University will compile and summarise the results of course evaluations. The University will also inform participants of the results and any decisions relating to measures taken in response to the course evaluations. The results will be made available to the students (HF 1:14).

Interim rules

If a course is no longer offered, or has undergone significant changes, the students must be offered two opportunities for re-examination based on the syllabus that applied at the time of registration, for a period of one year after the changes have been implemented.

Additional information

If a student has a Learning support decision, the examiner has the right to provide the student with an adapted test, or to allow the student to take the exam in a different format. The syllabus is a translation of a Swedish source text.