Outline
This module will introduce practical computational techniques used for modelling dynamic and
complex systems in MATLAB. The concepts of dynamic and complex systems, especially complex
biological systems will be introduced. We will then introduce two main computational modelling
techniques for modelling dynamic and complex systems: (1) equation-based and (2) agent-based
modelling techniques. By using examples drawn from real-world dynamic and complex systems,
especially complex biological systems, students will explore and understand both modelling
techniques, in particular their underlying assumptions and limitations and how to apply them
appropriately to model dynamic and complex systems. Methods for analysing computational models,
e.g., phase plan analysis and statistical methods will be introduced. Students will learn how to use
MATLAB to construct computation models based on the two modelling techniques to simulate
complex systems such as predator-prey interaction and animal swarms. Students will also be
introduced to the advanced MATLAB toolboxes such as Systems Biology Toolbox, and will use them
to model complex biological systems.
Aims
The aims of this module are to:

Introduce computational techniques for modelling dynamic and complex systems

Demonstrate how to use MATLAB to construct computational models to simulate dynamic and
complex systems

Gain practical experience of modelling dynamic and complex systems using MATLAB
Learning Outcomes
On successful completion of this module, the student should be able
to:
Assessed by:
1
Understand the general principle and procedure of
computational modelling.
Examination
2
Understand equation-based and agent-based modelling
techniques. Know their advantages and disadvantages
Examination
3
Select an appropriate modelling technique for modelling a
dynamic or complex system such as animal swarms. Be
able to explain the underlying assumptions and limitations
Examination, Continuous
Assessment
4
Use methods such as Phase Plane Analysis and statistical
techniques to analyse equation-based and agent-based
models
Examination, Continuous
Assessment
5
Implement these models using MATLAB. Be able to use
advanced MATLAB programming skills e.g., verctorisation
to write efficient code,
Examination, Continuous
Assessment
6
Apply appropriate MATLAB toolboxes such as Systems
Biology Toolbox to model complex systems as appropriate
Continuous Assessment
Detailed Syllabus
1. Introduction to dynamic systems modelling (2 hours)
2. Brief Introduction to MATLAB programming (2 hours)
3. Equation-based modelling techniques (10 hours)
4. Agent-based modelling techniques (5 hours)
5. Introduction to MATLAB modelling toolboxes (1 hour)
6. Methods for analysing computational models (2 hours)