CSCU9YM - Modelling for Complex Systems


Dr. Savi Maharaj (course coordinator)
Dr. Carron Shankland


MAT911; CSC9V4

Learning outcomes

Students will acquire the following:

  • The ability to analyse and decompose a problem in terms of agents, states, and activities.
  • The ability to create an abstract computational model of a system using agent-based modelling techniques.
  • The skills to use a range of analysis and simulation tools to investigate the behaviour of a model.


  • Introduction to complex systems as distributed networks of interacting, autonomous components exhibiting self-organisation and emergent behaviour.
  • Examples of complex systems drawn from Computing, Biology, and the Social Sciences.
  • Agent-based spatial modelling of complex systems using NetLogo.
  • Analysis of systems via stochastic simulation and simple statistical techniques.
  • Species/activity based modelling of systems using BioPEPA.
  • Use of BioPEPA tools to investigate systems through time-series analysis, derivation of ordinary differential equations, inference of invariants, and model-checking.


In order to obtain a pass grade for the module you must:

  • Submit all items of assessed coursework

Non-submission of any single item of assessed coursework will result in the award of no grade for the module as a whole. This rule (regarding coursework) may be relaxed for students who can show good cause for failure to submit. Good cause may include illness (for which a medical certificate or other evidence will be required).


  • NetLogo modelling assignment (50%)
  • Quantitative modelling assignment (40%)
  • Practical checkpoints (10%)


Further information and teaching materials for this module.

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