Seminar/Thesis: Agent Simulators for Individual Behaviour

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Agent-based models can be used to simulate population behaviour. Using the simulated behaviours, we can analyse the different components that affect the spread of infections. Our current experience with the pandemic has shown that different regions might have a different response to similar intervention strategies. Using the simulator, we can study the social, cultural, and geographic factors that affect the efficiency of various interventions. More importantly, we can evaluate the economic and social impacts of the selected intervention strategies.


Implement agent behaviours for public and private spaces and evaluate effects on the population in terms of space utilisation, the number of isolations, and the duration of infection wave.

Learning Objectives

  • Gain an overview of dynamic system modelling.
  • Explore and understand the features of human behaviour in public places
  • Apply particle modelling to analyse infection propagation.
  • Create simulator modules to model people behaviour in public and private space scenarios.

Course Data

Project typeSeminar/Thesis
PeriodWinter Semester 2021/22
Presence timeVirtual seminar, working from remote
Useful knowledgePython, data analytics
Work distribution40% algorithm development, 30% data analysis and evaluation, 20% consultation, 10% reporting
Med. Eng. designationAdvanced Context Recognition (ACR)
StudOn linkComing soon
First meetingComing soon
RegistrationVia StudOn, obligatory after introduction.


Up-to-date literature recommendations are provided during the lectures.


  • Final project presentation, demonstrator and final report.


Dr. Luis I. Lopera G.

  • Job title: Researcher
  • Address:
    Henkestraße 91, Haus 7, 1. OG
    91052 Erlangen
  • Phone number: +49 9131 85-23605
  • Email:
Friedrich-Alexander-Universität Erlangen-Nürnberg