Seminar/Thesis: Agent Simulators for Individual Behaviour
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.
- 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.
|Period||Winter Semester 2021/22|
|Presence time||Virtual seminar, working from remote|
|Useful knowledge||Python, data analytics|
|Work distribution||40% algorithm development, 30% data analysis and evaluation, 20% consultation, 10% reporting|
|Med. Eng. designation||Advanced Context Recognition (ACR)|
|StudOn link||Coming soon|
|First meeting||Coming soon|
|Registration||Via StudOn, obligatory after introduction.|
Up-to-date literature recommendations are provided during the lectures.
- Final project presentation, demonstrator and final report.