INF-34806 Agent-Based Modelling of Complex Adaptive Systems (previously INF-50806)

Nobody wants disease or war. Why do events happen in society, or in biology, without anyone being in control? This is called emergent behaviour. It is the result of the combined actions of independent people, plants or animals in an environment. Would you like to model emergent behaviour and run your own models, do sensitivity analysis on them and validate them? Then this course is for you.

Emergent behaviour occurs among animals when they form flocks or plagues, among people when they form riots or queues. The emergent system can be modelled by looking at what drives the agents: rewards, punishments. The simulation model will let these agents interact and generate emergent behaviour.

The course is for social and biological scientists alike, PhD or MSc. You can simulate the possible effects of policy measures, marketing campaigns, social media hypes, disease outbreaks, xenophobia, social network structure, social learning. If your focus is on ecosystems you can simulate the effect of genetic mutation rate, diversity, growth rates, predation.

In simulating emergence, you consider the system under study as a complex adaptive system. It is complex if the relation of output variables to input variables is in between chaos and linearity. It is adaptive if the agents in the system have some awareness about the system state and can adapt their behaviour accordingly. This leads to a multi-level approach in which both the detail level of the agent, and the overall level of the system, are important. This perspective opens new opportunities of linking disciplines in research.

Note: In academic year 2020 - 2021 we offer this course in period 4.