Agent Based Modelling for the social sciences
Agent-based models (ABMs) are computational simulations suitable to systematically experiment with, and analyse, interactions and processes in complex systems. ABMs have been used in many disciplines,
within and beyond social sciences, with applications in archeology, biology, ecology, geography, economics and computational sciences. ABMs allow for flexible and unambiguous representations of the behavioural plus environmental heterogeneity observed in different agent populations and to simulate experimental scenarios of interest. This approach can be used to investigate output at the individual-level and at the system-level, including emergent properties arising from agent’s interactions with each other and their environment.
The seminar will be focused on the following topics: (I) how ABMs can generate new knowledge and (II) how qualitative data can be used to inform behavioural rules in ABMs. A short practical session
using the NetLogo ABM platform will be integrated in the seminar, so we encourage attendants to bring a laptop with the following software installed: