This short workshop is intended to introduce agent-based modeling and kickstart working with NetLogo. In the first part we will discuss why one would use ABM’s as a theoretical tool to understand democratic debate. In the second part, we will get you started with NetLogo, a very intuitive and easy tool to program simple ABMs. We explain the basics of NetLogo and show some simple and some more advanced code.
Today, we…
Diffusion model of innovation:
Some other NetLogo models:
Very useful in your NetLogo endeavors:
On actor-based thinking:
On the relation between ABM and CSS:
A more practical guide to starting with ABM:
If you want, you can do this little exercise to get your hands dirty with NetLogo coding.
For the hands-on part of the session, we looked at a simple alternative to Everett Rogers’ theory about the diffusion of innovation from a complexity perspective. Rogers argued that the often observed S-curve in the adoption of innovations is due to differences in individual tendencies to adopt an innovation. Assuming that (1) such a tendency is normally distributed in a population, and (2) people are aware of the number of others that have adopted the innovation, reveals the non-linear relationship between time and share of the population that adopted some innovation.
Alternatively, Agent-Based Modeling can offer a competing explanation that relies on network structure, but does not make assumptions about individual differences, nor assumes that people have complete information about the state of the world.