The climate crisis can be mitigated if we choose more climate friendly. This is by no means easy as choices are not only affected by intentions, but also by outcomes of these choices.

That is, the choice between flying to Ibiza (climate unfriendly) or taking the bus to Amsterdam beach (climate friendly) can be conceptualized as a reinforcement learning process, in which the outcomes of a choice, e.g. good weather in Ibiza or bad weather in Amsterdam, may weaken a climate-friendly intention.  The issue here is that typically only short-term outcomes are experienced, and not the future long-term ones (e.g. fires, floods etc.).

In this project we will investigate the effect of a so-called “futuring intervention”. In futuring, the  future outcomes are made vivid, which is expected to strengthen climate friendly intentions. The effects of the intervention will be studied in a reinforcement learning paradigm, which will be analyzed by developing a computational model (either in Python or R).

What you will learn: reading literature, designing study and writing a pre-registration, obtaining ethical approval, developing and implementing a futuring-based reinforcement learning task, computational modeling, writing a report and presenting your project. You are likely to work in a team of students, so you also learn to cooperate!

for further info: please contact prof. dr Hilde Huizenga: h.m.huizenga@uva.nl