Nowadays, AI is used in almost every corner of society. For a long time, choice behaviour analysis was considered the exclusive domain of theory-driven (parametric) methods, in particular discrete choice models (founded in micro-economic theory). Recently this has changed. Thrilling new AI methods are being developed to obtain deeper behavioural insights on choice behaviour. These methods can complement and extend the theory-driven tools of choice behaviour researchers as they typically are:
(1) More flexible & (2) Less restrictive in terms of data types.
Researchers at AI4ChoiceLab aim to bridge the gap between data-driven AI methods and theory-driven discrete choice methods, for better understanding human choice behaviour.