A main focus of my research is to examine the cognitive and computational principles of human learning and decision making. When and why do people abandon their habitual choices to gain new experiences? How do they generalize their prior experiences to make inferences and informed decisions in novel situations? The goal of my research is to understand (1) how people interact with their environment in order to acquire knowledge about it, (2) how this knowledge is structured and adapted to an ever-changing world, and (3) how this knowledge is used to make better inferences and decisions. I approach these topics with a combination of mathematical modelling and behavioural experiments. I use Bayesian reinforcement learning as a mathematical framework to understand learning and decision making at the cognitive, behavioural and neural level. My research lies on the intersection of psychology and AI, and is characterised by a synergy between theoretical and methodological development.