Research interests

RESEARCH INTERESTS

My goal is understanding how humans learn to make decisions at the behavioral, computational and neural levels. I am mainly (but not only!) interested in situations when decisions are based on past experience (a.k.a. reinforcement learning) . 

In the last few years I mainly worked two computational hypotheses concerning human reinforcement learning:

1. value is learned in a relative scale

2. value is learned in a biased manner 

In addition to extending the "relative value" and the "learning bias" frameworks, new lines of research in my team investigate social learning , the experience/description gap and, more recently, the intersection between cognitive science and artificial intelligence.  I also enjoy questioning the epistemological and methodological foundations of decision-making, neuroeconomics and cognitive science research. 

In my "spare time", I am writing a book on "decision making" with Valentin Wyart for Oxford University Press (a "very short introduction" that is proving not so quickly written as originally thought...). 

KEY PUBLICATIONS