M2
Internship
Information
LNC2
Laboratory:

LNC2

Team
Human reinforcement learning
Adviser
Stefano Palminteri

The candidate will combine methods from computational modeling, behavioural economics and cognitive sciences to address how humans learn to make value-based decisions. The ideal candidate will have good programming skills. A non-exhaustive lists of specific topics includes: comparing experience-based and description-based decisions: a memory-based account of value-based decision-making; social reinforcement learning. Most internships will implicate an experimental part, however, occasionally, we will consider pure theoretical (simulation-based) projects. 

More information about our research: https://sites.google.com/site/stefanopalminteri/phd-research