Behavioural and Neural Characterization of Optimistic Reinforcement Learning

Posted: 11 Oct 2017

See all articles by Sacha Bourgeois-Gironde

Sacha Bourgeois-Gironde

École Normale Supérieure (ENS); Université Paris II

Date Written: July 10, 2017


When forming and updating beliefs about future life outcomes, people tend to consider good news and to disregard bad news. This tendency is assumed to support the optimism bias. Whether this learning bias is specific to ‘high-level’ abstract belief update or a particular expression of a more general ‘low-level’ reinforcement learning process is unknown. Here we report evidence in favour of the second hypothesis. In a simple instrumental learning task, participants incorporated better-than-expected outcomes at a higher rate than worse-than-expected ones. In addition, functional imaging indicated that inter-individual difference in the expression of optimistic update corresponds to enhanced prediction error signalling in the reward circuitry. Our results constitute a step towards the understanding of the genesis of optimism bias at the neurocomputational level.

Keywords: Human Behavior, Learning Algorithms, Reward

JEL Classification: D87, D89

Suggested Citation

Bourgeois-Gironde, Sacha, Behavioural and Neural Characterization of Optimistic Reinforcement Learning (July 10, 2017). Available at SSRN:

Sacha Bourgeois-Gironde (Contact Author)

École Normale Supérieure (ENS) ( email )

45 rue d’Ulm
Paris Cedex 05, F-75230

Université Paris II ( email )

12 place du Pantheon
Paris cedex 06, 75231

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
PlumX Metrics