New trends in decision-making: modeling learning from robotics to economics

 Organizers:

Stefano palminteri (Laboratoire de Neurosciences Cognitives & Inserm  - stefano.palminteri@ens.fr )
Sacha Bourgeois Gironde (Institut Jean Nicod & Université Paris 2 - sbgironde@gmail.com )

March 23, 2018

Program:

9:15
Stefano Palminteri & Sacha Bourgeois-Gironde
Forewords

9:30-10:00
Kerstin Preuschoff (Geneva Finance Research Institute)
Uncertainty and surprise in decision-making and learning

10:15-10:45
Philippe Jehiel (Paris School of Economics)
Some thoughts on learning through categories

11:00-11:30
Mehdi Khamassi (Institut des Systèmes Intelligents et de Robotique)
Is it efficient to perform meta-learning with social rewards the same way as with non-social ones? Insights from robotics experiments

11:45-12:15
Ido Erev (Techion - Israel Institute of Technology)
Anomalies, forecasts, and decision research during the big data revolution
Behavioral decision research highlights interesting choice anomalies, and proposes elegant cognitive models that can explain these phenomena. Yet, it is often easier to predict behavior with theory-free machine learning tools than with the leading cognitive models.  One reason for the difficulty in deriving general predictions using cognitive models is that different models are often proposed to explain different phenomena. It is then unclear which model to use to address a new task. The current talk reviews recent research and describes a new choice prediction competition project that try to address this problem (see https://cpc18.wordpress.com).  

12:30
End