In light of the new tools for researchers to conduct and communicate their research, we organized a workshop to discuss essential elements for a researcher in 2019. Morning session speakers (Dr. Franck Ramus, Élodie Chabrol, and Judith Lenglet) will advise researchers on how to communicate their research to their peers and the general public (e.g. blogs, twitter, graphical presentation), while afternoon speakers (Dr. Guillaume Dumas, Georgia Loukatou, Sacha Altay, and Dr. Camila Scaff) will showcase crucial tools (e.g.

Pour rencontrer Ingrid Johnsrude, merci de contacter Daniel Pressnitzer : daniel.pressnitzer@gmail.com.

Pour rencontrer Coren Apicella, merci de contacter Nicolas Baumard : nbaumard@gmail.com.

Pour rencontrer Catherine Hobaiter, merci de contacter Philippe Schlenker : philippe.schlenker@gmail.com

Pour rencontrer Stephen Fleming, merci de contacter Catherine Tallon-Baudry: catherine.tallon-baudry@ens.fr.

The brain and cognitive sciences are hard at work on a great scientific quest — to reverse engineer the human mind and its intelligent behavior. Yet these field are still in their infancy. Not surprisingly, forward engineering approaches that aim to emulate human intelligence (HI) in artificial systems (AI) are also still in their infancy.

Western history of thought abounds with claims that knowledge is valued and sought. Yet people often choose not to know. We call the conscious choice not to seek or use knowledge (or information) deliberate ignorance. Using examples from a wide range of domains, we demonstrate that deliberate ignorance has important functions. We systematize types of deliberate ignorance, describe their functions, discuss their normative desirability, and consider how they can be modeled. We conclude that the desire not to know is no anomaly.

Modern theories of reinforcement learning posit two systems competing for control of behavior: a "model-free" or "habitual" system that learns cached state-action values, and a "model-based" or  "goal-directed" system that learns a world model which is then used to plan actions. I will argue that humans can adaptively invoke model-based computation when its benefits outweigh its costs. A simple meta-control learning rule can capture the dynamics of this cost-benefit analysis. Neuroimaging evidence points to the role of cognitive control regions in this computation.

La maladie de Huntington (MH), maladie neurodégénérative génétique due à l’atrophie du striatum, se déclare vers 40 ans. Même si les patients ont des troubles du langage, le rôle du striatum dans le langage est débattu. En effet, les tests de langage impliquent une composante décisionnelle, déficitaire dans la MH. J’ai étudié la MH pour spécifier le rôle du striatum dans l’interaction langage–prise de décision et comprendre les mécanismes de compensation qui retardent l’apparition des déficits.

Organisée par Yves Laszlo et Nicolas Baumard.

Cette journée de rencontre vise à promouvoir la collaboration scientifique entre départements et à créer de nouveaux projets interdisciplinaires.

9:30 INTRODUCTION - Yves Laszlo

9:45 COMPUTER SCIENCE
With presentations of collaborations with Biology and Cognitive Sciences

9:45 ‘Recent advances in machine learning’ Francis Bach