Swiss Computational Neuroscience Series in CMU, Geneva - LCN


Thursday, November 3rd, CMU-GENEVA, 17h00

Peter DAYAN, Gatsby Computational Neuroscience Unit, University College London (homepage)

Interactions between Model-free and Model-based Reinforcement Learnin

Abstract:

Substantial recent work has explored multiple mechanisms of decision-making in humans and other animals. Functionally and anatomically distinct modules have been identified, and their individual properties have been examined using intricate behavioural and neural tools. I will discuss the background of these studies, and show fMRI results that suggest closer and more complex interactions between the mechanisms than originally conceived. In some circumstances, model-free methods seize control after much less experience than would seem normative; in others, temporal difference prediction errors, which are epiphenomenal for the model-based system, are nevertheless present and apparently effective. Finally, I will show that model-free and model-based methods on occasion both cower in the face of Pavlovian influences, and will try and reconcile this as a form of robust control.