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Optimistic reinforcement learning: computational and neural bases

G. Lefebvre, M. Lebreton, F. Meyniel, S. Bourgeois-Gironde, S. Palminteri
doi: https://doi.org/10.1101/038778
G. Lefebvre
aLaboratoire de Neurosciences Cognitives (LNC), INSERM U960, Ecole Normale Supérieure, 75005, Paris, France
bLaboratoire d'Économie Mathématique et de Microéconomie Appliquée (LEMMA), Université Panthéon-Assas, 75006, Paris, France
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M. Lebreton
cAmsterdam Brain and Cognition (ABC), Nieuwe Achtergracht 129, 1018 WS Amsterdam, the Netherlands
dAmsterdam School of Economics (ASE), Faculty of Economics and Business (FEB), Roetersstraat 11, 1018 WB Amsterdam, the Netherlands
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F. Meyniel
eCognitive Neuroimaging Unit, CEA, INSERM, Université Paris-Sud, Université, Paris-Saclay, NeuroSpin center, 91191 Gif/Yvette, France
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S. Bourgeois-Gironde
bLaboratoire d'Économie Mathématique et de Microéconomie Appliquée (LEMMA), Université Panthéon-Assas, 75006, Paris, France
fInstitut Jean-Nicod (IJN), CNRS UMR 8129; Ecole Normale Supérieure, 75005, Paris, France
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S. Palminteri
aLaboratoire de Neurosciences Cognitives (LNC), INSERM U960, Ecole Normale Supérieure, 75005, Paris, France
gInstitute of Cognitive Neurosciences (ICN), University College London, WC1N 3AR London, UK
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Posted October 03, 2016.
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Optimistic reinforcement learning: computational and neural bases
G. Lefebvre, M. Lebreton, F. Meyniel, S. Bourgeois-Gironde, S. Palminteri
bioRxiv 038778; doi: https://doi.org/10.1101/038778
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Optimistic reinforcement learning: computational and neural bases
G. Lefebvre, M. Lebreton, F. Meyniel, S. Bourgeois-Gironde, S. Palminteri
bioRxiv 038778; doi: https://doi.org/10.1101/038778

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