Objectif The combination of empirical testing with computational modeling is the most promising path in neuroscience of decision-making. Nonetheless, neuro-computational models of decision-making are still affected by two main limitations. First, computer simulations, typically used for testing neural models, represent the environment in a very simplistic way, exposing the computational models to “toy problems”. Second, computational neuroscience often neglects that bodily processes do not simply “execute” what is decided centrally, but are part of cognitive processing itself (embodied cognition). The main goal of this project is to solve these two limitations and to open a new path in cognitive and computational neuroscience of decision-making. We plan the embodiment in a humanoid robotic platform (iCub) of a novel neuro-computational model, representing the state of the art in modeling neurobiology of decision-making. This neural model, the Reinforcement Meta-Learner (RML), generates emergent (i.e. homunculus-free) cognitive control signals and supports learning to solve complex decision problems by self-regulating its internal parameters (meta-learning). In simplified and disembodied computer simulations, the RML already revealed to be exceptionally successful in explaining many different experimental data sets (both neural and behavioural) from different domains. The RML embodiment would represent one of the few cases where a neural model, born completely in the domain of cognitive neuroscience, would be embodied in a humanoid robot. The fusion of cognitive neuroscience and humanoid robotics will allow to investigate the role of embodiment in decision-making in real world problems (contribution to neuroscience), and it also would represent a unique opportunity to test the effectiveness of the RML to be a new way for developing genuinely autonomous decision-making in robots (contribution to robotics). Champ scientifique natural sciencesbiological sciencesneurobiologycognitive neuroscienceengineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringroboticsautonomous robotsnatural sciencesbiological sciencesneurobiologycomputational neurosciencenatural sciencesmathematicsapplied mathematicsmathematical model Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Thème(s) MSCA-IF-2017 - Individual Fellowships Appel à propositions H2020-MSCA-IF-2017 Voir d’autres projets de cet appel Régime de financement MSCA-IF-EF-ST - Standard EF Coordinateur CONSIGLIO NAZIONALE DELLE RICERCHE Contribution nette de l'UE € 168 277,20 Adresse PIAZZALE ALDO MORO 7 00185 Roma Italie Voir sur la carte Région Centro (IT) Lazio Roma Type d’activité Research Organisations Liens Contacter l’organisation Opens in new window Site web Opens in new window Participation aux programmes de R&I de l'UE Opens in new window Réseau de collaboration HORIZON Opens in new window Coût total € 168 277,20