Description du projet
Examiner la capacité de l’humain à comprendre les actions d’autrui
Malgré les progrès considérables des neurosciences cognitives et des disciplines connexes, il n’existe pas de modèle plausible sur le plan informatique et neurobiologique de l’interprétation par l’humain du comportement d’autrui. Le projet TrackingMinds, financé par l’UE, mettra en œuvre une approche multimodale et mathématiquement précise pour faire la lumière sur la capacité mentale de l’humain à suivre l’esprit de son semblable et à déduire ses croyances et préférences cachées. TrackingMinds se concentrera sur la façon dont nous observons les autres ainsi que sur la façon dont nous prévoyons et apprenons de leurs décisions. Le projet veut également contribuer au développement de meilleurs systèmes d’intelligence artificielle interactifs, de prédictions d’équilibre en théorie économique et même d’approches innovantes contre les déficiences sociales dans les troubles mentaux.
Objectif
A core research question in cognitive neuroscience and many other disciplines is to understand how humans interpret the behavior of others. Despite the plethora of empirical work on human Theory of Mind, we still lack a computationally and neurobiologically plausible model. The goal of the current project is to fill this gap by leveraging our extensive knowledge of decision making, which has been formalized as a process of evidence accumulation. Thus, my central hypothesis is that humans utilize their own evidence-accumulation machinery to track others’ minds and to infer their hidden beliefs and preferences. Importantly, my theory goes far beyond previous accounts (e.g. the mirror neuron system), as it specifies not only how we observe others, but also how we predict and learn from their decisions.
I will subject this hypothesis to a series of studies that test its behavioral, physiological and neurobiological implications. Thereto, I will employ cutting-edge cognitive neuroscience tools, including cognitive modeling, eye tracking, functional magnetic resonance imaging, and electroencephalography (EEG). Moreover, I will use EEG hyperscanning to probe the synchronization of brain signals related to evidence accumulation in interacting people. Finally, I will develop a multi-agent artificial intelligence (AI) system that can infer the hidden beliefs of other agents on the basis of their decision processes. I will then show that this AI system provides superior performance in coordinating its actions with human partners.
The multi-modal and mathematically rigorous approach of TrackingMinds will advance our understanding of human mentalizing abilities profoundly. Thereby, it will stimulate further research and applications. First, it can help to devise better interactive AI systems. Second, it has strong implications for equilibrium predictions in economic theory. Third, it can foster new interventions of social mental disorders such as autism and social anxiety.
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ERC-STG - Starting GrantInstitution d’accueil
20148 Hamburg
Allemagne