Quantum reinforcement learning during human decision-making

• Published in: Nature human behaviour Vol. 4; no. 3; pp. 294 - 307
• Main Authors: Li, Ji-An, Dong, Daoyi, Wei, Zhengde, Liu, Ying, Pan, Yu, Nori, Franco, Zhang, Xiaochu
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.03.2020; Nature Publishing Group
• Subjects: 59/36; 631/378/2649/1409; 639/766/483/640; Adult; Applied psychology; Behavioral Sciences; Biomedical and Life Sciences; Brain Mapping; Cigarette Smoking - physiopathology; Cognition; Cortex; Decision making; Decision Making - physiology; Executive Function - physiology; Experimental Psychology; Functional magnetic resonance imaging; Gambling; Humans; Learning; Life Sciences; Magnetic Resonance Imaging; Microeconomics; Models, Theoretical; Neurosciences; Personality and Social Psychology; Prefrontal Cortex - diagnostic imaging; Prefrontal Cortex - physiology; Prefrontal Cortex - physiopathology; Quantum Theory; Reinforcement; Reinforcement, Psychology; Smoking
• ISSN: 2397-3374; 2397-3374
• DOI: 10.1038/s41562-019-0804-2

Classical reinforcement learning (CRL) has been widely applied in neuroscience and psychology; however, quantum reinforcement learning (QRL), which shows superior performance in computer simulations, has never been empirically tested on human decision-making. Moreover, all current successful quantum models for human cognition lack connections to neuroscience. Here we studied whether QRL can properly explain value-based decision-making. We compared 2 QRL and 12 CRL models by using behavioural and functional magnetic resonance imaging data from healthy and cigarette-smoking subjects performing the Iowa Gambling Task. In all groups, the QRL models performed well when compared with the best CRL models and further revealed the representation of quantum-like internal-state-related variables in the medial frontal gyrus in both healthy subjects and smokers, suggesting that value-based decision-making can be illustrated by QRL at both the behavioural and neural levels. Li et al. show that human value-based decision-making can be modelled using the quantum reinforcement learning framework. These new models reveal the importance of the medial frontal cortex in this quantum-like decision-making process.