Quantum-like modeling: cognition, decision making, and rationality

Andrei Khrennikov
2020 Mind & Society  
Recent years were characterized by the real explosion of interest to applications of quantum measurement theory and other parts of quantum formalism outside of physics, especially in psychology, decision making, economics, finances, and social science (as well as in genetics and molecular biology), see, e.g., monographs (Khrennikov 2004 (Khrennikov , 2010 Busemeyer and Bruza 2012; Haven 2013; Asano et al. 2015 ; Bagarello 2019; Schade 2019). Quantum-like models reflect those specialties of
more » ... tive information processing which match well with the quantum formalism. We emphasize that the strategy of quantum-like modeling does not assume that the whole body of quantum theory should be explored. The quantum-like representation of mental states and (self-)observations is operational. It does not provide the complete picture of cognitive processes including functioning of neuronal networks in the brain. In principle, one can search for finer models, so to say prequantum models, and couple such models with the quantum operational description. The main distinguishing feature of quantum-like modeling is exploring quantum probability theory, the calculus of complex probability amplitudes. As was shown by the author (Khrennikov 2004 (Khrennikov , 2010 , one of the consequences of this calculus is modification of the formula of total probability. The classical formula, for two observables A and B (represented by random variables on the Kolmogorov probability) space has the form: Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
doi:10.1007/s11299-020-00240-6 fatcat:vv4ujx5xuzdvldkahhsjalfhw4