Predictive Modeling of Human Behavior: A Quantum-Inspired Approach

Mohanraj Muralidharan

Abstract: Understanding and predicting human behavior remains a complex challenge across scientific disciplines. This study explores a quantum-inspired approach to behavioral modeling, drawing on analogies from quantum mechanics to identify potential underlying patterns in human actions. Key parallels include the spatial distribution of individuals analogous to electron orbitals, the dual nature of behavior at individual and group levels resembling wave-particle duality, and the aggregation of collective decisions reflecting quantum wave function collapse. By integrating concepts from quantum cognition and quantum decision theory, this work examines the theoretical foundations, modeling techniques, and limitations of applying quantum analogies to behavioral prediction. The findings suggest that quantum-inspired models may.

Keywords: Quantum Cognition, Human Behavior Modeling, Quantum Decision Theory, Collective Decision-Making, Behavioral Prediction, Wave Function Collapse, P vs NP