Abstract
Human decision making affects all aspects of engineering practice and has been extensively studied in the literature. However, it has been observed that our decision-making behavior is not properly modeled using classical probability techniques. Consequently, alternative models have been explored with varying degrees of success. One of these approaches is based on using the mathematics of quantum mechanics to model human decisions, which has successfully explained paradoxes such as Ellsberg paradox, question order effect and violation of the law of total probability. In this paper, we explore the use of Open Quantum Systems to model decision making and propose their use in engineering decision making modeling and prediction. It is also proposed that such models can be better parameterized by analyzing associated brain activity using Magnetoencephalography (MEG). We select MEG as the imaging method of choice as it provides multiple advantages over widely used techniques of EEG and fMRI. The paper provides a framework for possible experiments that can be conducted to investigate the dynamics. We provide preliminary data on how this can be accomplished in practice and provide avenues for future research in this area.
