Technical, economic, regulatory, environmental, and social political interests make the process of selecting an appropriate wastewater treatment technology complex. Although this problem has already been addressed from dimensioning approach, our proposal in research, a model decision making for conventional secondary municipal through continuous-discrete, non-parametric Bayesian networks was de...

Emergency decision making is still an important issue in unconventional emergency management research. Although many studies have been written on this topic, they remain political and qualitative, and it is difficult to make them operational in practice. Therefore, this article proposes a decision-theoretic rough set over two universes as an approach for solving this difficulty. The proposed ap...

Probabilistic models of decision making under various forms of uncertainty have been applied in recent years to numerous behavioral and model-based fMRI studies. These studies were highly successful in enabling a better understanding of behavior and delineating the functional properties of brain areas involved in decision making under uncertainty. However, as different studies considered differ...

Bayesian implementation concerns decision making problems when agents have incomplete information. This paper proposes that the traditional sufficient conditions for Bayesian implementation shall be amended by virtue of a quantum Bayesian mechanism. In addition, by using an algorithmic Bayesian mechanism, this amendment holds in the macro world. More importantly, we find that the revelation pri...

Perceptual decision making can be described as a process of accumulating evidence to a bound which has been formalized within drift-diffusion models (DDMs). Recently, an equivalent Bayesian model has been proposed. In contrast to standard DDMs, this Bayesian model directly links information in the stimulus to the decision process. Here, we extend this Bayesian model further and allow inter-tria...