Dynamic modeling for decision-making process based on the Bayesian theory

Decision-making is a complicated process, which takes on uncertainty and complexity. Bayesian Networks (BNs) provide a framework for decision-making in which to deal with the problems combining the experts´ knowledge structure and specific data; and Influence Diagrams can be used to analysis the feasibility of some decisions as the extension of BNs. Furthermore, in order to decrease the amount of assigned conditional probabilities and introduce the concept of time-varying, Dynamic Influence Networks is proposed to be used as a new method of knowledge elicitation.