Extending GeNIe for building graphical decision-theoretic models
Yunfei Ge, Lihua Zhou, Shengmin Cui, Ming Yang · 2013
The influence diagram is a graph model for solving complex decision problems based on uncertain information. In order to deal with various decision problems, many new types of influence diagram have been developed. In this paper, we extend GeNIe, a development environment for building graphical decision-theoretic models, by using the library of functions (SMILE) for graphical probabilistic and decision-theoretic models, and thus GeNIe can model and evaluate the qualitative influence diagram with weights and the influence diagram with interval parameters.