An implicit model development process for bounding external, seemingly intangible/non-quantifiable factors

Abstract

This research expands the modeling and simulation (M&S) body of knowledge through the development of an Implicit Model Development Process (IMDP). When augmented to traditional Model Development Processes (MDP), the IMDP enables the development of models that can address a broader array of effects than previously possible, giving users the flexibility to explore hard-to-model factors like space and cyber while gaining insight into their potential impacts on operational effectiveness. Specifically, the IMDP provides a formalized methodology for developing an improved model definition, where a broader, more holistic approach of defining a model's referent is achieved. Next, the IMDP codifies the process for implementing the improved model definition within the operational model. This work serves as a proof of concept for the development of operational models that can account for and quantify External, Seemingly Intangible/Non-Quantifiable (ESINQ) factors and effects, and provides M&S users a new tool for addressing ESINQ and other soft factors that do not fit well into traditional MDPs. Finally, through the application of ESINQ-enabled meta-models, this work demonstrates how the improved understanding generated by the IMDP can be used to improve a set of operational and acquisitions decision support tools.