Development and Application of a Rapid Military Model Development Framework
Abstract
Military operations are complex systems composed of the interactions of many smaller discrete systems, or assets: watercraft, troops, etc. Historically, requirements for new assets have been created based on standalone optimization. It is not just necessary to optimize requirements for a single scenario, but the requirements that will benefit the entire military operation as a whole in different scenarios. To capture all of the interactions and develop a complete understanding of the overall system, it is necessary to model both combat and logistics, which have traditionally been modeled and analyzed separately. To characterize military operations and assets, it is necessary to move beyond the traditional models that use aggregated approximations for combat and stand alone nodal analysis for logistics to a framework which captures the complex interaction between combat and logistics while allowing a large number of automated cases and scenarios to run with no human in the loop. The framework this paper discusses was created to facilitate the making of models to analyze and characterize military operations and the effects that future assets will have on entire operations. The framework is agent-based, allowing bottom up definition and the gathering of emergent behavior, and uses the beliefs, desires, and intentions (BDI) agent model. Modeling of communication and BDI creates myopic agents constrained by the information they can obtain, process, and react to. The framework is first depicted and then validated by the creation of a model defining requirements for a future asset, the Transformable Craft. The creation and testing of the model prove that the requirements for the framework have been met. The potential applications ranges from data-farming military operations models for future asset requirement, characterizing military operations systems, and providing a stepping stone for future agent-based military operations modeling and simulation work.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 2010
- Accession Number
- ADA534783
Entities
People
- Nelson Andriano
Organizations
- Georgia Tech