Exploration of Force Transition in Stability Operations Using Multi- Agent Simulation

摘要

Stability Operations have become the most prevalent mission for U.S. forces in the current global security environment. This research explores new methods to assist in determining when it is acceptable to downsize a force in a stability operation. The methodology developed provides insight into the problem by quantifying force protection risk, mission failure risk, and time in the context of the operational threat environment. The Pythagoras Multi-Agent Simulation and Data Farming techniques are used to investigate force-level comparisons in a theoretical threat continuum based on a peacekeeping scenario similar to the Bosnian operation. The data from the simulation is used to construct simple tools for decision makers. These tools are used collectively to find the balance, according to a commander's priorities, between the conflicting issues of force protection, mission success, and time. Two areas are identified as significant in achieving success in a stability operation. They are troop posturing and troop employment. The problem is that they are often overlooked or under emphasized. The results of this research demonstrate that posturing and employment should be considered as factors equal to force size in contributing to the goal of maximizing force presence. In addition, the research provides a vehicle to assist military planners with ways in which a stability force can maximize and maintain near continuous presence, while simultaneously minimizing the risk to the force and adhering to operational timelines. Overall, the important conclusion is the significance of troop posture on force size transitions. As a force is downsized, it is crucial to evaluate how to maintain presence with the smaller force. This is evident by the surprising success achieved by the smallest force in the simulation. It was able to project a greater presence by utilizing small dispersed units, much like the Combined Action Platoons in Vietnam.