Acquisition Decision Support with Monterey Phoenix
Abstract
The number of possibilities that can arise from complex system behaviors and interactions is regularly underestimated by approaches and tools that are biased towards the capture of known and wanted behaviors. This research tests a new methodology for exposing and controlling unknown and unwanted behaviors using Monterey Phoenix models, and then assesses risk of events and event traces as an example analysis that informs acquisition decisions. A summer internship activity was conducted to guide the development of source data for this research based on behavior models of a competition known as Aquaticus. The new emergent behavior analysis methodology is applied to provide a set of validated scenarios to inform risk analysis. An initial model contained two traces showing unexpected game rule violations, which were corrected in a final model containing eight traces of valid potential behavior possibilities for the blue team, red team, and environment. Risk factors were then computed for each trace to inform overall risk statistics across the entire model, including a total risk (sum of all trace risk factors), a maximum risk, and an average risk across all eight traces. This methodology provides the first rigorous and systematic search pattern for unknown unknown behaviors supported by automated tools. It increases awareness and understanding of emergent behaviors within and among systems and the environment.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 2022
- Accession Number
- AD1189487
Entities
People
- Kristin Giammarco
- Pamela Dyer
Organizations
- Naval Postgraduate School