Innovative Uses of Artificial Intelligence and Machine Learning in Scenario Planning and Design

A simulation optimization tool can exploit existing missile defense simulation models to streamline the scenario generation analysis process. OptTek's Phase I project will focus on using a simulation optimization approach to solve the problem of generating a minimal collection of test scenarios, using the minimum number of shared scenario components, that meets a required set of test objectives. Each individual scenario taken through the end to end scenario generation process involves substantial effort including discussion, documentation, and manual scenario generation in high fidelity tools. Likewise, scenario components require a great deal of time and effort to prepare for the test event. We will explore the use of an optimization tool with medium fidelity digital simulation models early in the scenario generation process to minimize the required test scenarios and scenario components. OptTek proposes to enhance previously created scenario generation optimizer software, updating it to work with the current software. Additionally, artificial intelligence (AI) /machine learning (ML) predictors will be created and trained to automatically suggest independent combinations of test objectives in scenarios that will be used to make the scenario generation process more efficient. Finally, to support digital test and assessment, mechanisms for adaptive management of digital tests will be explored that will reduce the number of simulation runs needed to achieve desired assessment results. Approved for Public Release | 21-MDA-11013 (19 Nov 21)