Category: Opportunity
DoD Communities Of Interest: Advanced Electronics
Subject : Stratagem: Applying State-of-the-Art AI/ML to Air Battle Management
Due Date: Rolling through Sep 30, 2022
Government Organization: AFRL - Air Force Research Laboratory
Description :
On October 25, the Air Force Research Laboratory posted an updated version of Stratagem: Applying State-of-the-Art Artificial Intelligence and Machine Learning Approaches to Air Battle Management.
AFRL/RI is seeking innovative research to create a capability to develop new Artificial Intelligence-based capabilities that can reason in real-time about developments in the battlespace during wartime engagements and assist planners and decision-makers responsible for reacting to those developments.
As the Air Force begins to operate in contested environments against near-peer and/or peer adversaries, the demands on operational planners and warfighters will quickly increase, thereby requiring decision support assistance. In recent years, major developments in Artificial Intelligence (AI) for video game-playing agents have suggested that some of these approaches could be considered candidates to provide that form of decision support.
The objective of this effort is three-fold. First, AFRL is looking to investigate and develop machine intelligence approaches for supporting and performing operations in complex adversarial environments. It is imperative to explore existing decision support AI algorithms and machine learning methods applicable to developing strategies and playing complex games.
Second, AFRL desires the capability to capture human expertise to augment warfighter capability through gameplay in Air Force (AF) relevant “video games” via interactive components. We will record and learn from subject matter experts and end-user warfighters using these AF video games motivated by operational use cases. Finally, AFRL will apply domain adaptation techniques to transfer AI strategies and/or machine-learned models from video gameplay to AF relevant challenge problems/simulations.
AFRL envisions developing AI approaches in unclassified game playing domains and attempting to transfer to either unclassified or classified scenarios in tools like Advanced Framework for Simulation Integration and Modeling (AFSIM) or others. To develop these capabilities, the focus will be placed on using existing game-playing engines and newly developed interactive “simulation” environments that operators can play, either supported by or against AI agents.
Website: https://sam.gov/opp/0c48744fc48f4967a45612dad94cac24/view
Questions or assistance, contact:
North Carolina Defense Technology Transition Office (DEFTECH)
Dennis Lewis
lewisd@ncmbc.us
703-217-3127
Bob Burton
burtonr@ncmbc.us
910-824-9609
North Carolina Defense Technology Transition Office | PO Box 1748, Fayetteville, NC 2B303