AFRL seeks AI mission ops sources

On May 26, the Air Force Research Laboratory (AFRL) posted a request for information for Artificial Intelligence (AI)-Enabled Environment for Live, Synthetic, Blended (LSB) Distributed Mission Operations. White papers are due by 12:00 p.m. Mountain on June 25.


The Air Force Research Laboratory Space Vehicles Directorate’s Simulation & Technology Assessment Branch (AFRL/RVES) invests in agile and affordable modeling, simulation & analysis technologies and testbeds to enable live, virtual, and constructive assessments of new mission concepts and capabilities. One goal of the MSE&A program is to gain early technical insights into how emerging technologies would perform in an operationally representative environment.

The Distributed Mission Operations (DMO) Center (DMOC) provides virtual training and virtual environments for the Air Force, Joint and Coalition warfighters that accurately represent friendly and adversary forces within a virtual space. Their purpose is to prepare warfighters for combat by training a Combat Representative Force in a Combat Representative Environment. The DMOC accomplishes this using a powerful set of environment generators (EGs) and linking geographically separated Live, Virtual, and Constructive entities within shared Joint & Coalition synthetic theater environments (such as, Distributed Mission Operation Network (DMON), Air Reserve Component Network (ArcNet), Navy Continuous Training Environment (NCTE), and Joint Training & Experimentation Network.)

AFRL/RVES and the DMOC are collaborating to develop and integrate game-changing space capabilities into a Live, Synthetic, Blended (LSB) all-domain warfighting environment. This collaboration will enable both Air Force operational training and development of statistically and scientifically driven Modeling, Simulation & Analysis (MS&A) in order to equip Warfighters to dominate in time, space and complexity across all operating domains.

AFRL is soliciting white papers for developing AI-enabled, agile and affordable modeling, simulation, and analysis technologies and testbeds, as described in Topic Area 2 of the basic announcement.

Full information is available here.

Source: SAM