As part of the Air Force’s future vision, missions are expected to have a smaller footprint and deploy fewer personnel to complete objectives than in the past. However, it’s unlikely all crew members will have the necessary training to complete the wide variety of tasks assigned during these missions, especially when operating in a resource-limited environment. The Personalized Learning Assistant for Training Optimization (PLATO) from Charles River Analytics remedies this knowledge gap by tailoring personalized training in real time to the warfighter’s prior experience, available resources, and even the environmental conditions.
Traditionally, Air Force missions have been beefed-up deployments with large numbers of warfighters needed to carry out a wide range of complex and very specific tasks. Each of these team members usually only performs tasks within their Air Force Specialty Code (AFSC). But to reduce its footprint while remaining nimble, the Air Force has leaned into the Agile Combat Employment (ACE) model, where a reduced number of personnel carry out a subset of missions in remote environments where they might not have ready access to the ideal complement of resources.
PLATO’s personalized learning assistant provides the adaptive cross-modality capabilities that make the ACE model practical for Air Force operations that are often conducted in austere, communications-limited settings. Consider, for example, a temporary airfield in a remote location designed to handle a small number of short-duration missions. These airfields would likely lack the tools and equipment to support each of the wide-ranging training platforms the Air Force employs. PLATO, which was funded by a Phase II Air Force Research Laboratory award of over $1.25M under the Small Business Innovation Research (SBIR) program, solves that problem.
“At a remote airfield, the training materials might have been geared toward video-based training, but the personnel don’t have any tools available on site that could play videos, for example. Using PLATO, Air Force personnel can modify—or remix—their existing video-based training so it can be printed as a PDF, and/or audio instructions that the Airmen can then use to quickly get up to speed on how to work with this aircraft,” says Dr. E. Vincent Cross, II, Principal Investigator on PLATO and Senior Scientist at Charles River.
“PLATO enables the Air Force to be more dynamic and complete missions with whatever personnel they have available and any equipment they have available,” says Cross.
Phase I of PLATO demonstrated the feasibility of the approach and satisfied the Air Force’s goal of delivering three kinds of training:
- Extensive training, when the warfighter has advance notice of mission requirements
- Refresher training, when aircraft arrival is imminent, and the warfighter only needs access to relevant information
- Real-time support, when the aircraft has arrived
PLATO’s personalized learning assistant, Cross says, uses the training modules that the Air Force has already developed—whether they are PDFs, video segments, or PowerPoint presentations—and presents the material in a device-agnostic format that best suits the warfighter’s work environment. The ability to use a tool to parse training materials in different formats instead of having to manually convert them from one format to another saves time and money, Cross says, which increases PLATO’s value to the Air Force. PLATO is also context aware, taking environmental considerations like ambient light, noise clutter, or ongoing tasks into account when determining the best modality for presenting training material.
Much of the solution’s AI underpinnings come from Charles River’s flagship adaptive training products, KWYN® (Knows What You Need™) and KWYN® MAGPIE (adapted for aviation implementations).
Three innovative components power PLATO: the Training Content Annotator, which breaks down training content into granular, structured components and provides semantic labels, the Context-Aware Content Mapper builds upon these annotated materials by dynamically aligning content with user-specific training scenarios, adapting the delivery to the trainee’s skill level, role, and real-time task progress, and the Context-Aware Content Courier serves as the delivery engine, factoring in the range of challenging conditions the warfighters might face and deliver the most helpful training content in the best medium for the task at hand.
Cross expects PLATO’s utility to extend beyond the Air Force to benefit all defense personnel. Its adaptive training capabilities could also support NASA astronauts on long-duration missions. The potential commercial applications are numerous, ranging from automotive repairs to oil and gas operations on remote offshore platforms with limited connectivity and challenging weather. PLATO can provide adaptive, real-time guidance for complex repair tasks using semantic frameworks to provide clear, step-by-step instructions. It’s ability to adapt to the user’s environment makes completing critical tasks faster, easier, and more cost effective.
Contact us to learn more about PLATO, KWYN®, or our other adaptive intelligent training capabilities.
This material is based upon work supported by the Air Force Research Laboratory under Contract No. FA2384-24-C-B020. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author (s) and do not necessarily reflect the views of the Air Force Research Laboratory.
