KBSI defined a neutral format for capturing, organizing, and sharing process-related knowledge that is based on the Integrated Definition family of Methods and the eXtended Markup Language (XML). Using this standard, KBSI developed an advanced authoring tool-kit for situation-based, process centric computer-based training systems.
Because processes are central to the operation of all aspects of an organization, most decision-making applications and implementation solutions deal with the capture, specification, representation, and manipulation of process-related information. This information may in turn be used to support business process re-engineering, workflow systems development, and a wide range of training needs. Since these application domains require the same process information, process knowledge capture for one application should easily support other purposes. Yet, sharing and reusing process knowledge across applications remains an unrealized vision. The need for standards to capture, represent, share, and display process-related information is particularly important in training applications. Process-centered training provides students with the most reliable approach for understanding, internalizing, and applying new concepts.
AARDIS researched advanced electronic warfare (EW) training methods and tools that reduce the cognitive workload of instructors, improve training effectiveness, accelerate improvements in student performance, and reduce training costs.
Pilot training at the U.S. Air Force (USAF) faces two fundamental challenges: rising training costs and restrictions, and the changing nature of military conflicts around the globe. According to a recent RAND study, the costs of USAF initial skills training (IST) have risen to approximately $750 million per year. In addition, the opportunities for live training exercises, because of limits on training airspace, rising fuel costs and heightened security, have been diminishing.
The FEAST technology uses an innovative methodology for dynamic scenario generation and adaption in simulation-based environments for mission operations training. The technology’s knowledge discovery and automated reasoning methods let you evolve scenario design knowledge over time.
KBSI began by establishing the requirements for a dynamic scenario generation for individual and team learning in simulation-based environments. This requirements building will utilize the Air Force’s Mission Essential Competencies (MECs)-based model as a means for enabling effective transformation from mission based training to competency based training in DMO training environments.
The FAMOS OSAI Method™ technology is a system for developing and executing distributed military simulation applications. The technology reduces the time and effort needed to develop and deploy distributed simulation applications and helps establish knowledge sharing and semantic integration among modeling and simulation applications.
In this initiative, KBSI collaborated with the Air Force to build a system for the development and execution of distributed military simulation applications. The Framework for Adaptive Modeling and Ontology-driven Simulation (FAMOS OSAI Method™) reduces the time and effort required for developing and deploying distributed simulation applications and lays the groundwork for knowledge sharing, communication, and semantic integration among modeling and simulation applications.
SUPERCISION™ uses data mining, Bayesian nets, situation theory, and commercial gaming technologies to support the assessment and improvement of decision making skills in training systems. SUPERCISION™ methods and tools improve scenario-based training and reduce the time and effort needed to create tailored training scenarios.
A frequently quoted maxim from the Army’s 100-5 Operations Field Manual states: “Effective decision making combines judgment with information as an element of combat power: it requires knowing if to decide, when to decide, and what to decide.”