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Command and Control, Modeling and Simulation, Training


OBJECTIVE: Investigate, design, and develop a command and control training system that incorporates state of the art virtual world, virtual reality, gaming engines, avatar, and artificial intelligence technologies. The end state would be multi-player distributed command and control training simulation that is able to model complex command and control element interactions and that is able to synthesize knowledge in real time through artificial intelligence to inform future interactions with the operator in the loop. DESCRIPTION: State of the art training systems have begun to incorporate virtual world, reality, gaming engines, avatars, and artificial intelligence technologies to immerse warfighters in a virtual world to hone a variety of skills and decision making that are not easily trained using traditional training systems. While these technologies have been applied to small scale individual training simulations; there has been no attempt to innovatively apply these same state of art technologies to a large-scale distributed command & control training simulation. Traditional training methods in complex dynamic environments are inefficient at adapting to changing audiences and technologies. A command and control training system must emulate the behavior of the Ballistic Missile Defense System (BMDS) while still providing flexibility to expose geographically distributed command and control personnel to stressful situations and decisions resulting from physical and/or cyber attack that occur as the battle unfolds on their respective command and control graphical user interface (GUI). The command and control personnel must be able to react dynamically to changes in red force tactics and decisions during the battle. Simultaneously the command & control training system must emulate chain of command personnel, not physically participating in the training event, that normally communicate with each other via voice or data communications (e.g. chat messaging). An innovative and tailored approach to virtual based educational delivery methods can increase efficiency and realism for command and control and BMDS training needs. The contractor should investigate emerging technologies in human factors, decision making, and knowledge and semantics that would be used to help emulate the dynamic command and control BMDS operations environment for the purpose of training and education with a high degree of realism. Also, researching recent domain ontology based approaches that could complement the existing BMDS common knowledge base across users through virtual world training scenarios. The contractor should investigate applicable artificial intelligence technology that could improve processing and user interfaces in the BMDS training environment. A critical aspect of the proposed technology is the compliance with the OSD/D9 (Training & Readiness) Virtual World Framework (VWF). The software design should consider an extensible and open architecture that could incorporate the use of diverse computing methodologies and platforms, such as mobile, web based, and multi-core processing environments while complying with security and information assurance standards. The simulation must be accessible from schoolhouses, regional training centers, and operational locations. PHASE I: Develop an innovative command and control training system architecture and design that integrates emerging virtual world, virtual reality, first person gaming, avatar, and artificial intelligence technologies for training through emulation of the BMDS. The architecture and design should incorporate the offeror"s innovation extending current state-of-the-art and security practices. The design should also clearly demarcate internally implemented functions from functionality provided by external services, if any. Conduct pilot studies which interface different training content, simulations, objects, users, and locations to extend and expand the scope of training and education. Phase I work products should include requirements/capabilities, architecture artifacts that would lead the Phase II and Phase III Commercialization development plans. PHASE II: Implement the Phase I design and Phase II development plan in a prototype and demonstrate the simulation capability. Continued improvements and refinements to the design, architecture, and technology capability should be based on stakeholder feedback, and continued collaboration with command and control operators, and Subject Matter Experts (SMEs). Demonstrate the proposed technology capability and performance with differing types of command and control structures. Demonstrate the ability to evaluate architectural attributes and integrate design choices which achieve scalability at the hardware and software levels (i.e., processor speed, network bandwidth, etc.). The Phase II work products would include supporting software development and architecture documentation, and installation and training/users guides. PHASE III: Integrate the developed command virtual world training system for demonstration in real world training environment. Improve and refine design, architecture, and capabilities based on stakeholder and user feedback. Demonstrate this capability through analysis showing performance and reliability of human machine interaction in the operational training environment. DUAL USE/COMMERCIALIZATION USE/COMMERCIALIZATION POTENTIAL: The contractor will pursue commercialization opportunities across the MDA BMDS and other applicable organizations in the Department of Defense (DoD) training domain. Multiple DoD organizations require OSD/D9 Training & Readiness compliance for next generation training. Those organizations could very easily leverage the base technology developed through this effort, requiring minimal changes to specific behaviors of the individual representations. The commercial gaming world will also be able to leverage much of the artificial intelligence that will be developed for the learning model"s ability to synthesize new knowledge that is captured through the execution of the simulation. This technology is also applicable to diverse related distributed on-line gaming, commercial training applications, commercial artificial intelligence applications, operator-in-the-loop simulations, and system-of-systems simulations.
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