Paper
19 May 2005 Distributed collaborative decision support environments for predictive awareness
Author Affiliations +
Abstract
The past decade has produced significant changes in the conduct of military operations: asymmetric warfare, the reliance on dynamic coalitions, stringent rules of engagement, increased concern about collateral damage, and the need for sustained air operations. Mission commanders need to assimilate a tremendous amount of information, rapidly assess the enemy’s course of action (eCOA) or possible actions and promulgate their own course of action (COA) - a need for predictive awareness. Decision support tools in a distributed collaborative environment offer the capability of decomposing complex multitask processes and distributing them over a dynamic set of execution assets that include modeling, simulations, and analysis tools. Revolutionary new approaches to strategy generation and assessment such as Linguistic Geometry (LG) permit the rapid development of COA vs. enemy COA (eCOA). LG tools automatically generate and permit the operators to take advantage of winning strategies and tactics for mission planning and execution in near real-time. LG is predictive and employs deep “look-ahead” from the current state and provides a realistic, reactive model of adversary reasoning and behavior. Collaborative environments provide the framework and integrate models, simulations, and domain specific decision support tools for the sharing and exchanging of data, information, knowledge, and actions. This paper describes ongoing research efforts in applying distributed collaborative environments to decision support for predictive mission awareness.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
William K. McQuay, Boris Stilman, and Vlad Yakhnis "Distributed collaborative decision support environments for predictive awareness", Proc. SPIE 5805, Enabling Technologies for Simulation Science IX, (19 May 2005); https://doi.org/10.1117/12.609727
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Cited by 3 scholarly publications.
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KEYWORDS
Data modeling

Human-machine interfaces

Process modeling

Bridges

Telecommunications

Systems modeling

Analytical research

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