A stochastic agent approach (SAA) for mission effectiveness

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Author(s)
Gordon, Seth Edward
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Daniel Guggenheim School of Aerospace Engineering
The Daniel Guggenheim School of Aeronautics was established in 1931, with a name change in 1962 to the School of Aerospace Engineering
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Abstract
A process for using stochastic and probabilistic agent decision-making was proposed. This process is employed to conduct a Mission Space Exploration to evaluate a wide assortment of possible matériel and non-matériel solutions to an identified capability gap. The Stochastic Agent Approach (SAA) simplifies the previously intractable Mission Design Space using Agent-Based Variables (ABVs). In this method, rather than a detailed discretization of the actions (or decision-making logic) undertaken by every simulated asset at every time-step, the variable space becomes a series of decision-affecting coefficients. The method was developed through a series of experiments to identify the stages necessary to achieve this capability. Case studies involving an aircraft strike mission and a contested reconnaissance scenario were used to explore the approach. However, this methodology is applicable to a variety of scenarios and situations. The procedure for generating and leveraging Agent-Based Variables is simulation method- and tool-agnostic, and adaptable to most potential scenarios. In summary, the SAA illustrates how to craft Agent-Based Variables to achieve a degree of Mission Space Exploration and capability approximation not currently feasible. This enables a superior ability to understand, adapt to, and conduct trades within the Mission Design Space through this inclusion of decision-making affecting parameters.
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2018-05-15
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Dissertation
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