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In military simulations, software agents are used to represent individuals, weapon platforms or aggregates thereof. Modeling the behavioral capabilities and limitations of such agents may be time-consuming, requiring extensive interaction with subject matter experts and complicated scripts, but nevertheless resulting in rigid, predictable performance. Autonomous agents that learn desired behaviors...
In this paper we report on our study of the performance of Deep Reinforcement Learning (DRL) agents in performing tasks that are illustrative for human Sensor Operators (SOs) in Remotely Piloted Aircraft Systems (RPASs). Our hypothesis is that the descriptive and predictive qualities of the agent's learning process potentially allow us to identify human task requirements, training needs, selection...
Commercial/Military-Off-The-Shelf (COTS/MOTS) Computer Generated Forces (CGF) packages are widely used in modeling and simulation for training purposes. Conventional CGF packages often include artificial intelligence (AI) interfaces, but lack behavior generation and other adaptive capabilities. We believe Machine Learning (ML) techniques can be beneficial to the behavior modeling process, yet such...
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