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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 32 minutes ago
Organization National Aeronautics and Space Administration (NASA) Reference Code 0328-NPP-NOV25-JPL-TechDev How to Apply All applications must be submitted in Zintellect Please visit the NASA
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sampling of information in decision-making Decision-making algorithms for human-robot collaborative tasks Game theory applied for multi-agent learning Distributed optimization communication for collaborative
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hardware implementing Deep Reinforcement Learning algorithms for the tactical arena. Additionally, High Level Synthesis (HLS) will be incorporated to obtain hardware designs optimized for various criteria
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collection of streaming sensor data. This project focuses on utilizing state-of-the-art reinforcement algorithms to 1) dynamically learn from multi-agent actions and context, 2) evaluate the environment and
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on the energy constraints associated with their mission planning and logistics of operation. The goal of this research is to develop new techniques and algorithms that can better plan the missions of aerial and