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Adam Herrmann
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Monte Carlo Tree Search Methods for the Earth-Observing Satellite Scheduling Problem
AP Herrmann, H Schaub
Journal of Aerospace Information Systems 19 (1), 70-82, 2022
152022
Reinforcement Learning for the Agile Earth-Observing Satellite Scheduling Problem
A Herrmann, H Schaub
IEEE Transactions on Aerospace and Electronic Systems, 2023
122023
Processing–Microstructure–Property Relationships in a Laser‐Deposited Fe‐Co‐V Alloy
S Firdosy, N Ury, JP Borgonia, B McEnerney, R Conversano, R Hofer, ...
Advanced Engineering Materials 24 (4), 2100931, 2022
92022
Autonomous On-board Planning for Earth-Orbiting Spacecraft
A Herrmann, H Schaub
2022 IEEE Aerospace Conference (AERO), 1-9, 2022
72022
Autonomous Spacecraft Tasking Using Monte Carlo Tree Search Methods
A Herrmann, H Schaub
31st AAS/AIAA Space Flight Mechanics Meeting, 2021
62021
A Comparison of Deep Reinforcement Learning Algorithms for Earth-Observing Satellite Scheduling
A Herrmann, H Schaub
AAS Spaceflight Mechanics Meeting, Austin, TX, 23-116, 2023
52023
Reinforcement Learning for Small Body Science Operations
A Herrmann, H Schaub
AAS/AIAA Astrodynamics Specialist Conference, 2022
42022
Single-Agent Reinforcement Learning for Scalable Earth-Observing Satellite Constellation Operations
A Herrmann, MA Stephenson, H Schaub
Journal of Spacecraft and Rockets 61 (1), 114-132, 2024
12024
Reinforcement Learning for the Multi-Satellite Earth-Observing Scheduling Problem
A Herrmann, JV Carneiro, H Schaub
1*
A Comparative Analysis of Reinforcement Learning Algorithms for Earth-Observing Satellite Scheduling
A Herrmann, H Schaub
Frontiers in Space Technologies 4, 1263489, 2023
2023
Reinforcement Learning for Spacecraft Planning and Scheduling
AP Herrmann
University of Colorado at Boulder, 2023
2023
Trustworthy Reinforcement Learning for Decentralized Control of Satellites
V Bajenaru, A Herrmann, H Schaub, J Ramirez, S Phillips
Monte Carlo Tree Search for Autonomous Small Body Science Operations
A Herrmann, H Schaub
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Articles 1–13