Abstract
Reinforcement learning is a machine learning approach in which an intelligent agent learns to take actions to maximize a reward. We will apply this to the design of a Titan landing control system. Reinforcement learning is a tool to approximate solutions that could have been obtained by dynamic programming, but whose exact solutions are computationally intractable [3].
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References
D. Bertsekas. Reinforcement Learning and Optimal Control. Athena Scientific, 2019.
Daniel S. Kolosa. A Reinforcement Learning Approach to Spacecraft Trajectory Optimization. Technical Report Dissertations 3542, Western Michigan University, 2019.
W. E. Wiesel. Spaceflight Dynamics. McGraw-Hill, 1988.
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Paluszek, M., Thomas, S., Ham, E. (2022). Reinforcement Learning. In: Practical MATLAB Deep Learning. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-7912-0_15
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DOI: https://doi.org/10.1007/978-1-4842-7912-0_15
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