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Lunar Lander Reinforcement Learning Project

Tyler Kinkade

This was a small exploratory project to compare the effectiveness of artificial agent algorithms ranging in sophistication from naive to deep reinforcement learning (Russell & Norvig, 2022; Sutton & Barto, 2018) to successfully land a virtual "lunar lander" in a Gymnasium (2022) model environment. After comparing the various models, I explored the effects of various hyperparameters on a deep Q-network model (Mnih et al., 2015).

See the project.ipynb Jupyter notebook for the full report.

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AI reinforcement learning virtual lunar lander project

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