Lunar-Lander-Double-Deep-Q-Networks and aigym_dqn
These are **competitors** — both implement Deep Q-Network variants to solve the same lunar landing problem in OpenAI Gym environments, with Double DQN (A) being a more advanced algorithmic approach than standard DQN (B).
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Maturity
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Community
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Maintenance
10/25
Adoption
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Maturity
9/25
Community
0/25
Stars: 17
Forks: 6
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Commits (30d): 0
Language: Python
License: MIT
Stars: 4
Forks: —
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
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About Lunar-Lander-Double-Deep-Q-Networks
anh-nn01/Lunar-Lander-Double-Deep-Q-Networks
An AI agent that use Double Deep Q-learning to teach itself to land a Lunar Lander on OpenAI universe
About aigym_dqn
kucharzyk-sebastian/aigym_dqn
Deep Q-Network agent implemented in Python capable of learning to land on the moon in MoonLander-v2 environment from AI Gym library
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