policy
-LunarLander-PPO-Agent
meheramir123 · PyTorch
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Overview
Name
-LunarLander-PPO-Agent
Author
meheramir123
Framework
PyTorch
License
unknown
Skill type
aerial
Evidence level
untested
Task description
A Reinforcement Learning (RL) agent trained using the PPO (Proximal Policy Optimization) algorithm to land a lunar module safely and precisely on the landing pad.
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
3+17 mentioned but not in catalog yetCompatible environments
0No environments list -LunarLander-PPO-Agent yet.
Datasets that reference this policy
0No datasets reference -LunarLander-PPO-Agent yet.