policy
Lunar-Lander-RL-Model
gokulan006 · PyTorch
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Overview
Name
Lunar-Lander-RL-Model
Author
gokulan006
Framework
PyTorch
License
unknown
Skill type
aerial
Evidence level
untested
Task description
This project uses Reinforcement Learning (RL) to train an AI agent to land a spacecraft in the OpenAI Gym Lunar Lander environment. The model leverages Deep Q-Networks (DQN) and other deep learning-based RL techniques for optimal landing strategies. 🔹 Key Concepts: Reinforcement Learning, Q-learn
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 Lunar-Lander-RL-Model yet.
Datasets that reference this policy
0No datasets reference Lunar-Lander-RL-Model yet.