policy
Mario-Game-Reinforcement-Learning
Ahmed-Nezar · Stable-Baselines3
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Overview
Name
Mario-Game-Reinforcement-Learning
Author
Ahmed-Nezar
Framework
Stable-Baselines3
License
unknown
Skill type
other
Evidence level
untested
Task description
This project is a reinforcement learning project that uses the PPO algorithm to train an agent to play the game Super Mario Bros. The game is played using the gym-super-mario-bros environment. The agent is trained using the stable-baselines3 library. The agent was trained for 5 million steps and was
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 Mario-Game-Reinforcement-Learning yet.
Datasets that reference this policy
0No datasets reference Mario-Game-Reinforcement-Learning yet.