policy
RL-PCO-Atlantis-Atari
canoksuzoglu1 · PyTorch
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Overview
Name
RL-PCO-Atlantis-Atari
Author
canoksuzoglu1
Framework
PyTorch
License
unknown
Skill type
manipulation
Evidence level
untested
Task description
This project trains and evaluates a Proximal Policy Optimization (PPO) agent to play the Atari game Atlantis using Stable Baselines3. The agent is trained with a Convolutional Neural Network (CNN) policy and evaluated for its performance in the game. It includes scripts for training, evaluating, and
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 RL-PCO-Atlantis-Atari yet.
Datasets that reference this policy
0No datasets reference RL-PCO-Atlantis-Atari yet.