bipedal_walker_ppo / README.md
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Adding::Bipedal Walker trained using PPO
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---
library_name: stable-baselines3
tags:
- BipedalWalker-v3
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: Proximal Policy Optimisation (PPO)
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: BipedalWalker-v3
type: BipedalWalker-v3
metrics:
- type: mean_reward
value: 229.21 +/- 63.57
name: mean_reward
verified: false
---
# **Proximal Policy Optimisation (PPO)** Agent playing **BipedalWalker-v3**
This is a trained model of a **Proximal Policy Optimisation (PPO)** agent playing **BipedalWalker-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...
```