Instructions to use RyanAA/ppo-SnowballTarget with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use RyanAA/ppo-SnowballTarget with ml-agents:
mlagents-load-from-hf --repo-id="RyanAA/ppo-SnowballTarget" --local-dir="./download: string[]s"
- Notebooks
- Google Colab
- Kaggle
File size: 671 Bytes
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tags:
- reinforcement-learning
- ml-agents
- ppo
- unity
- SnowballTarget
- ML-Agents-SnowballTarget
license: mit
---
# PPO SnowballTarget
This is a trained PPO agent playing SnowballTarget using Unity ML-Agents.
## Environment
SnowballTarget
## Algorithm
PPO (Proximal Policy Optimization)
## Training Results
Final mean reward: ~23.2 after 200k training steps.
## Usage
You can watch the agent play directly in your browser:
1. Go to:
https://huggingface.co/spaces/ThomasSimonini/ML-Agents-SnowballTarget
2. Search for "RyanAA"
3. Select `SnowballTarget.onnx`
4. Click "Watch the agent play"
## Files
- `SnowballTarget.onnx` — trained policy network |