Reinforcement Learning
ml-agents
ONNX
ML-Agents-SnowballTarget
SnowballTarget
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use SimhaSimha/ppo-SnowballTarget with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use SimhaSimha/ppo-SnowballTarget with ml-agents:
mlagents-load-from-hf --repo-id="SimhaSimha/ppo-SnowballTarget" --local-dir="./download: string[]s"
- Notebooks
- Google Colab
- Kaggle
File size: 809 Bytes
e0b4dec | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ---
library_name: ml-agents
tags:
- ML-Agents-SnowballTarget
- SnowballTarget
- ml-agents
- reinforcement-learning
- deep-reinforcement-learning
model-index:
- name: ppo-SnowballTarget
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: ML-Agents-SnowballTarget
type: ML-Agents-SnowballTarget
metrics:
- type: mean_reward
value: 25.50 +/- 2.10
name: mean_reward
---
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
To learn more check Unit 5 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit5/introduction
|