---
tags:
- deep-reinforcement-learning
- reinforcement-learning
- ml-agents
- unity-ml-agents
- poca
- SoccerTwos
- deep-rl-course
- ML-Agents-SoccerTwos
library_name: ml-agents
---

# ML-Agents SoccerTwos Model for Deep RL Course Unit 7

This is a trained multi-agent reinforcement learning model using the **POCA (MA-POCA)** trainer algorithm to play soccer in the Unity `SoccerTwos` environment. 

This model was trained as part of the [Hugging Face Deep Reinforcement Learning Course](https://huggingface.co).

## Environment Details
* **Name**: SoccerTwos
* **Number of Teams**: 2 (Blue vs Purple)
* **Agents per Team**: 2
* **Goal**: Outscore the opposing team within the time limit.

## Training Configuration
The training was conducted with shortened parameters to optimize computation overhead:
* **Max Steps**: 500,000
* **Hidden Units**: 128
* **Batch Size**: 1024
* **Trainer Type**: poca

## How to Use
To inspect or utilize this policy file locally within your ML-Agents environment workspace, look at the uploaded `.onnx` binary file inside this repository.