forgedRice/ML-Agents-SoccerTwos
By forgedRice · ↓ 0 · ♥ 0 · Updated 2025-09-27
What's in this repo
This page lists the files in forgedRice/ML-Agents-SoccerTwos, including SoccerTwos-48499986.onnx, SoccerTwos-48999991.onnx, SoccerTwos-49499988.onnx and more.
- 5 ONNX models (.onnx files)
- 19 files, including 6 .pt, 5 .onnx, 3 .json, 1 .md, 1 .0, 1 .yaml
- Last updated 2025-09-27
ONNX files
| File | Size | Download |
|---|---|---|
| SoccerTwos/SoccerTwos-48499986.onnx | — | Download |
| SoccerTwos/SoccerTwos-48999991.onnx | — | Download |
| SoccerTwos/SoccerTwos-49499988.onnx | — | Download |
| SoccerTwos/SoccerTwos-49999945.onnx | — | Download |
| SoccerTwos/SoccerTwos-50000080.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
library_name: ml-agents tags:
- SoccerTwos
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SoccerTwos
- multi-agent
- self-play
- MA-POCA
MA-POCA Agent playing SoccerTwos
This is a trained multi-agent team playing SoccerTwos using the Unity ML-Agents Library with MA-POCA (Multi-Agent POsthumous Credit Assignment) and self-play.
The agents learned cooperative 2v2 soccer behavior where each team tries to score goals while preventing the opponent from scoring.
Algorithm: MA-POCA with Self-Play
Training: 5,000,000 timesteps
Environment: SoccerTwos 2v2 soccer
Team Strategy: Cooperative multi-agent behavior
This model participates in the AI vs AI Challenge where it competes against other trained agents on the leaderboard.
Watch the Agent Play
You can watch this agent compete against others at: https://huggingface.co/spaces/unity/ML-Agents-SoccerTwos
Check the AI vs AI leaderboard: https://huggingface.co/spaces/huggingface-projects/AIvsAI-SoccerTwos
Model info
Created: 2025-09-27
Updated: 2025-09-27
View on Hugging Face