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SoccerTwos
MahaLakshmi2026/SoccerTwos
SoccerTwos is a reinforcement learning model from MahaLakshmi2026. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product. It is set up for ml-agents.
This repository contains a trained multi-agent reinforcement learning model for the Unity ML-Agents SoccerTwos environment.
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.onnx1.8 MB · 100%
At a glance
- Task
- Reinforcement Learning
- Library
- ml-agents
- Access
- Public
- Created
- Sep 23, 2026
- Updated
- Sep 23, 2026
- SHA
- bd2340f9
Model card
From the Hugging Face model README
MA-POCA Agent playing SoccerTwos
This repository contains a trained multi-agent reinforcement learning model for the Unity ML-Agents SoccerTwos environment.
Environment
- Environment: SoccerTwos
- Teams: 2
- Agents per team: 2
- Trainer: MA-POCA (POCA)
- Self-play: Enabled
- Framework: Unity ML-Agents
- Model format: ONNX
- Training steps: 547,682
Model
The trained policy is available as:
SoccerTwos.onnx
Training
The model was trained using the official Unity ML-Agents SoccerTwos environment and the MA-POCA trainer with self-play.
Training was stopped after 547,682 steps and the final ONNX model was exported successfully.
The reported reward metadata is based on training group-reward observations and is not an AI-vs-AI leaderboard score.
Hugging Face Deep Reinforcement Learning Course
This model was trained for Unit 7 of the Hugging Face Deep Reinforcement Learning Course.
- Task
- Reinforcement Learning
- Library
- ml-agents
- Created
- Sep 23, 2026
- Updated
- Sep 23, 2026