doublechocolatecup/ML-Agents-SoccerTwos

reinforcement-learning model by doublechocolatecup

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[](https://github.com/Unity-Technologies/ml-agents) [](https://github.com/Unity-Technologies/ml-agents/blob/main/docs/Learning-Environment-Examples.md#soccer-twos) [](https://opensource.org/licenses/Apache-2.0) [](https://onnx.ai/) A sophisticated multi-agent reinforcement learning model trained on the Unity ML-Agents SoccerTwos environment. This model demonstrates advanced cooperative and competitive behaviors in a 2v2 soccer simulation, showcasing emergent team strategies and individual skill development. The SoccerTwos model represents a breakthrough in multi-agent reinforcement learning, where four AI agents (two teams of two players each) learn to play soccer through self-play and competitive training. The model exhibits complex behaviors including: Game Setup: Physics & Mechanics: Each agent receives: Offensive Strategies: Defensive Strategies: Minimum: Recommended: We welcome contributions to improve the…

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Model overview

doublechocolatecup/ML-Agents-SoccerTwos is a reinforcement-learning model repository published by doublechocolatecup on Hugging Face. The source reports the ml-agents library.

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Model facts

Task: reinforcement-learning
Library: ml-agents
Recent downloads (30 days): 0
Cumulative likes: 0
Hugging Face trending score: 0
Reported safetensors parameters: Not reported
Architecture: Not reported
License: Not reported — check the model card
Access: Not gated by Hugging Face
Created: 2026-09-26T06:33:33.000Z
Last modified: 2026-09-26T06:33:35.000Z

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