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说明文档

library_name: ml-agents tags:

  • SoccerTwos
  • deep-reinforcement-learning
  • reinforcement-learning
  • ML-Agents-SoccerTwos

poca 智能体玩 SoccerTwos

这是一个使用 Unity ML-Agents 库 训练的 poca 智能体玩 SoccerTwos 的模型。

使用方法（配合 ML-Agents）

文档地址：https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/

我们编写了完整的教程，教你如何使用 ML-Agents 训练你的第一个智能体并将其发布到 Hub：

  • 一个简短教程，教你训练 Huggy 小狗 🐶 去捡棍子，然后直接在浏览器中与它玩耍：https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
  • 一个更详细的教程，帮助你理解 ML-Agents 的工作原理：https://huggingface.co/learn/deep-rl-course/unit5/introduction

继续训练

mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume

观看你的智能体游玩

你可以直接在浏览器中观看你的智能体游玩

  1. 如果该环境属于 ML-Agents 官方环境，请访问 https://huggingface.co/unity
  2. 第一步：找到你的 model_id：Ahmad1423/poca-SoccerTwos
  3. 第二步：选择你的 .nn /.onnx 文件
  4. 点击"观看智能体游玩"👀

Ahmad1423/poca-SoccerTwos

作者 Ahmad1423

reinforcement-learning ml-agents
↓ 0 ♥ 0

创建时间: 2025-01-27 17:54:56+00:00

更新时间: 2025-01-27 17:56:08+00:00

在 Hugging Face 上查看

文件 (33)

.gitattributes
README.md
SoccerTwos.onnx ONNX
SoccerTwos/SoccerTwos-1499102.onnx ONNX
SoccerTwos/SoccerTwos-1499102.pt
SoccerTwos/SoccerTwos-18499942.onnx ONNX
SoccerTwos/SoccerTwos-18499942.pt
SoccerTwos/SoccerTwos-18999924.onnx ONNX
SoccerTwos/SoccerTwos-18999924.pt
SoccerTwos/SoccerTwos-19499962.onnx ONNX
SoccerTwos/SoccerTwos-19499962.pt
SoccerTwos/SoccerTwos-1999030.onnx ONNX
SoccerTwos/SoccerTwos-1999030.pt
SoccerTwos/SoccerTwos-19999986.onnx ONNX
SoccerTwos/SoccerTwos-19999986.pt
SoccerTwos/SoccerTwos-20041758.onnx ONNX
SoccerTwos/SoccerTwos-20041758.pt
SoccerTwos/SoccerTwos-2499772.onnx ONNX
SoccerTwos/SoccerTwos-2499772.pt
SoccerTwos/SoccerTwos-2999348.onnx ONNX
SoccerTwos/SoccerTwos-2999348.pt
SoccerTwos/SoccerTwos-3260.onnx ONNX
SoccerTwos/SoccerTwos-3260.pt
SoccerTwos/SoccerTwos-3375924.onnx ONNX
SoccerTwos/SoccerTwos-3375924.pt
SoccerTwos/checkpoint.pt
SoccerTwos/events.out.tfevents.1737899815.TufLap.20920.0
SoccerTwos/events.out.tfevents.1737959850.TufLap.26228.0
config.json
configuration.yaml
run_logs/Player-0.log
run_logs/timers.json
run_logs/training_status.json