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ppo 智能体游玩 Pyramids

这是一个训练好的 ppo 智能体,用于游玩 Pyramids, 使用 Unity ML-Agents Library 训练。

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,帮助你学习如何使用 ML-Agents 训练第一个智能体并发布到 Hub:

  • 简短教程:教你让 Huggy 小狗 🐶 去捡棍子,然后直接在浏览器中与它互动: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
  • 详细教程:深入了解 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. 如果环境是 ML-Agents 官方环境的一部分,请访问 https://huggingface.co/unity
  2. 第一步:找到你的 model_id:s14pe/ppo-Pyramid
  3. 第二步:选择你的 .nn /.onnx 文件
  4. 点击 Watch the agent play 👀

s14pe/ppo-Pyramid

作者 s14pe

reinforcement-learning ml-agents
↓ 0 ♥ 0

创建时间: 2024-03-07 19:18:02+00:00

更新时间: 2024-03-07 22:17:18+00:00

在 Hugging Face 上查看

文件 (35)

.gitattributes
Pyramids.onnx ONNX
Pyramids/Pyramids-1000039.onnx ONNX
Pyramids/Pyramids-1000039.pt
Pyramids/Pyramids-1499903.onnx ONNX
Pyramids/Pyramids-1499903.pt
Pyramids/Pyramids-1999919.onnx ONNX
Pyramids/Pyramids-1999919.pt
Pyramids/Pyramids-1999990.onnx ONNX
Pyramids/Pyramids-1999990.pt
Pyramids/Pyramids-2000102.onnx ONNX
Pyramids/Pyramids-2000102.pt
Pyramids/Pyramids-2100049.onnx ONNX
Pyramids/Pyramids-2100049.pt
Pyramids/Pyramids-2499999.onnx ONNX
Pyramids/Pyramids-2499999.pt
Pyramids/Pyramids-2999998.onnx ONNX
Pyramids/Pyramids-2999998.pt
Pyramids/Pyramids-3000126.onnx ONNX
Pyramids/Pyramids-3000126.pt
Pyramids/Pyramids-999911.onnx ONNX
Pyramids/Pyramids-999911.pt
Pyramids/checkpoint.pt
Pyramids/events.out.tfevents.1709831665.54b79351de07.19820.0
Pyramids/events.out.tfevents.1709839089.54b79351de07.49573.0
Pyramids/events.out.tfevents.1709842175.54b79351de07.62222.0
Pyramids/events.out.tfevents.1709842345.54b79351de07.62956.0
Pyramids/events.out.tfevents.1709845030.54b79351de07.73755.0
Pyramids/events.out.tfevents.1709849499.54b79351de07.91689.0
README.md
config.json
configuration.yaml
run_logs/Player-0.log
run_logs/timers.json
run_logs/training_status.json