代码仓库
软件工具 / 开源
Agent Priors guided Policy Learning · Agentics-robotics
用于策略学习和技能构成的机器人学习框架。
概述
A robot-learning framework for policy learning and skill composition.<br><br>Publisher summary：“APPL is an agentic robot learning framework connecting policy learning with agent-based skill selection and composition through structural priors for generalization from a few…”<br><br>Use its repository to inspect the implementation, documentation and supported workflows. This directory record identifies the maintainer, code license and related resources; it does not claim that the project has been installed or tested on your robot.
项目信息
- 维护者
- Agentics-robotics
- 主要语言
- Python
- 存储库代码许可证
- MIT
- 模型重量许可证
- 未记录
- 数据集许可
- 未记录
- 硬件设计许可证
- 未记录
- 维护
- 未存档在最后记录的元数据中
- 最后观察到的存储库推送
- 2026-10-04
代码许可不会自动涵盖模型权重、数据集或硬件设计。未记录的许可证详细信息需要与发布者确认。
文档部分
- Agent Priors-guided Policy Learning (APPL)
- Start with the released results
- Experiments
- Data and trained policies
- Environments and API configuration
- Layout and verification
