AI 中文总结
本研究介绍了AGENTONOMICS框架的首个应用Dr. AGENTONOMICS，将其作为教学智能体，提出其可拓展为多角色系统并探讨其对多中心AI经济的意义。
AI 中文摘要
AGENTONOMICS是一个将AI智能体视为经济实体的框架，可通过集成管理架构对其进行设计、管理和治理。Dr. AGENTONOMICS是该框架的首个应用：一款在慕尼黑工业大学（TUM）“工商管理中的AI智能体”课程背景下开发的教学智能体。它构思于2025/26冬季学期，于2026夏季学期首次面向学生推出，作为一项教学实验，该智能体既是学生研究的对象，也是学生学习和应用该框架的媒介。当前原型是一款基于网络、具备检索增强功能的辅导工具，用于解释AGENTONOMICS概念并解答学生问题。本报告指出，同一系统可在辅导功能基础上拓展出三个递进角色：提供多模态教学的化身讲师、指导学生使用AGENTONOMICS设计与管理参考框架（ADMRF）的设计顾问，以及协助构建学生指定智能体的元智能体。这些角色具有递进关系，因为它们共享相同的界面、智能层、工具、知识库和生态系统连接，而编排器会为每项任务选择角色特定的算法。本文展示了原型架构、概述了开发路线图，并探讨了其对多中心AI经济的意义，旨在引发更多关于智能体如何教授、应用并最终复制其设计所依据的框架的讨论。
英文摘要
AGENTONOMICS is a framework that treats AI agents as economic entities that can be designed, managed, and governed through an integrated management architecture. Dr. AGENTONOMICS is its first application: a lecture agent developed in the context of the TUM course on AI agents in business administration. Conceived during the winter semester 2025/26 and first introduced to students in the summer semester 2026, it serves as a didactic experiment in which the agent is both the object that students study and the medium through which they learn and apply the framework. The current prototype is a web-based, retrieval-grounded tutor that explains AGENTONOMICS concepts and supports student questions. This report argues that the same system can grow beyond tutoring into three additional cumulative roles: an avatar lecturer that delivers multimodal instruction, a design consultant that guides students through the AGENTONOMICS Design & Management Reference Framework (ADMRF), and a meta-agent that helps construct the agents students have specified. These roles are cumulative because they share the same interface, intelligence layer, tools, knowledge base, and ecosystem connection, while an orchestrator selects the role-specific algorithm required for each task. We present the architecture of the prototype, outline its development roadmap, and discuss its implications for a polycentric AI economy. This report is intended to invite further discussion on how agents can teach, apply, and eventually reproduce the frameworks by which they are designed.
CommentsTechnical report, Technical University of Munich
