让可信的AI代理代表人或组织在线自主行动
Here's Charlie! Realising the Semantic Web vision of Agents in the age of LLMs
- 代理仅在缺乏足够信息时才询问用户，实现人机协同决策
- 用规则确保数据使用安全，用大模型支持自然语言交互
- 适合关注隐私与自动化平衡的开发者和政策制定者
本文研究了一种近中期未来：个人和组织可委托半自主的AI驱动代理代为执行网络交互。这些代理在具备充分上下文和信心时可自主运行，否则会主动向用户求助。这种人机对话机制使用户能传授信任的信息源、数据共享偏好及决策风格，从而在保留代理便利性的同时，最大化对自身数据与决策的控制权。针对构建可信赖的半自主代理网络这一核心问题，研究识别出关键需求，并以通用个人助理为例展示原型系统。该系统采用Notation3规则保障信念、数据共享与数据使用的安全约束，结合大模型实现自然语言交互与软件代理间的意外对话。
原文摘要 · Abstract (English)
This paper presents our research towards a near-term future in which legal entities, such as individuals and organisations can entrust semi-autonomous AI-driven agents to carry out online interactions on their behalf. The author's research concerns the development of semi-autonomous Web agents, which consult users if and only if the system does not have sufficient context or confidence to proceed working autonomously. This creates a user-agent dialogue that allows the user to teach the agent about the information sources they trust, their data-sharing preferences, and their decision-making preferences. Ultimately, this enables the user to maximise control over their data and decisions while retaining the convenience of using agents, including those driven by LLMs. In view of developing near-term solutions, the research seeks to answer the question: "How do we build a trustworthy and reliable network of semi-autonomous agents which represent individuals and organisations on the Web?". After identifying key requirements, the paper presents a demo for a sample use case of a generic personal assistant. This is implemented using (Notation3) rules to enforce safety guarantees around belief, data sharing and data usage and LLMs to allow natural language interaction with users and serendipitous dialogues between software agents.
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