提出自适应智能代理委派框架，实现动态任务分配与权责清晰交接。
Intelligent AI Delegation
- 构建包含权责转移与信任机制的动态委派流程
- 支持复杂网络中人机协同的灵活任务分解与执行
- 适用于未来智能体网络中的标准化协作协议
AI 代理正具备处理日益复杂任务的能力。为达成更宏大的目标，它们需能将问题合理分解为可管理的子任务，并安全地委派给其他 AI 代理或人类。然而，现有任务分解与委派方法依赖简单启发式规则，难以动态适应环境变化，且对意外失败缺乏鲁棒性。本文提出一种自适应智能代理委派框架，包含一系列涉及任务分配的决策，整合了权责转移、责任归属、问责机制、角色与边界清晰界定、意图明确表达，以及双方（或多方）间建立信任的机制。该框架适用于复杂委派网络中的人类与 AI 委托方和受托方，旨在推动新兴智能体网络中协作协议的发展。
原文摘要 · Abstract (English)
AI agents are able to tackle increasingly complex tasks. To achieve more ambitious goals, AI agents need to be able to meaningfully decompose problems into manageable sub-components, and safely delegate their completion across to other AI agents and humans alike. Yet, existing task decomposition and delegation methods rely on simple heuristics, and are not able to dynamically adapt to environmental changes and robustly handle unexpected failures. Here we propose an adaptive framework for intelligent AI delegation - a sequence of decisions involving task allocation, that also incorporates transfer of authority, responsibility, accountability, clear specifications regarding roles and boundaries, clarity of intent, and mechanisms for establishing trust between the two (or more) parties. The proposed framework is applicable to both human and AI delegators and delegatees in complex delegation networks, aiming to inform the development of protocols in the emerging agentic web.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。