发表机构
SuperAgentX AI（SuperAgentX AI）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对企业AI向操作系统演进带来的治理碎片化问题，提出统一策略架构UPA，通过统一策略模型覆盖智能体、工具及交互，扩展运行时义务与审计，奠定安全可问责治理基础。
AI 中文摘要
企业AI正在演变为企业操作系统，其中自主AI智能体能够规划、推理、使用记忆、调用工具、执行工作流，并与其他智能体协作。这种转变带来了新的治理挑战：现有的授权、安全、护栏和合规机制是分散的，并非为将自主AI作为统一系统进行治理而设计。本文介绍了统一策略架构（UPA），一种面向企业AI操作系统的治理架构。UPA提供了一种统一的策略模型，用于治理AI与智能体、工具、工作流、记忆、企业资源、智能体间交互以及企业业务规则。它将策略控制从授权扩展到包括运行时义务、人工审批、合规性、审计证据和治理评估。我们展示了UPA的治理模型、声明式策略语言基础、策略评估语义、可扩展插件、行业策略包以及企业治理评估框架。我们还确定了多智能体协调、来源感知策略和有状态运行时治理的扩展方向。UPA为构建安全、可问责和可治理的自主AI企业操作系统奠定了基础。
英文摘要
Enterprise AI is evolving into an Enterprise Operating System where autonomous AI agents can plan, reason, use memory, invoke tools, execute workflows, and collaborate with other agents. This shift creates a new governance challenge: existing authorization, security, guardrails, and compliance mechanisms are fragmented and are not designed to govern autonomous AI as a unified system. This paper introduces the Unified Policy Architecture (UPA), a governance architecture for Enterprise AI Operating Systems. UPA provides a unified policy model for governing AI and agents, tools, workflows, memory, enterprise resources, and agent-to-agent interactions and enterprise business rules. It extends policy control beyond authorisation to include runtime obligations, human approvals, compliance, audit evidence, and governance evaluation. We present UPA's governance model, declarative policy language foundations, policy evaluation semantics, extensible plugins, industry policy packs, and an evaluation framework for enterprise governance. We also identify extensions for multi-agent coordination, provenance-aware policies, and stateful runtime governance. UPA provides a foundation for building secure, accountable, and governable Enterprise Operating Systems for autonomous AI.
Comments58 pages, 6 figures. Includes appendices with the DGPL grammar, SID registry, EAGBench benchmark specification, extended governance models, and policy examples
