SORA-ATMAS：面向未来智慧城市的自适应信任管理与多大语言模型对齐治理
SORA-ATMAS: Adaptive Trust Management and Multi-LLM Aligned Governance for Future Smart Cities
AI总结：
针对智慧城市中智能体AI部署的治理、风险与合规挑战，提出SORA-ATMAS框架，通过自适应信任管理与多LLM对齐治理实现安全高效决策，经实验验证其性能、可扩展性与跨域互操作性。
摘要：
智慧城市的快速发展使得人们愈发依赖智能互联服务来优化基础设施、资源配置与市民福祉。智能体AI（Agentic AI）凭借支持自主决策与自适应协调的能力，已成为核心赋能技术，可让城市系统对动态状况做出实时响应。其优势在交通等领域尤为显著：通过整合交通数据、天气预报与安全传感器，可实现动态路径规划与更快的险情响应。然而，它在异构智慧城市生态中的部署带来了关键的治理、风险与合规（GRC）挑战，包括去中心化基础设施中的问责制、数据隐私与监管对齐问题。\n我们通过三个领域智能体（气象、交通、安全）对SORA-ATMAS进行了评估，结果表明其治理策略（含高风险场景的回退机制）能有效引导多个大语言模型（LLM，包括GPT、Grok、DeepSeek）生成领域优化且符合政策的输出，各智能体的平均绝对误差（MAE）平均降低35%。实验结果显示：气象监测稳定，高风险交通平台的处理效果达0.85，安全/消防场景下的自适应信任调节效果达0.65。对3智能体部署的运行时分析验证了其可扩展性：吞吐量为每秒13.8-17.2次请求，执行时间低于72毫秒，治理延迟低于100毫秒；分析预测显示其在更大规模下仍能保持性能。跨域规则保障了安全互操作，仅在气象条件验证通过时才允许交通改道。\n这些结果证实SORA-ATMAS是一个符合监管要求、具备上下文感知能力且可验证的治理框架，能将分布式智能体的输出整合为可问责的实时决策，为智慧城市管理提供了有韧性的基础。
英文摘要：
The rapid evolution of smart cities has increased the reliance on intelligent interconnected services to optimize infrastructure, resources, and citizen well-being. Agentic AI has emerged as a key enabler by supporting autonomous decision-making and adaptive coordination, allowing urban systems to respond in real time to dynamic conditions. Its benefits are evident in areas such as transportation, where the integration of traffic data, weather forecasts, and safety sensors enables dynamic rerouting and a faster response to hazards. However, its deployment across heterogeneous smart city ecosystems raises critical governance, risk, and compliance (GRC) challenges, including accountability, data privacy, and regulatory alignment within decentralized infrastructures. Evaluation of SORA-ATMAS with three domain agents (Weather, Traffic, and Safety) demonstrated that its governance policies, including a fallback mechanism for high-risk scenarios, effectively steer multiple LLMs (GPT, Grok, DeepSeek) towards domain-optimized, policy-aligned outputs, producing an average MAE reduction of 35% across agents. Results showed stable weather monitoring, effective handling of high-risk traffic plateaus 0.85, and adaptive trust regulation in Safety/Fire scenarios 0.65. Runtime profiling of a 3-agent deployment confirmed scalability, with throughput between 13.8-17.2 requests per second, execution times below 72~ms, and governance delays under 100 ms, analytical projections suggest maintained performance at larger scales. Cross-domain rules ensured safe interoperability, with traffic rerouting permitted only under validated weather conditions. These findings validate SORA-ATMAS as a regulation-aligned, context-aware, and verifiable governance framework that consolidates distributed agent outputs into accountable, real-time decisions, offering a resilient foundation for smart-city management.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
