用区块链监控智能体决策，确保可信可追溯。
A Blockchain-Monitored Agentic AI Architecture for Trusted Perception-Reasoning-Action Pipelines
- 用链式架构记录智能体感知-推理-行动全过程
- 实测在库存、交通、医疗场景中延迟可控且防篡改
- 适合需合规审计的高风险自主系统应用
智能体AI在医疗、智慧城市、数字取证和供应链管理中的自主决策应用日益增长。尽管具备实时推理能力，但其信任度与信息完整性面临挑战。本文提出一种基于LangChain的多智能体系统与许可区块链相结合的统一架构，实现对智能体行为的持续监控、策略执行与不可篡改的审计。该框架将感知-概念化-行动循环与区块链治理层联动，验证输入、评估建议动作并记录执行结果。采用Hyperledger Fabric构建系统，集成MCP动作执行器与LangChain智能体，在智能库存管理、交通信号控制和医疗监测任务中进行实验。结果表明，区块链安全验证能有效防止未经授权操作，全程可追溯，且运行延迟保持在合理范围。该框架为高影响力自主智能体应用提供了既自主又负责任的通用解决方案。
原文摘要 · Abstract (English)
The application of agentic AI systems in autonomous decision-making is growing in the areas of healthcare, smart cities, digital forensics, and supply chain management. Even though these systems are flexible and offer real-time reasoning, they also raise concerns of trust and oversight, and integrity of the information and activities upon which they are founded. The paper suggests a single architecture model comprising of LangChain-based multi-agent system with a permissioned blockchain to guarantee constant monitoring, policy enforcement, and immutable auditability of agentic action. The framework relates the perception conceptualization-action cycle to a blockchain layer of governance that verifies the inputs, evaluates recommended actions, and documents the outcomes of the execution. A Hyperledger Fabric-based system, action executors MCP-integrated, and LangChain agent are introduced and experiments of smart inventory management, traffic-signal control, and healthcare monitoring are done. The results suggest that blockchain-security verification is efficient in preventing unauthorized practices, offers traceability throughout the whole decision-making process, and maintains operational latency within reasonable ranges. The suggested framework provides a universal system of implementing high-impact agentic AI applications that are autonomous yet responsible.
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