用AI代理系统实现黄金资产链上化，1.2秒完成发行，0.5%低交易价差。
AI Agent Architecture for Decentralized Trading of Alternative Assets
- 分角色AI代理协同工作，链上合约控风险，链下智能体做决策。
- 链上发行<1.2秒，市场做市价差低于0.5%，支持5000笔/秒吞吐。
- 抗攻击检测快至10秒，支持多签更新与社区投票治理，适合金融级应用。
去中心化交易真实世界另类资产（如黄金）需连接物理托管与区块链系统，同时满足合规、流动性与风险管理要求。我们提出GoldMine OS——一个面向研究的架构，采用多个专用AI代理自动且安全地将实物黄金转化为基于区块链的稳定币（OZ）。该方案结合链上智能合约进行关键风险控制，链下AI代理负责决策，融合区块链的透明性与AI自动化灵活性。系统包含四个协作代理（合规、铸币、做市、风控）及一个协调核心，并通过模拟与受控试点部署进行评估。实验显示，原型系统可在1.2秒内完成按需铸币，较人工流程快逾100倍；做市代理在波动环境下仍维持0.5%以下的窄价差；故障注入测试表明：预言机价格欺骗攻击10秒内被检测并阻断，模拟金库误报触发即时铸币暂停，用户影响极小。基准测试中系统可扩展至每秒5000笔交易、支持10000名并发用户。结果表明，基于AI代理的去中心化另类资产交易所可满足严苛性能与安全要求。我们讨论了其对传统非流动性资产普惠化的意义，并阐述治理模型——多签代理更新与链上社区投票设定风险参数——提供了持续透明、可适应及形式化系统完整性保障。
原文摘要 · Abstract (English)
Decentralized trading of real-world alternative assets (e.g., gold) requires bridging physical asset custody with blockchain systems while meeting strict requirements for compliance, liquidity, and risk management. We present GoldMine OS, a research oriented architecture that employs multiple specialized AI agents to automate and secure the tokenization and exchange of physical gold into a blockchain based stablecoin ("OZ"). Our approach combines on chain smart contracts for critical risk controls with off chain AI agents for decision making, blending the transparency and reliability of blockchains with the flexibility of AI driven automation. We describe four cooperative agents (Compliance, Token Issuance, Market Making, and Risk Control) and a coordinating core, and evaluate the system through simulation and a controlled pilot deployment. In experiments the prototype delivers on demand token issuance in under 1.2 s, more than 100 times faster than manual workflows. The Market Making agent maintains tight liquidity with spreads often below 0.5 percent even under volatile conditions. Fault injection tests show resilience: an oracle price spoofing attack is detected and mitigated within 10 s, and a simulated vault mis reporting halts issuance immediately with minimal user impact. The architecture scales to 5000 transactions per second with 10000 concurrent users in benchmarks. These results indicate that an AI agent based decentralized exchange for alternative assets can satisfy rigorous performance and safety requirements. We discuss broader implications for democratizing access to traditionally illiquid assets and explain how our governance model -- multi signature agent updates and on chain community voting on risk parameters -- provides ongoing transparency, adaptability, and formal assurance of system integrity.
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