面向另类资产网络可信代币化的AI治理代理架构
AI-Governed Agent Architecture for Web-Trustworthy Tokenization of Alternative Assets
AI总结：
本文提出一种AI治理代理架构，将智能代理与区块链结合，通过AI驱动的治理层和加密经济激励实现另类资产的可信代币化，并以房地产案例验证其在防欺诈和合规方面的有效性。
摘要：
另类资产代币化正在改变非传统金融工具在网络上的表示和交易方式。然而，确保基于网络的代币化生态系统的可信度面临重大挑战，从验证链下资产数据到执行监管合规均存在困难。本文提出了一种AI治理的代理架构，将智能代理与区块链相结合，以实现另类资产的网络可信代币化。在所提出的架构中，自主代理编排代币化流程（资产验证、估值、合规检查以及生命周期管理），而AI驱动的治理层通过自适应策略和加密经济激励来监控代理行为并强化信任。我们证明该方法增强了资产代币化的透明度、安全性和合规性，解决了围绕数据真实性和欺诈的关键问题。一个关于房地产资产代币化的案例研究说明了该架构如何通过实时AI异常检测和链上执行来降低风险（例如欺诈性挂牌和洗钱）。我们的评估和分析表明，将AI治理与多代理系统及区块链相结合，可以显著增强代币化资产生态系统中的信任。这项工作为网络上可信的资产代币化提供了一个新颖的框架，并为旨在部署安全、合规的代币化平台的从业者提供了见解。
英文摘要：
Alternative Assets tokenization is transforming non-traditional financial instruments are represented and traded on the web. However, ensuring trustworthiness in web-based tokenized ecosystems poses significant challenges, from verifying off-chain asset data to enforcing regulatory compliance. This paper proposes an AI-governed agent architecture that integrates intelligent agents with blockchain to achieve web-trustworthy tokenization of alternative assets. In the proposed architecture, autonomous agents orchestrate the tokenization process (asset verification, valuation, compliance checking, and lifecycle management), while an AI-driven governance layer monitors agent behavior and enforces trust through adaptive policies and cryptoeconomic incentives. We demonstrate that this approach enhances transparency, security, and compliance in asset tokenization, addressing key concerns around data authenticity and fraud. A case study on tokenizing real estate assets illustrates how the architecture mitigates risks (e.g., fraudulent listings and money laundering) through real-time AI anomaly detection and on-chain enforcement. Our evaluation and analysis suggest that combining AI governance with multi-agent systems and blockchain can significantly bolster trust in tokenized asset ecosystems. This work offers a novel framework for trustworthy asset tokenization on the web and provides insights for practitioners aiming to deploy secure, compliant tokenization platforms.
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。
