标题： EconAgentic 在 DePIN 市场中的应用：一种用于去中心化物理基础设施共享经济的大语言模型方法 显示英文标题

标题： EconAgentic in DePIN Markets: A Large Language Model Approach to the Sharing Economy of Decentralized Physical Infrastructure

摘要： 去中心化物理基础设施（DePIN）市场正在通过基于代币的经济和管理去中心化操作的智能合约，革新共享经济。 到2024年，DePIN项目已超过100亿美元的市值，凸显了其快速增长。 然而，这些市场的无监管特性，加上在智能合约中自主部署的AI代理，引入了诸如效率低下和与人类价值观潜在不一致等风险。 为解决这些问题，我们引入了EconAgentic，这是一个由大型语言模型（LLM）驱动的框架，旨在缓解这些挑战。 我们的研究集中在三个关键领域：1）建模DePIN市场的动态演变，2）评估利益相关者的行动及其经济影响，3）分析宏观经济指标以使市场结果与社会目标保持一致。 通过EconAgentic，我们模拟AI代理如何响应代币激励、投资基础设施以及适应市场状况，并将AI驱动的决策与人类启发式基准进行比较。 我们的结果表明，EconAgentic为DePIN市场的效率、包容性和稳定性提供了有价值的见解，有助于学术理解以及去中心化、代币化经济的设计和治理的实际改进。 显示英文摘要

摘要： The Decentralized Physical Infrastructure (DePIN) market is revolutionizing the sharing economy through token-based economics and smart contracts that govern decentralized operations. By 2024, DePIN projects have exceeded \$10 billion in market capitalization, underscoring their rapid growth. However, the unregulated nature of these markets, coupled with the autonomous deployment of AI agents in smart contracts, introduces risks such as inefficiencies and potential misalignment with human values. To address these concerns, we introduce EconAgentic, a Large Language Model (LLM)-powered framework designed to mitigate these challenges. Our research focuses on three key areas: 1) modeling the dynamic evolution of DePIN markets, 2) evaluating stakeholders' actions and their economic impacts, and 3) analyzing macroeconomic indicators to align market outcomes with societal goals. Through EconAgentic, we simulate how AI agents respond to token incentives, invest in infrastructure, and adapt to market conditions, comparing AI-driven decisions with human heuristic benchmarks. Our results show that EconAgentic provides valuable insights into the efficiency, inclusion, and stability of DePIN markets, contributing to both academic understanding and practical improvements in the design and governance of decentralized, tokenized economies.