用大模型模拟去中心化基建市场，让AI更懂人类价值观。
EconAgentic in DePIN Markets: A Large Language Model Approach to the Sharing Economy of Decentralized Physical Infrastructure
- 用大语言模型建模去中心化基建市场的动态演化
- 发现AI在激励下能提升市场效率与公平性
- 适合研究区块链经济与AI治理的学者和开发者
去中心化物理基础设施（DePIN）市场正通过基于代币的经济机制和智能合约推动共享经济变革。截至2024年，DePIN项目市值已超100亿美元，展现出快速增长势头。然而，市场缺乏监管，加上智能合约中自主部署的AI代理可能引发效率低下和与人类价值观错位等问题。为此，我们提出EconAgentic——一个由大语言模型驱动的框架，用于应对这些挑战。研究聚焦三大方向：1）建模DePIN市场的动态演化；2）评估利益相关方行为及其经济影响；3）分析宏观经济指标以实现市场结果与社会目标对齐。通过EconAgentic，我们模拟了AI代理在代币激励下的响应、基础设施投资及市场适应行为，并与人类启发式决策基准进行对比。结果显示，该框架可为理解DePIN市场的效率、包容性与稳定性提供关键洞见，有助于深化学术认知并优化去中心化、代币化经济的设计与治理。
原文摘要 · Abstract (English)
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.
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