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English(EN) But How Would AI Agents Run a Town's Economy?

研究发现:AI代理在管理模拟城镇经济方面遇到困难

一项新研究通过在基于真实Pokhara Lakeside地理的封闭经济系统中模拟100个具备记忆功能的LLM代理,探讨了AI代理将如何管理城镇的经济。该模拟运行长达26周,结果显示经济活动显著放缓,即使是大的需求冲击也仅略微增加企业收入和工资,并且大部分现金转移支付仍未被花费。研究发现,LLM的选择显著影响了经济结果,而代理的记忆功能则几乎没有影响。在此次模拟中,经济工具比纯粹的社交工具取得了更大的成功。 AI

影响 表明当前LLM代理在复杂经济管理方面的能力存在局限性,并强调了代理记忆和工具使用方式的重要性。

排序理由 关于AI代理在经济背景下模拟的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.MA (Multiagent) 阅读 →

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研究发现:AI代理在管理模拟城镇经济方面遇到困难

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关于AI代理在经济背景下模拟的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Chetan Phakami Pun ·

    但AI代理将如何运行城镇经济?

    We placed 100 memory-equipped large language model (LLM) agents in charge of a closed, money-conserving spatial economy on real Pokhara Lakeside geography (earning wages, running businesses, setting prices) and ran this multi-agent simulation for up to 26 simulated weeks, well pa…