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English(EN) Persistent Partners Raise Prices Among Learning Agents

人工智能代理商在与一致的合作伙伴配对时学会提高价格

一篇新发表在arXiv上的研究探讨了定价代理商如何在重复的Bertrand竞争场景中学习设定价格。研究发现,与一致的合作伙伴配对的代理商会持续设定更高的价格,将利润提高了约0.27的竞争利润与垄断利润之间的差距。即使代理商看不到对手的价格,也观察到了这种效应,这表明存在一种学习到的惩罚机制或独立于直接观察的战略定价。使用Qwen2.5模型进行的探索性测试表明,当对手的价格从提示中省略时,会出现类似的定价行为。 AI

影响 展示了人工智能代理商如何发展战略定价行为,可能影响市场动态和竞争。

排序理由 学术论文,详细介绍了代理商学习的实验结果。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.MA (Multiagent) 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

人工智能代理商在与一致的合作伙伴配对时学会提高价格

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学术论文,详细介绍了代理商学习的实验结果。[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) · Xiao Xiao ·

    主要学习代理提高价格

    When pricing agents meet repeatedly on a platform, the platform decides who faces whom. We ask whether that choice moves the prices the agents learn, and whether a rise comes with learned punishment. In a pre-registered randomised experiment in the Bertrand duopoly of Calvano et …