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English(EN) Towards Adaptive and Real-Survey-Aligned Simulated Urban Mobility Behaviour of Generative Agents

生成式智能体在模拟城市出行行为方面展现出潜力

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了一种使用生成式智能体（GAs）模拟城市出行行为的新方法，该方法与真实世界的出行调查数据一致。经过调整提示的 GAs 在模仿模式划分方面展现出潜力，且没有中断，但它们在逐次出行匹配调查数据方面仍有不足。值得注意的是，GAs 展现出适应不可预见事件的能力，并且一种名为 Jev-1.13 TypeSafe 的类型化分类器在不生成文本的情况下取得了优异的结果，这表明了复杂决策模拟的替代方法。 AI

影响 这项研究通过实现更真实的出行行为模拟，有望改善城市规划和交通服务。

排序理由 学术论文，详细介绍了一种新的基于智能体的模拟方法。

在 arXiv cs.MA (Multiagent) 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

生成式智能体在模拟城市出行行为方面展现出潜力

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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Yves Bru, Kamaldeep Singh Oberoi, Benoit Gaudou ·

    迈向生成式智能体自适应且与真实调查一致的城市出行行为

    arXiv:2610.22407v1 Announce Type: cross Abstract: In existing agent-based simulations of multimodal urban mobility, agents, representing humans, choose their travel modes either using discrete choice or machine learning models fitted on structured travel survey data, or with rule…

  2. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Benoit Gaudou ·

    迈向生成式智能体自适应且与真实调查一致的城市出行行为模拟

    In existing agent-based simulations of multimodal urban mobility, agents, representing humans, choose their travel modes either using discrete choice or machine learning models fitted on structured travel survey data, or with rules explicitly written by the domain experts. Such a…

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