让AI像城市规划师一样思考，融合专家工具与自主决策。
Towards Urban Planing AI Agent in the Age of Agentic AI
- 构建能自主决策的智能规划代理，突破传统生成模型预设结构限制。
- 引入城市规划专家工具，增强AI对专业理论与实践的理解能力。
- 适合关注智能城市、人机协同规划的研究者与政策制定者。
生成式AI、大语言模型和智能体式AI虽各自发展，但它们在城市规划领域的融合带来了新机遇。现有研究将城市规划视为生成任务，由AI在地理空间、社会及以人为本的约束下生成用地布局，实现自动化城市设计。然而，现有方法存在两大关键缺陷：一是生成结构需人为预设，如对抗生成、前向/逆向扩散、分层区域-兴趣点结构等均依赖强假设；二是忽视城市规划领域专家开发的实用工具，这些工具基于城市理论指导实践，而纯神经网络方法未加以利用。为此，本文提出未来研究方向——智能体式城市规划AI，呼吁将智能体式AI与参与式城市主义相结合，推动更符合实际的城市规划创新。
原文摘要 · Abstract (English)
Generative AI, large language models, and agentic AI have emerged separately of urban planning. However, the convergence between AI and urban planning presents an interesting opportunity towards AI urban planners. Existing studies conceptualizes urban planning as a generative AI task, where AI synthesizes land-use configurations under geospatial, social, and human-centric constraints and reshape automated urban design. We further identify critical gaps of existing generative urban planning studies: 1) the generative structure has to be predefined with strong assumption: all of adversarial generator-discriminator, forward and inverse diffusion structures, hierarchical zone-POI generative structure are predefined by humans; 2) ignore the power of domain expert developed tools: domain urban planners have developed various tools in the urban planning process guided by urban theory, while existing pure neural networks based generation ignore the power of the tools developed by urban planner practitioners. To address these limitations, we outline a future research direction agentic urban AI planner, calling for a new synthesis of agentic AI and participatory urbanism.
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