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The two fields of urban planning and artificial intelligence (AI) arose anddeveloped separately. However, there is now cross-pollination and increasinginterest in both fields to benefit from the advances of the other. In thepresent paper, we introduce the importance of urban planning from thesustainability, living, economic, disaster, and environmental perspectives. Wereview the fundamental concepts of urban planning and relate these concepts tocrucial open problems of machine learning, including adversarial learning,generative neural networks, deep encoder-decoder networks, conversational AI,and geospatial and temporal machine learning, thereby assaying how AI cancontribute to modern urban planning. Thus, a central problem is automatedland-use configuration, which is formulated as the generation of land uses andbuilding configuration for a target area from surrounding geospatial, humanmobility, social media, environment, and economic activities. Finally, wedelineate some implications of AI for urban planning and propose key researchareas at the intersection of both topics.

Towards Automated Urban Planning: When Generative and ChatGPT-like AI Meets Urban Planning