Machine Learning in Urban Decision-Making: Potential, Challenges, and Experiences

In this review paper, the authors highlight Machine Learning (ML) applications to assess their usefulness quantitatively and qualitatively in urban planning decision-making processes. The ML algorithms and broader Artificial Intelligence (AI) seem to have a more comprehensive application range and the ability to acquire information and knowledge even from spurious datasets. The current research aims to briefly define the emergent field of the most used algorithms of machine learning in urban planning and their usage in decision-making as well as analyzing their potentials and limitations. They have been done by presenting some classifications based on a literature review and finally providing a qualitative assessment of the described algorithms. This assessment puts into evidence the advantages and disadvantages of using the present algorithms in Urban planning decision-making usefulness.