When the Streets Flood, Let the AI Drive: Reinforcement Learning for Climate‑Resilient Cities
A flooded street is not only a drainage problem. It is a transport problem, a budget problem, an insurance problem, a public-trust problem, and, if the city waits long enough, a very expensive lesson in pretending that yesterday’s weather statistics are still a planning manual. Copenhagen is a useful place to begin because the paper’s case is not imaginary. In 2011, the city experienced a major cloudburst that flooded streets, disrupted roads and rail, and caused damage estimated at around 6 billion Danish kroner. The new research paper, Artificial Intelligence for Climate Adaptation: Using Reinforcement Learning for Climate Change-Resilient Transport, uses Copenhagen’s inner city as the testbed for a larger question: how should a city decide where, when, and how much to invest in flood adaptation between 2024 and 2100?1 ...