Learning to Solve Stochastic Multi-Agent Path Finding

International audienceIn large transportation networks, real-time traffic management is essential to minimize disruptions and maximize punctuality. This is especially true for railway systems, where delays can easily propagate from one train to the next due to infrastructure constraints. We propose novel algorithms to tackle this problem, using the Flatland challenge as a testing ground