Road network shortest path distance calculation method based on reinforcement learning

The invention discloses a road network shortest path distance calculation method based on reinforcement learning, and relates to the technical field of computer data management, and the method comprises the steps: converting a shortest path distance index construction process into a Markov decision process; based on a Markov decision process, constructing and training a strategy model based on reinforcement learning; constructing a 2-hop label index of a hierarchical structure by utilizing the strategy model; the method comprises the following steps of: optimizing a 2-hop label index; and processing the query by using the optimized 2-hop label index, and returning a query result. According to the method, the constructed index structure is more balanced, the occupied space is small, the query speed is higher, the practicability is high, the intelligence is high, the model index construction speed is high, and the generalization performance is good. 本发明公开了一种基于强化学习的路网最短路径距离计算方法，涉及计算机数据管理技术领域，包括：将构建最短路径距离索引的过程转化成