Crucially, this distribution of border points is agnostic of routing speed profiles. It’s based only on whether a road is passable or not. This means the same set of clusters and border points can be used for all car routing profiles (default, shortest, fuel-efficient) and all bicycle profiles (default, prefer flat terrain, etc.). Only the travel time/cost values of the shortcuts between these points change based on the profile. This is a massive factor in keeping storage down – map data only increased by about 0.5% per profile to store this HH-Routing structure!
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// A minimal writer implementation — just an object with methods
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如何构建智能体有了理想的标杆，我们怎么构建智能体？基本逻辑很简单：以可获取的最“聪明”、理想的模型为核心（大脑），通过软件工程来搭建一个系统，弥补模型的不足，尽量逼近理想智能体的形态。