We explored standard advanced algorithms like Contraction Hierarchies (CH), known for their speed. But they presented their own set of deal-breakers for OsmAnd:
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Accuse the agent of potentially cheating its algorithm implementation while pursuing its optimizations, so tell it to optimize for the similarity of outputs against a known good implementation (e.g. for a regression task, minimize the mean absolute error in predictions between the two approaches)