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arXiv Machine Learning By Chenyang Yuan, Xiaoyuan Cheng

CityDeploy-Bench: Benchmarking Physics-Grounded Spatial Set Planning for Multi-Transmitter Network Deployment

Read the original on arXiv Machine Learning →

CityDeploy-Bench is a new benchmark that frames multi‑transmitter wireless network deployment as a physics‑grounded spatial set planning problem, verified by a unified ray‑tracing engine. It decouples utility representation from planning dynamics, allowing systematic comparison of direct scalar rewards, relational models, and higher‑order interaction structures across different planners. Experiments show that as physical coupling increases, deployment quality hinges on capturing collective transmitter interactions; stronger search alone cannot compensate for missing relational structure, highlighting the coordination nature of the problem.

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