Numerical Simulator for Target Coverage Problem

该数据集通过构建一个数值模拟器来模拟真实世界中方向传感器网络（DSN）的目标覆盖问题。该模拟器对提出的HiT-MAC方法与其他多智能体强化学习（MARL）方法以及一种启发式集中方法进行了评估，并支持进行消融研究。研究的任务是方向传感器网络中的目标覆盖问题。This dataset develops a numerical simulator to model the target coverage problem of directional sensor networks (DSN) in real-world scenarios. The simulator evaluates the proposed HiT-MAC method against other multi-agent reinforcement learning (MARL) methods and a heuristic centralized approach, and supports ablation studies. The core research task of this dataset centers on the target coverage problem in directional sensor networks.