Maximum target coverage by adjusting the orientation of distributed sensors is an important problem in directional sensor networks (DSNs). This problem is.

Oct 25, 2020 · We propose a Hierarchical Target-oriented Multi-Agent Coordination (HiT-MAC), which decomposes the target coverage problem into two-level tasks.

Summary and Contributions: The authors propose a reinforcement learning approach to the target coverage problems in directional sensor network.

This repository is the official implementation of Learning Multi-Agent Coordination for Enhancing Target Coverage in Directional Sensor Networks.

A Hierarchical Target-oriented Multi-Agent Coordination (HiT-MAC), which decomposes the target coverage problem into two-level tasks: targets assignment by ...

This paper proposes multi-agent hierarchical RL method to the target coverage problems in directional sensor networks. Empirical results are provided to ...

Dec 6, 2020 · Maximum target coverage by adjusting the orientation of distributed sensors is an important problem in directional sensor networks (DSNs).

May 5, 2023 · Learning Multi-Agent Coordination for Enhancing Target Coverage in Directional Sensor Networks Download PDF · Open Website · Jing Xu, Fangwei ...

Oct 25, 2020 · Maximum target coverage by adjusting the orientation of distributed sensors is an important problem in directional sensor networks (DSNs).

Learning multi-agent coordination for enhancing target coverage in directional sensor networks. J Xu, F Zhong, Y Wang. Advances in Neural Information Processing ...