activity
20242026
collaborators

7 papers

cs.DM2026

Metropolis-Hastings Sampling of Phylogenetic Networks: Correcting for Symmetries

Leo van Iersel, Remie Janssen, Mark Jones +2

In phylogenetics, Metropolis-Hastings methods are commonly used to sample phylogenetic trees or networks, for example from Bayesian posteriors. These methods generally use transiti…

cs.RO2026

Task-Semantic Graph-Driven Distributed Agent Networking for Underwater Target Tracking

Shengchao Zhu, Guangjie Han, Chuan Lin +1

Autonomous underwater vehicle (AUV) swarms are emerging as intelligent underwater networks, where each node must sense, communicate, process local data, and make decisions under se…

cs.NI2026

Diffusion-Guided Cooperative Policy Learning for Target Tracking Based on Underwater Mobile Agent Networks

Jiaao Ma, Chuan Lin, Guangjie Han +3

Multi-agent reinforcement learning (MARL) provides a promising solution for cooperative target tracking in networks of autonomous underwater vehicles (AUVs). However, existing meth…

cs.RO2026

Multi-AUV Ad-hoc Networks-Based Multi-Target Tracking Based on Scene-Adaptive Embodied Intelligence

Kai Tian, Jialun Wang, Chuan Lin +4

With the rapid advancement of underwater net-working and multi-agent coordination technologies, autonomous underwater vehicle (AUV) ad-hoc networks have emerged as a pivotal framew…

cs.NI2026

DHEA-MECD: An Embodied Intelligence-Powered DRL Algorithm for AUV Tracking in Underwater Environments with High-Dimensional Features

Kai Tian, Chuan Lin, Guangjie Han +4

In recent years, autonomous underwater vehicle (AUV) systems have demonstrated significant potential in complex marine exploration. However, effective AUV-based tracking remains ch…

cs.NI2025

Smart Interrupted Routing Based on Multi-head Attention Mask Mechanism-Driven MARL in Software-defined UASNs

Zhenyu Wang, Chuan Lin, Guangjie Han +3

Routing-driven timely data collection in Underwater Acoustic Sensor Networks (UASNs) is crucial for marine environmental monitoring, disaster warning and underwater resource explor…