activity
20222024
most citedMobility-Aware Computation Offloading for Swarm Robotics using Deep Reinforcement Learning

13 citations · 18 across the 15 of their papers we have counts for

collaborators

15 papers

cs.LG2024

Is AI Robust Enough for Scientific Research?

Jun-Jie Zhang, Jiahao Song, Xiu-Cheng Wang +14

We uncover a phenomenon largely overlooked by the scientific community utilizing AI: neural networks exhibit high susceptibility to minute perturbations, resulting in significant d…

cs.IT2024

GNN-Empowered Effective Partial Observation MARL Method for AoI Management in Multi-UAV Network

Yuhao Pan, Xiucheng Wang, Zhiyao Xu +3

Unmanned Aerial Vehicles (UAVs), due to their low cost and high flexibility, have been widely used in various scenarios to enhance network performance. However, the optimization of…

cs.LG2024

Reliable Projection Based Unsupervised Learning for Semi-Definite QCQP with Application of Beamforming Optimization

Xiucheng Wang, Qi Qiu, Nan Cheng

In this paper, we investigate a special class of quadratic-constrained quadratic programming (QCQP) with semi-definite constraints. Traditionally, since such a problem is non-conve…

cs.AI2024

Trapezoidal Gradient Descent for Effective Reinforcement Learning in Spiking Networks

Yuhao Pan, Xiucheng Wang, Nan Cheng +1

With the rapid development of artificial intelligence technology, the field of reinforcement learning has continuously achieved breakthroughs in both theory and practice. However,…

eess.SY2024

Constructing and Evaluating Digital Twins: An Intelligent Framework for DT Development

Longfei Ma, Nan Cheng, Xiucheng Wang +4

The development of Digital Twins (DTs) represents a transformative advance for simulating and optimizing complex systems in a controlled digital space. Despite their potential, the…

eess.SY20241 cited

Toward Enhanced Reinforcement Learning-Based Resource Management via Digital Twin: Opportunities, Applications, and Challenges

Nan Cheng, Xiucheng Wang, Zan Li +3

This article presents a digital twin (DT)-enhanced reinforcement learning (RL) framework aimed at optimizing performance and reliability in network resource management, since the t…