1 citations · 1 across the 4 of their papers we have counts for
4 papers
LEED: A Highly Efficient and Scalable LLM-Empowered Expert Demonstrations Framework for Multi-Agent Reinforcement Learning
Tianyang Duan, Zongyuan Zhang, Songxiao Guo +7
Multi-agent reinforcement learning (MARL) holds substantial promise for intelligent decision-making in complex environments. However, it suffers from a coordination and scalability…
Robust Deep Reinforcement Learning in Robotics via Adaptive Gradient-Masked Adversarial Attacks
Zongyuan Zhang, Tianyang Duan, Zheng Lin +8
Deep reinforcement learning (DRL) has emerged as a promising approach for robotic control, but its realworld deployment remains challenging due to its vulnerability to environmenta…
State-Aware Perturbation Optimization for Robust Deep Reinforcement Learning
Zongyuan Zhang, Tianyang Duan, Zheng Lin +7
Recently, deep reinforcement learning (DRL) has emerged as a promising approach for robotic control. However, the deployment of DRL in real-world robots is hindered by its sensitiv…
AGRNav: Efficient and Energy-Saving Autonomous Navigation for Air-Ground Robots in Occlusion-Prone Environments
Junming Wang, Zekai Sun, Xiuxian Guan +6
The exceptional mobility and long endurance of air-ground robots are raising interest in their usage to navigate complex environments (e.g., forests and large buildings). However,…