6 citations · 12 across the 7 of their papers we have counts for
7 papers
Rocket Landing Control with Random Annealing Jump Start Reinforcement Learning
Yuxuan Jiang, Yujie Yang, Zhiqian Lan +6
Rocket recycling is a crucial pursuit in aerospace technology, aimed at reducing costs and environmental impact in space exploration. The primary focus centers on rocket landing co…
Policy Bifurcation in Safe Reinforcement Learning
Wenjun Zou, Yao Lyu, Jie Li +7
Safe reinforcement learning (RL) offers advanced solutions to constrained optimal control problems. Existing studies in safe RL implicitly assume continuity in policy functions, wh…
DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models
Wei He, Kai Han, Yehui Tang +4
Large language models (LLMs) face a daunting challenge due to the excessive computational and memory requirements of the commonly used Transformer architecture. While state space m…
On the Stability of Datatic Control Systems
Yujie Yang, Zhilong Zheng, Shengbo Eben Li
The development of feedback controllers is undergoing a paradigm shift from (model-driven) control to (data-driven) control. Stability, as a f…
Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
Yinan Zheng, Jianxiong Li, Dongjie Yu +4
Safe offline RL is a promising way to bypass risky online interactions towards safe policy learning. Most existing methods only enforce soft constraints, i.e., constraining safety…
Safe Reinforcement Learning with Dual Robustness
Zeyang Li, Chuxiong Hu, Yunan Wang +2
Reinforcement learning (RL) agents are vulnerable to adversarial disturbances, which can deteriorate task performance or compromise safety specifications. Existing methods either a…