no code implementations • 27 Dec 2023 • Chendi Qu, Jianping He, Xiaoming Duan
Designing controllers to generate various trajectories has been studied for years, while recently, recovering an optimal controller from trajectories receives increasing attention.
no code implementations • 27 Dec 2023 • Chendi Qu, Jianping He, Xiaoming Duan, Jiming Chen
A simplistic model is less likely to contain the real reward function, while a model with high complexity leads to substantial computation cost and risks overfitting.
no code implementations • 28 Sep 2023 • Yiming Li, Jianfu Li, Jianping He, Cui Tao
Though Vaccines are instrumental in global health, mitigating infectious diseases and pandemic outbreaks, they can occasionally lead to adverse events (AEs).
no code implementations • 28 Aug 2023 • Xiangyu Mao, Jianping He
In this paper, we investigate the problem of dynamic unidentifiability and design the controller to make the system dynamics unidentifiable.
no code implementations • 31 Jul 2023 • Yushan Li, Zitong Wang, Jianping He, Cailian Chen, Xinping Guan
More importantly, we amend the noise design by introducing one-lag time dependence, achieving the zero state deviation and the non-zero topology inference error in the asymptotic sense simultaneously.
no code implementations • 20 Jan 2023 • Haoxuan Pan, Deheng Ye, Xiaoming Duan, Qiang Fu, Wei Yang, Jianping He, Mingfei Sun
We show that, despite such state distribution shift, the policy gradient estimation bias can be reduced in the following three ways: 1) a small learning rate; 2) an adaptive-learning-rate-based optimizer; and 3) KL regularization.
1 code implementation • 28 Nov 2022 • Xuechao Zhang, Xuda Ding, Yi Ren, Yu Zheng, Chongrong Fang, Jianping He
Then, we form a single quantity that measures the sensing quality of the targets by the camera network.
no code implementations • 19 Jun 2022 • Chendi Qu, Jianping He, Jialun Li
This paper aims at the trade-off between the control performance and state unpredictability of mobile agents in long time horizon.
no code implementations • 14 May 2022 • Xuda Ding, Han Wang, Jianping He, Cailian Chen, Xinping Guan
The variances of the estimation error and the fluctuations in performance are smaller with a properly-designed parameter $\gamma$ compared with the OLS methods.
no code implementations • 7 May 2022 • Jianping He, Yushan Li, Lin Cai, Xinping Guan
Considering the latest inference attacks that enable stealthy and precise attacks into NDSs with observation-based learning, this article focuses on a new security aspect, i. e., how to protect control mechanism secrets from inference attacks, including state information, interaction structure and control laws.
no code implementations • 30 Apr 2022 • Yushan Li, Jianping He, Lin Cai, Xinping Guan
We focus on the local topology inference problem of MRNs under formation control, where an inference robot with limited observation range can manoeuvre among the formation robots.
no code implementations • 28 Apr 2022 • Xuda Ding, Han Wang, Jianping He, Cailian Chen, Kostas Margellos, Antonis Papachristodoulou
Simulations demonstrates that BRSCA has a higher probability of finding feasible solutions, reduces the computation time by about 17. 4% and the energy cost by about four times compared to other methods in the literature.
no code implementations • 22 Feb 2022 • Wenzhe Zheng, Zhiyu He, Jianping He, Chengcheng Zhao, Chongrong Fang
We characterize the adverse impact of misbehaving nodes in a distributed manner via two-hop communication information and develop a deterministic detection-compensation-based consensus (D-DCC) algorithm with a decaying fault-tolerant error bound.
no code implementations • 2 Feb 2022 • Xiangyu Mao, Jianping He, Chengcheng Zhao
Next, an input design method is proposed to deal with the uncertainty and obtain stable identification results by minimizing the variance.
no code implementations • 4 Jun 2021 • Yushan Li, Jianping He, Xuda Ding, Lin Cai, Xinping Guan
The security of mobile robotic networks (MRNs) has been an active research topic in recent years.
no code implementations • 2 Jun 2021 • Yushan Li, Jianping He, Cailian Chen, Xinping Guan
Along with this line, we analyze the non-asymptotic inference performance of the proposed method by taking the OLS estimator as a reference, covering both asymptotically and marginally stable systems.
no code implementations • 2 Nov 2018 • Xiaoyu Wang, Cailian Chen, Yang Min, Jianping He, Bo Yang, Yang Zhang
Traffic prediction is a fundamental and vital task in Intelligence Transportation System (ITS), but it is very challenging to get high accuracy while containing low computational complexity due to the spatiotemporal characteristics of traffic flow, especially under the metropolitan circumstances.