no code implementations • 19 Nov 2023 • Lei Lei, Tong Liu, Kan Zheng, Xuemin, Shen
We focused on the PC sub-problem and proposed the MTCC-PC algorithm to learn an optimal PC policy given an RRA policy.
no code implementations • 19 Nov 2023 • Tong Liu, Lei Lei, Kan Zheng, Xuemin, Shen
It is proved that the optimal policy for the augmented state MDP is optimal for the original PC problem with observation delay.
no code implementations • 28 Apr 2023 • Jiaju Qi, Lei Lei, Kan Zheng, Simon X. Yang, Xuemin, Shen
In this paper, we investigate the scheduling issue of diesel generators (DGs) in an Internet of Things (IoT)-Driven isolated microgrid (MG) by deep reinforcement learning (DRL).
no code implementations • 15 Jun 2022 • Tong Liu, Lei Lei, Kan Zheng, Kuan Zhang
Deep Reinforcement Learning (DRL) is regarded as a potential method for car-following control and has been mostly studied to support a single following vehicle.
no code implementations • 3 Jun 2022 • Jiaju Qi, Lei Lei, Kan Zheng, Simon X. Yang
Nowadays, the application of microgrids (MG) with renewable energy is becoming more and more extensive, which creates a strong need for dynamic energy management.
no code implementations • 28 Mar 2022 • Lei Lei, Tong Liu, Kan Zheng, Lajos Hanzo
In this context, the value of V2X communications for DRL-based platoon controllers is studied with an emphasis on the tradeoff between the gain of including exogenous information in the system state for reducing uncertainty and the performance erosion due to the curse-of-dimensionality.
no code implementations • 19 Mar 2022 • Pengzun Gao, Long Zhao, Kan Zheng, Pingzhi Fan
The dual-function radar communication (DFRC) is an essential technology in Internet of Vehicles (IoV).
no code implementations • 26 Aug 2021 • Jiaju Qi, Qihao Zhou, Lei Lei, Kan Zheng
This paper presents a comprehensive survey of Federated Reinforcement Learning (FRL), an emerging and promising field in Reinforcement Learning (RL).
no code implementations • 5 Jun 2020 • Yue Tan, Chunjing Hu, Kuan Zhang, Kan Zheng, Ethan A. Davis, Jae Sung Park
Anomaly detection for non-linear dynamical system plays an important role in ensuring the system stability.
no code implementations • 7 Feb 2020 • Lei Lei, Yue Tan, Glenn Dahlenburg, Wei Xiang, Kan Zheng
Microgrids (MGs) are small, local power grids that can operate independently from the larger utility grid.
no code implementations • 22 Jul 2019 • Lei Lei, Yue Tan, Kan Zheng, Shiwen Liu, Kuan Zhang, Xuemin, Shen
Next, a comprehensive survey of the state-of-art research on DRL for AIoT is presented, where the existing works are classified and summarized under the umbrella of the proposed general DRL model.
no code implementations • 19 Jun 2019 • Lei Lei, Huijuan Xu, Xiong Xiong, Kan Zheng, Wei Xiang, Xianbin Wang
By leveraging the concept of mobile edge computing (MEC), massive amount of data generated by a large number of Internet of Things (IoT) devices could be offloaded to MEC server at the edge of wireless network for further computational intensive processing.
no code implementations • 17 Apr 2019 • Lei Lei, Jiaju Qi, Kan Zheng
In order to address the above limitations, we propose a patent analytics based on feature vector space model (FVSM), where the FVSM is constructed by mapping patent documents to feature vectors extracted by convolutional neural networks (CNN).
no code implementations • 25 Feb 2019 • Shiwen Liu, Kan Zheng, Long Zhao, Pingzhi Fan
Experimental results show that the HMMs trained with the continuous characterization of mobility features can give a higher prediction accuracy when they are used for predicting driving intentions.
no code implementations • 25 Feb 2019 • Lingyi Han, Kan Zheng, Long Zhao, Xianbin Wang, Xuemin Shen
Therefore, a framework combining with a deep clustering (DeepCluster) module is developed for STTP at largescale networks in this paper.
no code implementations • 12 Feb 2019 • Yue Tan, Kan Zheng, Lei Lei
In order to maximize detection precision rate as well as the recall rate, this paper proposes an in-vehicle multi-source fusion scheme in Keyword Spotting (KWS) System for vehicle applications.