|
|
|
|
|
Shiva Raj Pokhrel, Jonathan Kua, Deol Satish, Sebnem Ozer, Jeff Howe and Anwar Walid
We introduce a novel multipath data transport approach at the transport layer referred to as ?Deep Deterministic Policy Gradient for Multipath Performance-oriented Congestion Control? (DDPG-MPCC), which leverages deep reinforcement learning to enhance co...
ver más
|
|
|
|
|
|
|
|
|
|
|
Juyao Wei, Zhenggang Lu, Zheng Yin and Zhipeng Jing
This paper presents a novel data-driven multiagent reinforcement learning (MARL) controller for enhancing the running stability of independently rotating wheels (IRW) and reducing wheel?rail wear. We base our active guidance controller on the multiagent ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yuting Chen, Pengjun Zhao, Yi Lin, Yushi Sun, Rui Chen, Ling Yu and Yu Liu
Precise identification of spatial unit functional features in the city is a pre-condition for urban planning and policy-making. However, inferring unknown attributes of urban spatial units from data mining of spatial interaction remains a challenge in ge...
ver más
|
|
|
|
|
|
|
|
|
|
|
Fahad Alqahtani, Mohammed Almutairi and Frederick T. Sheldon
This study provides a comprehensive review and comparative analysis of existing Information Flow Tracking (IFT) tools which underscores the imperative for mitigating data leakage in complex cloud systems. Traditional methods impose significant overhead o...
ver más
|
|
|
|
|
|
|
|
|
|
|
Minseok Kong and Jungmin So
There are several automated stock trading programs using reinforcement learning, one of which is an ensemble strategy. The main idea of the ensemble strategy is to train DRL agents and make an ensemble with three different actor?critic algorithms: Advant...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shaowei Li, Yongchao Wang, Yaoming Zhou, Yuhong Jia, Hanyue Shi, Fan Yang and Chaoyue Zhang
Multiple unmanned aerial vehicle (multi-UAV) cooperative air combat, which is an important form of future air combat, has high requirements for the autonomy and cooperation of unmanned aerial vehicles. Therefore, it is of great significance to study the ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiachi Zhao, Jun Li and Lifang Zeng
Birds and experienced glider pilots frequently use atmospheric updrafts for long-distance flight and energy conservation, with harvested energy from updrafts serving as the foundation. Inspired by their common characteristics in autonomous soaring, a rei...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lihan Chen, Lihong Xu and Ruihua Wei
Due to the complex coupling of greenhouse environments, a number of challenges have been encountered in the research of automatic control in Venlo greenhouses. Most algorithms are only concerned with accuracy, yet energy-saving control is of great import...
ver más
|
|
|
|
|
|
|
|
|
|
|
Cihan Ates, Dogan Bicat, Radoslav Yankov, Joel Arweiler, Rainer Koch and Hans-Jörg Bauer
In this study, we propose a population-based, data-driven intelligent controller that leverages neural-network-based digital twins for hypothesis testing. Initially, a diverse set of control laws is generated using genetic programming with the digital tw...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ezra Wari, Weihang Zhu and Gino Lim
This paper proposes a continuous state partially observable Markov decision process (POMDP) model for the corrosion maintenance of oil and gas pipelines. The maintenance operations include complex and extensive activities to detect the corrosion type, de...
ver más
|
|
|
|
|
|