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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...
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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...
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Sheng Yu, Wei Zhu and Yong Wang
Wargames are essential simulators for various war scenarios. However, the increasing pace of warfare has rendered traditional wargame decision-making methods inadequate. To address this challenge, wargame-assisted decision-making methods that leverage ar...
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Jianya Yuan, Mengxue Han, Hongjian Wang, Bo Zhong, Wei Gao and Dan Yu
Collision avoidance planning has always been a hot and important issue in the field of unmanned aircraft research. In this article, we describe an online collision avoidance planning algorithm for autonomous underwater vehicle (AUV) autonomous navigation...
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Wenting Li, Xiuhui Zhang, Yunfeng Dong, Yan Lin and Hongjue Li
Multi-stage launch vehicles are currently the primary tool for humans to reach extraterrestrial space. The technology of recovering and reusing rockets can effectively shorten rocket launch cycles and reduce space launch costs. With the development of de...
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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...
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Wanli Li, Jiong Li, Ningbo Li, Lei Shao and Mingjie Li
Concerned with the problem of interceptor midcourse guidance trajectory online planning satisfying multiple constraints, an online midcourse guidance trajectory planning method based on deep reinforcement learning (DRL) is proposed. The Markov decision p...
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Xi Lyu, Yushan Sun, Lifeng Wang, Jiehui Tan and Liwen Zhang
This study aims to solve the problems of sparse reward, single policy, and poor environmental adaptability in the local motion planning task of autonomous underwater vehicles (AUVs). We propose a two-layer deep deterministic policy gradient algorithm-bas...
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Qianqian Wu, Qiang Liu, Zefan Wu and Jiye Zhang
In the field of ocean data monitoring, collaborative control and path planning of unmanned aerial vehicles (UAVs) are essential for improving data collection efficiency and quality. In this study, we focus on how to utilize multiple UAVs to efficiently c...
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Xiaohan Xu, Xudong Huang, Dianfang Bi and Ming Zhou
Aerodynamic compressor designs require considerable prior knowledge and a deep understanding of complex flow fields. With the development of computer science, artificial intelligence (AI) has been widely applied to compressors design. Among the various A...
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