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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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Weilai Jiang, Chenghong Zheng, Delong Hou, Kangsheng Wu and Yaonan Wang
The autonomous shape decision-making problem of a morphing aircraft (MA) with a variable wingspan and sweep angle is studied in this paper. Considering the continuity of state space and action space, a more practical autonomous decision-making algorithm ...
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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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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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Hy Nguyen, Srikanth Thudumu, Hung Du, Kon Mouzakis and Rajesh Vasa
Several approaches have applied Deep Reinforcement Learning (DRL) to Unmanned Aerial Vehicles (UAVs) to do autonomous object tracking. These methods, however, are resource intensive and require prior knowledge of the environment, making them difficult to...
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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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Guangxiu Ning, Lide Su, Yong Zhang, Jian Wang, Caili Gong and Yu Zhou
Due to its flexibility and versatility, the electric distributed drive micro-tillage chassis can be used more often in the future in Intelligence agriculture scenarios. However, due to the complex working conditions of the agricultural operation environm...
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Aiqing Huo, Xue Jiang and Shuhan Zhang
A rotary steerable drilling system is an advanced drilling technology, with stabilized platform tool face attitude control being a critical component. Due to a multitude of downhole interference factors, coupled with nonlinearities and uncertainties, cha...
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Yu Cao, Kan Ni, Xiongwen Jiang, Taiga Kuroiwa, Haohao Zhang, Takahiro Kawaguchi, Seiji Hashimoto and Wei Jiang
The potential of autonomous driving technology to revolutionize the transportation industry has attracted significant attention. Path following, a fundamental task in autonomous driving, involves accurately and safely guiding a vehicle along a specified ...
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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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