Zobrazeno 1 - 10
of 571
pro vyhledávání: '"action space"'
Publikováno v:
Future Transportation, Vol 4, Iss 2, Pp 579-590 (2024)
The autonomous vehicle is an innovative field for the application of machine learning algorithms. Controlling an agent designed to drive safely in traffic is very complex as human behavior is difficult to predict. An individual’s actions depend on
Externí odkaz:
https://doaj.org/article/b0d1393b1e5848919a228e8c204f4c2c
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 4, Pp 1032-1046 (2024)
Policy search is an efficient learning method in the field of deep reinforcement learning (DRL), which is capable of solving large-scale problems with continuous state and action spaces and widely used in real-world problems. However, such method usu
Externí odkaz:
https://doaj.org/article/38cab6c7b1a642e09717377cb10e2a4f
Autor:
Gadde, Lars-Erik, Håkansson, Håkan
Publikováno v:
Journal of Business & Industrial Marketing, 2023, Vol. 38, Issue 13, pp. 166-179.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JBIM-10-2022-0454
Autor:
Junzhe Jiang, Hongming Wang, Zhixing Huang, Zhuangfeng Zhou, Xiang Wu, Wenqin Deng, Xueyun Chen
Publikováno v:
IEEE Access, Vol 12, Pp 178507-178522 (2024)
In autonomous air combat, tactics are inherently complex, and control inputs are continuous. Traditional reinforcement learning (RL) algorithms often rely on discretization or independent Gaussian assumptions, which fail to capture correlations betwe
Externí odkaz:
https://doaj.org/article/e3053aaa064042119cf0921231ec81da
Autor:
Priva Chassem Kamdem, Alain B. Zemkoho, Laurent Njilla, Marcellin Nkenlifack, Charles A. Kamhoua
Publikováno v:
IEEE Access, Vol 12, Pp 171559-171570 (2024)
Cyber-physical systems (CPS) are increasingly vulnerable to sophisticated cyber-attacks that can target multiple layers within the system. To strengthen defenses against these complex threats, deception-based techniques have emerged as a promising so
Externí odkaz:
https://doaj.org/article/cdaa03326af64fec980452af7bbff1b2
Autor:
Bishoy Salama Attia, Aamen Elgharably, Mariam Nabil Aboelwafa, Ghada Alsuhli, Karim Banawan, Karim G. Seddik
Publikováno v:
IEEE Open Journal of the Communications Society, Vol 5, Pp 4902-4919 (2024)
We consider the problem of jointly enhancing the network throughput, minimizing energy consumption, and improving the network coverage of mobile networks. The problem is cast as a reinforcement learning (RL) problem. The reward function accounts for
Externí odkaz:
https://doaj.org/article/707e88357ee245fc9623387e59474b92
Publikováno v:
IEEE Open Journal of the Communications Society, Vol 5, Pp 3762-3774 (2024)
Cognitive radio networks (CRNs) mitigate spectrum scarcity by leveraging the holes in the licensed spectrum to enable Internet of Things (IoT) devices to opportunistically access the spectrum. However, IoT devices need to sense the spectrum before th
Externí odkaz:
https://doaj.org/article/19ea9d3c35894b14a9a780e057ce4e2c
Publikováno v:
Drones, Vol 8, Iss 5, p 205 (2024)
Path planning is one of the most essential parts of autonomous navigation. Most existing works are based on the strategy of adjusting angles for planning. However, drones are susceptible to collisions in environments with densely distributed and high
Externí odkaz:
https://doaj.org/article/dc70fa4369724093a0a13247a591665d
Publikováno v:
IEEE Access, Vol 11, Pp 107669-107684 (2023)
It is the key research object of electronic warfare to use UAV (Unmanned Aerial Vehicle) clusters to carry out electronic countermeasure tasks. The UAV carries loads such as reconnaissance and interference at the same time, which makes it necessary t
Externí odkaz:
https://doaj.org/article/4f71f02163c440549773315257ca11a4
Publikováno v:
Journal of Intelligent and Connected Vehicles, 2022, Vol. 5, Issue 3, pp. 316-332.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JICV-07-2022-0030