Results 31 to 40 of about 1,629,210 (315)
International Journal of Aerospace Engineering, 2023 Aiming at the problem that unmanned combat aerial vehicle (UCAV) is difficult to quickly and accurately perceive situation information and make maneuvering decision autonomously in modern air combat, which is easily affected by complex factors, a ...
Yuan Cao, Ying-Xin Kou, Zhanwu Li, An Xu
semanticscholar +1 more source
Crop Yield Prediction Using Deep Reinforcement Learning Model for Sustainable Agrarian Applications
IEEE Access, 2020 Predicting crop yield based on the environmental, soil, water and crop parameters has been a potential research topic. Deep-learning-based models are broadly used to extract significant crop features for prediction. Though these methods could resolve the
Dhivya Elavarasan +1 more
doaj +1 more source
End-to-End Autonomous Driving Through Dueling Double Deep Q-Network
Automotive Innovation, 2021 Recent years have seen the rapid development of autonomous driving systems, which are typically designed in a hierarchical architecture or an end-to-end architecture.
Baiyu Peng +6 more
semanticscholar +1 more source
A Reinforcement Learning Based Smart Cache Strategy for Cache-Aided Ultra-Dense Network
IEEE Access, 2019 The integration of caching and ultra-dense network (UDN) can not only improve the efficiency of content retrieval by reducing duplicate content transmissions but also improve the network throughput and system energy efficiency (EE) of the UDN.
Wei Li +5 more
doaj +1 more source
Amortized Variational Deep Q Network
, 2020 Accepted to appear in the Deep Reinforcement Learning Workshop at NeurIPS ...
Zhang, Haotian +3 more
openaire +2 more sources
Uncovering instabilities in variational-quantum deep Q-networks
Journal of the Franklin Institute, 2023 Authors Maja Franz, Lucas Wolf, Maniraman Periyasamy contributed equally (name order randomised).
Maja Franz +7 more
openaire +3 more sources
Path Planning for Mobile Robot Considering Turnabouts on Narrow Road by Deep Q-Network
IEEE Access, 2023 This paper proposes a path planning method for a nonholonomic mobile robot that takes turnabouts on a narrow road. A narrow road is any space in which the robot cannot move without turning around.
Tomoaki Nakamura +2 more
semanticscholar +1 more source
Overall computing offloading strategy based on deep reinforcement learning in vehicle fog computing
The Journal of Engineering, 2020 In order to solve the problem of network congestion caused by a large number of data requests generated by intelligent vehicles in LTE-V network, a brand-new fog server with fog computing function is deployed on both the cellular base stations and ...
HaiZhong Tan, Limin Zhu
doaj +1 more source
Deep Attention Q-Network for Personalized Treatment Recommendation
2023 IEEE International Conference on Data Mining Workshops (ICDMW), 2023 Tailoring treatment for individual patients is crucial yet challenging in order to achieve optimal healthcare outcomes. Recent advances in reinforcement learning offer promising personalized treatment recommendations; however, they rely solely on current patient observations (vital signs, demographics) as the patient's state, which may not accurately ...
Ma, Simin +3 more
openaire +3 more sources
, 2022 Reinforcement learning has shown an outstanding performance in the applications of games, particularly in Atari games as well as Go. Based on these successful examples, we attempt to apply one of the well-known reinforcement learning algorithms, Deep Q-Network, to the AI Soccer game.
Kim, Curie, Hwang, Yewon, Kim, Jong-Hwan
openaire +2 more sources