Suchergebnisse - "Policy gradient algorithm"

Motion planning for 7-degree-of-freedom bionic arm: Deep deterministic policy gradient algorithm based on imitation of human action von Li, Baojiang, Qiu, Shengjie, Ye, Haiyan, Guo, Yuting, Wang, Haiyan, Bai, Jibo

“… Meanwhile, bionic arms often require specific programming to be implemented for the subject to initially meet the control requirements, which makes it difficult to match the motion of the bionic arm …”
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Deep Ensemble Reinforcement Learning with Multiple Deep Deterministic Policy Gradient Algorithm von Wu, Junta, Li, Huiyun

“… Deep deterministic policy gradient algorithm operating over continuous space of actions has attracted great attention for reinforcement learning …”
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Optimization control of the double‐capacity water tank‐level system using the deep deterministic policy gradient algorithm von Ye, Likun, Jiang, Pei

“… Process control systems are subject to external factors such as changes in working conditions and perturbation interference, which can significantly affect the system's stability and overall performance …”
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Robust control for anaerobic digestion systems of Tequila vinasses under uncertainty: A Deep Deterministic Policy Gradient Algorithm von Mendiola-Rodriguez, Tannia A., Ricardez-Sandoval, Luis A.

“… Anaerobic digestion is a complex system subject to external perturbations and parametric uncertainty …”
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Brain-Inspired Deep Meta-Reinforcement Learning for Active Coordinated Fault-Tolerant Load Frequency Control of Multi-Area Grids von Li, Jiawen, Zhou, Tao, Cui, Haoyang

“… In addition, this paper proposes a brain-Inspired deep meta-deterministic policy gradient algorithm (BIMA-DMDPG …”
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Wide-Range Variable Cycle Engine Control Based on Deep Reinforcement Learning von Ding, Yaoyao, Wang, Fengming, Mu, Yuanwei, Sun, Hongfei

“… deterministic policy gradient algorithm, and it applies an action space pruning technique to optimize …”
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Robust Energy-Efficient DRL-Based Optimization in UAV-Mounted RIS Systems with Jitter von Salim, Mahmoud M., Rabie, Khaled M., Muqaibel, Ali H.

“… To address this, we reformulate the problem as a deep reinforcement learning (DRL) environment and develop a smoothed softmax dual deep deterministic policy gradient algorithm …”
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Deep-Reinforcement-Learning-Based Computation Offloading for Servicing Dynamic Demand in Multi-UAV-Assisted IoT Network von Lin, Na, Bai, Lu, Hawbani, Ammar, Guan, Yunchong, Mao, Chaojin, Liu, Zhi, Zhao, Liang

“… The dynamic scheduling and computation offloading of UAVs is the subject of this article. Specifically, we propose a deep deterministic policy gradient algorithm based on a greedy …”
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Adaptive trajectory controller design for unmanned surface vehicles based on SAC-PID von Guan, Wei, Xi, Zhaoyong, Cui, Zhewen, Zhang, Xianku

“… An adaptive proportional integral derivative (PID) controller based on the soft actor-critic (SAC) algorithm for trajectory control of unmanned surface …”
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Three-Dimensional Trajectory Design for Multi-User MISO UAV Communications: A Deep Reinforcement Learning Approach von Wang, Yang, Gao, Zhen

“… ), which is developed from a deep deterministic policy gradient algorithm. In particular, to represent the state information of UAV and environment, we set an additional information, i.e …”
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Online Assignment of Satellite Data Transmission Tasks Based on Twin Delayed Deep Deterministic Policy Gradient von Li, Ke, Xiong, Shunrui, Yang, Mingying, Ma, Sai

“… This study focuses on the scheduling problem of satellite data transmission tasks, where ground station resources are scarce and subject to multiple constraints, such as limited funding, long …”
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Learning Constrained Resource Allocation Policies in Wireless Control Systems von Lima, Vinicius, Eisen, Mark, Ribeiro, Alejandro

“… As wireless networks are noisy and subject to packet losses - which might impact the operation of the control system - proper distribution of communication resources among components of the wireless …”
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Coordinated Scheduling Strategy for Multi-Agent System in Active Distribution Grid based on Deep Reinforcement Learning Method von Liu, Xuan, Li, Wanbin, Song, Lin, Yao, Zhanfeng, Lu, Tianguang, Bai, Xue, Zhang, Yuqi, Wang, Wenxin, Zheng, Yanan, Liu, Chunxiu

“… First, each subject such as distributed power sources, energy storage devices and flexible loads is taken as an intelligent agent in an active distribution grid, and the real-time state information …”
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Independent Learning in Constrained Markov Potential Games von Jordan, Philip, Barakat, Anas, He, Niao

“… We propose an independent policy gradient algorithm for learning approximate constrained Nash equilibria …”
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Model-free Distortion Canceling and Control of Quantum Devices von Fouad, Ahmed F, Youssry, Akram, El-Rafei, Ahmed, Hammad, Sherif

“… First, in practice the control signals are usually subject to unknown classical distortions that could arise from the device fabrication, material properties and/or instruments generating those signals …”
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Computing Transition Pathways for the Study of Rare Events Using Deep Reinforcement Learning von Lin, Bo, Zhong, Yangzheng, Ren, Weiqing

“… Understanding the transition events between metastable states in complex systems is an important subject in the fields of computational physics, chemistry and biology …”
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A deep reinforcement learning approach to assess the low-altitude airspace capacity for urban air mobility von Asal Mehditabrizi, Samadzad, Mahdi, Sabzekar, Sina

“… Path planning is a vital subject in urban air mobility which could enable a large number of UAVs to fly simultaneously in the airspace without facing the risk of collision …”
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A Deep Reinforcement Learning Approach for Online Parcel Assignment von Zeng, Hao, Wu, Qiong, Han, Kunpeng, He, Junying, Hu, Haoyuan

“… More specifically, we introduce a novel Markov Decision Process (MDP) framework to model the OPA problem, and develop a policy gradient algorithm that adopts …”
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Sampling, Communication, and Prediction Co-Design for Synchronizing the Real-World Device and Digital Model in Metaverse von Meng, Zhen, She, Changyang, Zhao, Guodong, De Martini, Daniele

“… This work proposes a sampling, communication and prediction co-design framework to minimize the communication load subject to a constraint on tracking the Mean Squared Error (MSE …”
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Three-Dimensional Trajectory Design for Multi-User MISO UAV Communications: A Deep Reinforcement Learning Approach von Wang, Yang, Gao, Zhen

“… ), which is developed from a deep deterministic policy gradient algorithm. In particular, to represent the state information of UAV and environment, we set an additional information, i.e …”
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