Results 61 to 70 of about 298,347 (266)

A Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller

International Journal of Adaptive Control and Signal Processing, EarlyView.
Block Diagram of the Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller. ABSTRACT This article introduces a discrete‐time robust adaptive one‐sample‐ahead preview super‐twisting sliding mode controller. A stability analysis of the controller by Lyapunov criteria is developed to demonstrate its robustness in handling both ...
Guilherme Vieira Hollweg, Paulo Jefferson Dias de Oliveira Evald, Shivam Chaturvedi, Hilton Abilio Gründling, Rodrigo Varella Tambara, Wencong Su   +5 more
wiley   +1 more source

A Concept of a Digital and Traceable Manufacturing Documentation Based on Formalized Process Description Applied on Composite Aircraft Moveable

Advanced Engineering Materials, EarlyView.
The documentation of component manufacture has become an essential part of today's production processes, especially for the analysis and optimization of production or component design with regard to structural performance, economic efficiency, and sustainability.
Björn Denker, Dominik Delisle, Christian Krombholz, Martin Rädel, Frank Dressel   +4 more
wiley   +1 more source

Multiagent Deep Reinforcement Learning Algorithms in StarCraft II: A Review

IEEE Access
StarCraft II, as a real-time strategy game, features multiagent collaboration, complex decision-making processes, partially observable environments, and long-term credit assignment; thus, it is an ideal platform for exploring, validating, and optimizing ...
Yanyan Li, Yijun Wang, Yiwei Zhou
doaj   +1 more source

LFDC: Low-Energy Federated Deep Reinforcement Learning for Caching Mechanism in Cloud–Edge Collaborative

Applied Sciences, 2023
The optimization of caching mechanisms has long been a crucial research focus in cloud–edge collaborative environments. Effective caching strategies can substantially enhance user experience quality in these settings.
Xinyu Zhang, Zhigang Hu, Meiguang Zheng, Yang Liang, Hui Xiao, Hao Zheng, Aikun Xu   +6 more
doaj   +1 more source

Engineering a QoS Provider Mechanism for Edge Computing with Deep Reinforcement Learning

, 2019
With the development of new system solutions that integrate traditional cloud computing with the edge/fog computing paradigm, dynamic optimization of service execution has become a challenge due to the edge computing resources being more distributed and ...
Carpio, Francisco, Ferrer, Ana Juan, Jukan, Admela, Sosa, Roman   +3 more
core   +1 more source

Deep Reinforcement Learning

2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2023
Branka Hadji Misheva, Joerg Osterrieder
  +5 more sources

Advancing Electronic Application of Coordination Solids: Enhancing Electron Transport and Device Integration via Surface‐Mounted MOFs (SURMOFs)

Advanced Functional Materials, EarlyView.
The layer‐by‐layer (LbL) assembly of coordination solids, enabled by the surface‐mounted metal‐organic framework (SURMOF) platform, is on the cusp of generating the organic counterpart of the epitaxy of inorganics. The programmable and sequential SURMOF protocol, optimized by machine learning (ML), is suited for accessing high‐quality thin films of ...
Zhengtao Xu, Christof Wöll, Stefan Bräse   +2 more
wiley   +1 more source

A new approach for drone tracking with drone using Proximal Policy Optimization based distributed deep reinforcement learning

SoftwareX, 2023
In this paper, a distributed deep reinforcement learning algorithm based on Proximal Policy Optimization (PPO) is proposed for an unmanned aerial vehicle (UAV) to autonomously track another UAV. Accordingly, this paper makes three important contributions
Ziya Tan, Mehmet Karaköse
doaj   +1 more source

Fine-grained acceleration control for autonomous intersection management using deep reinforcement learning

, 2017
Recent advances in combining deep learning and Reinforcement Learning have shown a promising path for designing new control agents that can learn optimal policies for challenging control tasks.
Givargis, Tony, Mirzaei, Hamid
core   +1 more source

3D (Bio) Printing Combined Fiber Fabrication Methods for Tissue Engineering Applications: Possibilities and Limitations

Advanced Functional Materials, EarlyView.
Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana, Indra Apsite, Leonid Ionov   +2 more
wiley   +1 more source