Results 51 to 60 of about 98,895 (273)

Multi-Agent Deep Reinforcement Learning for Large-Scale Traffic Signal Control with Spatio-Temporal Attention Mechanism

Applied Sciences
Traffic congestion in large-scale road networks significantly impacts urban sustainability. Traditional traffic signal control methods lack adaptability to dynamic traffic conditions. Recently, deep reinforcement learning (DRL) has emerged as a promising
Wenzhe Jia, Mingyu Ji
doaj   +1 more source

Dot-to-Dot: Explainable Hierarchical Reinforcement Learning for Robotic Manipulation

, 2019
Robotic systems are ever more capable of automation and fulfilment of complex tasks, particularly with reliance on recent advances in intelligent systems, deep learning and artificial intelligence.
Beyret, Benjamin, Faisal, A. Aldo, Shafti, Ali   +2 more
core   +1 more source

Hierarchical model-based deep reinforcement learning for trading

, 2023
The kernel of this thesis posits that a hierarchical reinforcement learning (RL) system, with specialized agents, some of them being deep RL (DRL) agents, trained on distinct market data or employing diverse decision-making models, will surpass single-agent approaches in adapting to varying market conditions, optimizing risk-adjusted returns, and ...
openaire   +2 more sources

Multiple Twinning in Nacre and Aragonite

Advanced Functional Materials, EarlyView.
Electron backscatter diffraction map of a cluster of geologic aragonite, exhibiting single, double, and triple twins. The whole cluster is approximately 2 cm wide. Colors indicate crystal orientations, so that pixels where the a‐, b‐, and c‐axis is perpendicular to the image plane are green, red, and blue, respectively.
Connor A. Schmidt, William O. Nachlas, Bil Schneider, Xiaoming Mao, Eric Tambutté, Alexander A. Venn, Sylvie Tambutté, Pupa U. P. A. Gilbert   +7 more
wiley   +1 more source

Scalable Pursuit–Evasion Game for Multi-Fixed-Wing UAV Based on Dynamic Target Assignment and Hierarchical Reinforcement Learning

Drones
The unmanned aerial vehicle (UAV) pursuit–evasion game is the fundamental framework for promoting autonomous decision-making and collaborative control of multi-UAV systems.
Mulai Tan, Haocheng Sun, Dali Ding, Huan Zhou, Yongli Liu   +4 more
doaj   +1 more source

A Hierarchical Framework of Cloud Resource Allocation and Power Management Using Deep Reinforcement Learning

, 2017
Automatic decision-making approaches, such as reinforcement learning (RL), have been applied to (partially) solve the resource allocation problem adaptively in the cloud computing system.
Li, Zhe, Lin, Sheng, Liu, Ning, Qiu, Qinru, Tang, Jian, Wang, Yanzhi, Xu, Jielong, Xu, Zhiyuan   +7 more
core   +1 more source

Solvent‐Free Bonding Mechanisms and Microstructure Engineering in Dry Electrode Technology for Lithium‐Ion Batteries

Advanced Functional Materials, EarlyView.
Dry electrode technology revolutionizes battery manufacturing by eliminating toxic solvents and energy‐intensive drying. This work details two promising techniques: dry spray deposition and polymer fibrillation. How their unique solvent‐free bonding mechanisms create uniform microstructures for thicker, denser electrodes, boosting energy density and ...
Yuhao Liang, Hao Long, Zimo Huang, Ting He, Xueming Chen, Meng Li, Hao Chen, Shanqing Zhang   +7 more
wiley   +1 more source

A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems

, 2018
Bike sharing provides an environment-friendly way for traveling and is booming all over the world. Yet, due to the high similarity of user travel patterns, the bike imbalance problem constantly occurs, especially for dockless bike sharing systems ...
Cai, Qingpeng, Fang, Zhixuan, Huang, Longbo, Pan, Ling, Tang, Pingzhong   +4 more
core   +1 more source

Hierarchical Deep Multiagent Reinforcement Learning with Temporal Abstraction

, 2018
Multiagent reinforcement learning (MARL) is commonly considered to suffer from non-stationary environments and exponentially increasing policy space. It would be even more challenging when rewards are sparse and delayed over long trajectories. In this paper, we study hierarchical deep MARL in cooperative multiagent problems with sparse and delayed ...
Tang, Hongyao, Hao, Jianye, Lv, Tangjie, Chen, Yingfeng, Zhang, Zongzhang, Jia, Hangtian, Ren, Chunxu, Zheng, Yan, Meng, Zhaopeng, Fan, Changjie, Wang, Li   +10 more
openaire   +2 more sources

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source