Results 81 to 90 of about 323,609 (233)
Advanced Functional Materials, EarlyView.The study proposes a 1‐bit programmable metasurface based on flip‐disc display, named flip‐disc metasurface (FD‐MTS). This new design enables ultralow energy consumption while maintaining coding patterns. It also exhibits high scalability and multifunctional flexibility.
Jiang Han Bao +8 more
wiley +1 more source
The advancements and applications of deep reinforcement learning in Go [PDF]
ITM Web of ConferencesCombining Deep Learning's perceptual skills with Reinforcement Learning's decision-making abilities, Deep Reinforcement Learning (DRL) represents a significant breakthrough in Artificial Intelligence (AI).
Zheng Xutao
doaj +1 more source
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 +7 more
wiley +1 more source
Improved Path Planning for Indoor Patrol Robot Based on Deep Reinforcement Learning [PDF]
, 2022 Jianfeng Zheng +4 more
openalex +1 more source
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 +17 more
wiley +1 more source
Energy Efficiency Strategy for Big Data in Cloud Environment Using Deep Reinforcement Learning [PDF]
, 2022 Neeraj Kumar Pandey +5 more
openalex +1 more source
Advanced Functional Materials, EarlyView.This study establishes a materials‐driven framework for entropy generation within standard CMOS technology. By electrically rebalancing gate‐oxide traps and Si‐channel defects in foundry‐fabricated FDSOI transistors, the work realizes in‐materia control of temporal correlation – achieving task adaptive entropy optimization for reinforcement learning ...
Been Kwak +14 more
wiley +1 more source
Advanced Functional Materials, EarlyView.Fibrous benzenetrispeptide (BTP) hydrogels, fabricated via strain‐promoted azide‐alkyne cycloaddition (SPAAC) crosslinking, form robust, bioinert networks. These hydrogels can support 3D cell culture, where cell viability and colony growth depend on the fiber content.
Ceren C. Pihlamagi +5 more
wiley +1 more source
Learning a Swarm Foraging Behavior with Microscopic Fuzzy Controllers Using Deep Reinforcement Learning [PDF]
, 2021 Fidel Aznar +2 more
openalex +1 more source
Importance mixing: Improving sample reuse in evolutionary policy search methods
, 2018 Deep neuroevolution, that is evolutionary policy search methods based on deep neural networks, have recently emerged as a competitor to deep reinforcement learning algorithms due to their better parallelization capabilities.
Perrin, Nicolas +2 more
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