Results 141 to 150 of about 640,433 (264)

Reinforcement learning

Scholarpedia, 2008
Bernd Porr, Florentin Woergoetter
openaire   +1 more source

2D Nanomaterials Toward Function‐Ready Superlubricity in Advanced Microsystems

Advanced Materials, EarlyView.
A unified framework links structural and transformation superlubricity with microsystem functions and deployment requirements. Mechanisms, device architectures, integration strategies, AI‐guided discovery, and benchmarking protocols are connected to define function‐ready superlubricity in advanced microsystems.
Yushan Geng, Jun Yang, Yong Yang
wiley   +1 more source

Estimating the motor exploration in reinforcement learning. [PDF]

iScience
Zai AT, Lorenz C, Srikantharajah S, Giret N, Hahnloser RHR.   +4 more
europepmc   +1 more source

Data‐Driven Cation Engineering Guides Electrolyte Design for Sustainable Aqueous Zinc Battery Chemistries

Advanced Materials, EarlyView.
To address the persistent challenges of vanadium dissolution and capacity fading in zinc‐ion batteries, we introduce a cation‐engineered electrolyte strategy underpinned by a data‐driven framework. This approach efficiently and reliably predicts a Na+‐Mg2+‐Zn2+ tri‐cation electrolyte with well‐balanced and sustainable advantages, enabling Zn/VOx ...
Xuesong Xie, Yinfei Lyu, Huorong Ren, Witold Pedrycz, Yifan Li, Yang Yang, Xuehai Tan, Minggang Xie, Yi Guan, Yuxuan Xue, Ning Chen, Zhi Li   +11 more
wiley   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Participatory-informed preference optimization (PiPrO): A reinforcement learning simulation study. [PDF]

PLOS Digit Health
Templin T, Song S, Fort S, Sinnott-Armstrong N.   +3 more
europepmc   +1 more source

Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics

Advanced Materials, EarlyView.
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair, Hrisheekesh Thachoth Chandran, Karl Leo, Hans Kleemann   +3 more
wiley   +1 more source

A reinforcement learning and sequential sampling model constrained by gaze data. [PDF]

PLoS Comput Biol
Hayes WM, Touchard MJ.
europepmc   +1 more source

AI–Guided 4D Printing of Carnivorous Plants–Inspired Microneedles for Accelerated Wound Healing

Advanced Materials, EarlyView.
This work presents an artificial intelligence (AI)‐guided 4D‐printed microneedle platform inspired by carnivorous plants for wound healing. A thermo‐responsive shape memory polymer enables body temperature–triggered self‐coiling for autonomous wound closure.
Hyun Lee, Moon‐Jo Kim, DongEung Kim, Chan Ho Moon, Seojoon Bang, Hyeong Seok Kang, Ju Yeong Gwon, Jong Hwa Seo, Junhyub Jeon, Junhyuk Son, Munwon Lim, Minho Kang, Dong Yun Lee, Donghyun Lim, Jung‐Hoon Park, Gi Doo Cha, Soo‐Hong Lee, Tae‐Sik Jang, Kisuk Yang, Yunho Jeong, Youngho Eom, Hyun‐Do Jung   +21 more
wiley   +1 more source

On the need for abstract, deep reinforcement learning models in neuroscience. [PDF]

Front Neuroinform
Duarte S, Al-Hejji X, Bermudez Contreras E, Chalmers E.   +3 more
europepmc   +1 more source