Results 51 to 60 of about 139,994 (273)

A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science

Advanced Engineering Materials, EarlyView.
We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann, Sarath Menon, Raphael Röske, Johannes Steinhülb, Michael Selzer, Jan Janssen, Tilmann Hickel, Ruth Schwaiger, Jörg Neugebauer   +8 more
wiley   +1 more source

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

Dual Preference Learning for Multi-Agent Reinforcement Learning

IEEE Access
Designing effective reward functions is fundamental challenging in reinforcement learning, especially in complex multi-agent systems with intricate credit assignment.
Sehyeok Kang, Minu Kim, Jihwan Oh, Se-Young Yun   +3 more
doaj   +1 more source

Multi-agent Reinforcement Learning Algorithm Based on AI Planning [PDF]

Jisuanji kexue
At present,deep reinforcement learning algorithms have made a lot of achievements in various fields.However,in the field of multi-agent task,agents are often faced with non-stationary environment with larger state-action space and sparse rewards,low ...
XIN Yuanxia, HUA Daoyang, ZHANG Li
doaj   +1 more source

A Cooperative Multi-Agent Reinforcement Learning Method Based on Coordination Degree

IEEE Access, 2021
Multi-agent reinforcement learning (MARL) has become a prevalent method for solving cooperative problems owing to its tractable implementation and task distribution. The goal of the MARL algorithms for fully cooperative scenarios is to obtain the optimal
Haoyan Cui, Zhen Zhang
doaj   +1 more source

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

Advanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner, Dhananjeya Kumaar, Giacomo Torti, Killian Keller, Till Zellweger, Florian M. Schenk, Christoph Weilenmann, Daniel Chelladurai, Vara Prasad Jonnalagadda, Ghazi Sarwat Syed, Vanessa Wood, Jürg Leuthold, Alexandros Emboras, Maksym Yarema, Mathieu Luisier   +14 more
wiley   +1 more source

Electrolyte Design Strategies for Static Shuttle‐Free and Long‐Life Aqueous Zinc‐Iodine Batteries

Advanced Functional Materials, EarlyView.
This review systematically summarizes recent advances in electrolyte design for static aqueous Zn‐I2 batteries, highlighting solvation regulation and interfacial engineering strategies to control reaction kinetics, suppress iodine shuttling, enhance energy density, and stabilize multi‐electron iodine redox chemistry for durable, high‐performance energy
Qianqin Zhou, Fan Zhang, Ting Liao, Ziqi Sun   +3 more
wiley   +1 more source

Multi-AUV Hunting Strategy Based on Regularized Competitor Model in Deep Reinforcement Learning

Journal of Marine Science and Engineering
Reinforcement learning has made significant progress in single-agent applications, but it still faces various challenges in multi-agent scenarios. This study investigates the application of reinforcement learning algorithms in a competitive game scenario
Yancheng Sui, Zhuo Wang, Guiqiang Bai, Hao Lu   +3 more
doaj   +1 more source

A Regularized Opponent Model with Maximum Entropy Objective [PDF]

, 2019
In a single-agent setting, reinforcement learning (RL) tasks can be cast into an inference problem by introducing a binary random variable o, which stands for the "optimality".
Gong, Zhichen, Punakkath, Faiz, Tian, Zheng, Wang, Jun, Wen, Ying, Zou, Shihao   +5 more
core   +1 more source

Engineering Strategies for Stable and Long‐Life Alkaline Zinc‐Based Flow Batteries

Advanced Functional Materials, EarlyView.
Alkaline zinc‐based flow batteries face persistent challenges from unstable zinc deposition, including dendrite growth, passivation, corrosion, and hydrogen evolution, which severely limit cycling stability. Current research addresses these issues through coordinated electrode structuring, electrolyte regulation, and membrane design to control zinc ...
Yuran Bai, Xiaoyu Huo, Xin Long, Enkang Fu, Xusong Gong, Lei Wei, Liang An   +6 more
wiley   +1 more source