Results 111 to 120 of about 6,813,126 (333)
Synchrotron Radiation for Quantum Technology
Advanced Functional Materials, EarlyView.Materials and interfaces underpin quantum technologies, with synchrotron and FEL methods key to understanding and optimizing them. Advances span superconducting and semiconducting qubits, 2D materials, and topological systems, where strain, defects, and interfaces govern performance.
Oliver Rader +10 more
wiley +1 more source
Advanced Functional Materials, EarlyView.By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto +8 more
wiley +1 more source
Advanced Functional Materials, EarlyView.Bloodstream infections (BSI) are one of the leading causes of mortality and morbidity in both civilian and military populations. This paper summarizes recent progress in novel treatment strategies to manage BSI arising from both bacterial and fungal pathogens using molecules, particles, and materials to elicit host‐directed immunity.
Thomas Thomou +11 more
wiley +1 more source
Buana Information Technology and Computer SciencesReinforcement learning (RL) approaches, particularly Q-learning, have emerged as strong tools for autonomous agent training, allowing agents to acquire optimum decision-making rules through interaction with their surroundings.
Biplov Paneru +3 more
doaj +1 more source
A Reinforcement Learning Approach for Smart Farming [PDF]
Database Systems Journal, 2019 At a basic level, the aim of machine learning is to develop solutions for real-life engineering problems and to enhance the performance of different computers tasks in order to obtain an algorithm that is highly independent of human intervention.
Gabriela ENE
doaj
A Theoretical Analysis of Cooperative Behavior in Multi-Agent Q-learning [PDF]
A number of experimental studies have investigated whether cooperative behavior may emerge in multi-agent Q-learning. In some studies cooperative behavior did emerge, in others it did not. This report provides a theoretical analysis of this issue.
Kaymak, U., Waltman, L.R.
core +1 more source
Advanced Functional Materials, EarlyView.Thermal transport in Ru and W thin films is studied using steady‐state thermoreflectance, ultrafast pump–probe spectroscopy, infrared‐visible spectroscopy, and computations. Significant Lorenz number deviations reveal strong phonon contributions, reaching 45% in Ru and 62% in W.
Md. Rafiqul Islam +14 more
wiley +1 more source
Q-Learning with Heterogeneous Update Strategy
, 2023 Tao Tan, Xie Hong, Liang Feng
openalex +1 more source
MinMaxMin $Q$-learning is a novel optimistic Actor-Critic algorithm that addresses the problem of overestimation bias ($Q$-estimations are overestimating the real $Q$-values) inherent in conservative RL algorithms. Its core formula relies on the disagreement among $Q$-networks in the form of the min-batch MaxMin $Q$-networks distance which is added to ...
Soffair, Nitsan, Mannor, Shie
openaire +2 more sources
Advanced Functional Materials, EarlyView.A miniaturized mechano‐acoustic sensor is developed using an electrospun PVDF nanomesh as the diaphragm in a capacitive sensor structure. Unlike conventional nanomesh‐based sensors, it achieves high linear sensitivity, a broad and flat frequency response, and a compact form factor.
Jeng‐Hun Lee +8 more
wiley +1 more source