Results 161 to 170 of about 416,094 (301)
Deep Reinforcement Learning Approaches for Sensor Data Collection by a Swarm of UAVs
This article presents four decentralized reinforcement learning algorithms for autonomous data harvesting and investigates how collaboration improves collection efficiency. It also presents strategies to minimize training times by improving model flexibility, enabling algorithms to operate with varying number of agents and sensors.
Thiago de Souza Lamenza +2 more
wiley +1 more source
Diagnostic et prise en charge de la maladie cœliaque. [PDF]
Blom JJ +4 more
europepmc +1 more source
Mission de prospection pour l'élaboration de projets de recherche sur les arboviroses zoonotiques en Asie du Sud-Est. Rapport de mission du 22 août au 4 septembre 2010 [PDF]
Chevalier, Véronique
core
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
Toward a Standardized Suicide Risk Assessment in Psychotic Disorders: A Delphi Study With Mental Health Experts: Vers une évaluation standardisée du risque de suicide chez les personnes atteintes de troubles psychotiques : étude Delphi auprès d'experts en santé mentale. [PDF]
Diotte F, Genest C, Thomas H, Lecomte T.
europepmc +1 more source
Enabling Stochastic Dynamic Games for Robotic Swarms
This paper scales stochastic dynamic games to large swarms of robots through selective agent modeling and variable partial belief space planning. We formulate these games using a belief space variant of iterative Linear Quadratic Gaussian (iLQG). We scale to teams of 50 agents through selective modeling based on the estimated influence of agents ...
Kamran Vakil, Alyssa Pierson
wiley +1 more source
Soins de santé primaires pour les personnes ayant reçu une transplantation rénale. [PDF]
Rampersad C, Bau J.
europepmc +1 more source
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source

