Results 151 to 160 of about 21,060 (240)
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
Cooperative bots exhibit nuanced effects on cooperation across strategic frameworks. [PDF]
Si Z, He Z, Shen C, Tanimoto J.
europepmc +1 more source
Dynamics on higher-order networks: a review. [PDF]
Majhi S, Perc M, Ghosh D.
europepmc +1 more source
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
Coordination and equilibrium selection in games: the role of local effects. [PDF]
Raducha T, San Miguel M.
europepmc +1 more source
Human‐Machine Mutual Trust Based Shared Control Framework for Intelligent Vehicles
This work introduces a bidirectional‐trust‐driven shared control framework for human‐machine co‐driving. The method models human‐to‐machine trust from intention discrepancies and Bayesian skill assessment, and machine‐to‐human trust from integrated ability evaluation.
Zhishuai Yin +4 more
wiley +1 more source
This study explores the origins of life by linking prebiotic chemistry, the emergence of information‐carrying molecules such as RNA and proteins, and philosophical questions about consciousness. The study emphasizes the role of molecular evolution in the Central Dogma and provides insights into the chemical origins of biology and the basis of life's ...
Harald Schwalbe +5 more
wiley +2 more sources
Coordination of network heterogeneity and individual preferences promotes collective fairness. [PDF]
Han X +6 more
europepmc +1 more source
Myopic reallocation of extraction improves collective outcomes in networked common-pool resource games. [PDF]
Schauf A, Oh P.
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

