Nature

Machine learning articles from across Nature Portfolio

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...
IEEE

Predefined-Time Distributed Optimal Control for Nonlinear Multiagent Systems via Reinforcement Learning

Abstract: This paper investigates the predefined-time adaptive distributed optimal control problem for nonlinear multiagent systems with unknown dynamics and actuator saturation. A novel ...
IEEE

Distributed Flexible Job Shop Scheduling With Heterogeneous Transportation Resources Constraints via Deep Reinforcement Learning and Graph Neural Network

Abstract: The distributed flexible job shop scheduling problem (DFJSP) has emerged as a critical challenge in the field of scheduling optimization due to its intricate resource allocation and the ...
GitHub

Playwright Essential Training: Abstractions, Fixtures, and Complex Scenarios

This is the repository for the LinkedIn Learning course Playwright Essential Training: Abstractions, Fixtures, and Complex Scenarios. The full course is available from LinkedIn Learning. Playwright is ...
GitHub

Exo-plore: Exploring Exoskeleton Control Space through Human-Aligned Simulation

Exoskeletons show great promise for enhancing mobility, but providing appropriate assistance remains challenging due to the complexity of human adaptation to external forces. Current state-of-the-art ...