This article proposes an end-to-end framework for solving multiobjective optimization problems (MOPs) using deep reinforcement learning (DRL), that we call DRL-based multiobjective optimization ...

EMBL-EBI scientists and collaborators at Heidelberg University have developed CORNETO, a new computational tool that uses ...

A new data-driven technique for obstacle avoidance in autonomous vehicles is reported in the International Journal of Vehicle ...

AI-assisted design methods now allow for automated optimization, drastically shortening development cycles while boosting ...

To solve the UAV trajectory optimization problem, two algorithms over two timescales are proposed: a successive convex approximation strategy and a multi-agent reinforcement learning (MARL)-based ...

Achieving high efficiency, long operational lifetime, and excellent color purity is essential for organic light-emitting ...

AI’s performance advantages are tightly linked to methodological rigor and technological integration. Data preprocessing ...

In the current era of big data, the volume of information continues to grow at an unprecedented rate, giving rise to the crucial need for efficient ...