Machine learning technique teaches power-generating kites to extract energy from turbulent airflows more effectively, ...

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...

Researchers introduce the EAVM protocol, achieving 17 % lower energy use and 20 % longer network lifetime in IoT systems with advanced virtualization techniques.

I didn’t want to build another loud kid’s app. I wanted to build something that felt like sitting beside your child while ...

Individuals with chronic opioid use, whether addicted or not, show heightened learning from negative reinforcement, suggesting that avoidance behavior may underlie both the development and persistence ...

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

Abstract: Autonomous driving at unsignalized intersections is still considered a challenging application for machine learning due to the complications associated with handling complex multi-agent ...

Artificial Intelligence (AI) has achieved remarkable successes in recent years. It can defeat human champions in games like Go, predict protein structures with high accuracy, and perform complex tasks ...

ABSTRACT: Depression treatment often involves a complex and lengthy trial-and-error process, where clinicians sequentially prescribe medications to identify the most ...