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

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

A team of researchers has developed a new method for controlling lower limb exoskeletons using deep reinforcement learning. The method enables more robust and natural walking control for users of ...

Traffic congestion, fuel consumption, and emissions also offer quantifiable performance indicators, making mobility uniquely ...

This illustration draws a parallel between quantum state tomography and natural language modeling. In quantum tomography, structured measurements yield probability outcomes that are aggregated to ...

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

Researchers have developed a novel framework, termed PDJA (Perception–Decision Joint Attack), that leverages artificial intelligence (AI) to address a ...

Researchers have developed a novel framework, termed PDJA (Perception–Decision Joint Attack), that leverages artificial ...

A Japanese semiconductor plant shows how autonomous control based on artificial intelligence is becoming reality. As process control technologies advance, one concept gaining prominence is autonomy.

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.