As the electricity market is progressively liberalized, virtual bidding has emerged as a novel participation mechanism attracting increasing attention. This paper integrates evolutionary game theory ...

ABSTRACT: Personalized dosing of mood stabilizers remains challenging due to substantial inter-individual variability in symptom severity, treatment responsiveness, and vulnerability to adverse ...

Utilities worldwide are turning to artificial intelligence (AI) and machine learning to stabilize networks, forecast consumption, detect faults, and optimize system performance in real-time. What was ...

AI improves renewable energy forecasting accuracy by up to 33%, helping grid operators better integrate solar and wind resources. Predictive maintenance powered by AI reduces equipment downtime by ...

Extreme events such as earthquakes can readily cause structural damage and operational disturbances in power grids, thereby weakening the system’s supply stability and recovery capability and posing ...

Abstract: Reinforcement learning algorithms have revolutionized autonomous decision-making in various domains. In this paper, we compare Q-learning and DQN for solving a 100x100 grid model of a ...

Apple, Meta, and Google are locked in a fierce battle to lead the next wave of AI, and they’ve recently increased their focus on hardware. With its latest acquisition of the AI startup Q.ai, Apple ...

Abstract: To address the issues of slow convergence speed and poor path planning performance in dynamic obstacle environments. This paper proposes an improved Q-Learning path planning algorithm for ...

Artificial intelligence continues to be the central force behind the upcoming productivity revolution. Yet in the US, foundational energy constraints threaten to stall progress. The primary obstacle ...