The majority of global road transportation emissions come from passenger and freight
vehicles. Electric vehicles (EV) provide a sustainable transportation way, but customers' …

We have analyzed 127 publications for this review paper, which discuss applications of
Reinforcement Learning (RL) in marketing, robotics, gaming, automated cars, natural …

Understanding spatiotemporal correlations in power systems is crucial for maintaining grid
stability, reliability, and efficiency. By discerning connections between spatial and temporal …

Future engineering systems with new capabilities that far exceed today's levels of autonomy,
functionality, usability, dependability, and cyber security are predicted to be designed and …

Electricity peak load forecasting plays an important role in electricity generation capacity
planning to ensure reliable power supplies. To achieve high forecast accuracy, multiple …

The demand for public fast charging stations is increasing with the number of electric
vehicles on roads. The charging queues and waiting times get longer, especially during the …

A number of decision support tools facilitating the use of Electric Vehicles (EVs) have been
recently developed. Due to the EVs' limited autonomy, routing and path planning are the …

With the continuous development of transportation electrification, the cybersecurity of energy
infrastructure has become increasingly prominent. Explicitly, EVs resemble a significant tool …

Industrial control systems are often used to assist and manage an industrial operation.
These systems' weaknesses in the various hierarchical structures of the system components …

Reinforcement Learning (RL) has emerged as a powerful paradigm in Artificial Intelligence
(AI), enabling agents to learn optimal behaviors through interactions with their environments …