Transformers have significantly impacted domains like natural language processing,
computer vision, and robotics, where they improve performance compared to other neural …

Recent advancements in deep reinforcement learning (DRL) have led to its application in
multi-agent scenarios to solve complex real-world problems, such as network resource …

This research study aims to investigate the microgrid operation for distributing energy
including of a local user, a wind turbine, 5 photovoltaics (PV), and a battery, which is linked …

A novel smart metering technique capable of anomaly detection was proposed for real‐time
home power management system. Smart meter data generated in real‐time were obtained …

The Credit Assignment Problem (CAP) refers to the longstanding challenge of
Reinforcement Learning (RL) agents to associate actions with their long-term …

Photovoltaic (PV) and wind energy are widely considered eco-friendly renewable energy
resources. However, due to the unpredictable oscillations in solar and wind power …

Collaborative control of a dual-arm robot refers to collision avoidance and working together
to accomplish a task. To prevent the collision of two arms, the control strategy of a robot arm …

In recent years, unmanned aerial vehicles (UAVs) have been considered for many
applications, such as disaster prevention and control, logistics and transportation, and …

Training agents via deep reinforcement learning with sparse rewards for robotic control
tasks in vast state space are a big challenge, due to the rareness of successful experience …

The evolutionary algorithm has become a major method for neural architecture search
recently. However, the fixed probability distribution employed by the traditional evolutionary …