This paper offers a comprehensive overview of machine learning (ML) methodologies and
algorithms, highlighting their practical applications in the critical domain of water resource …

Abstract Deep Reinforcement Learning has made significant progress in multi-agent
systems in recent years. The aim of this review article is to provide an overview of recent …

The area of building energy management has received a significant amount of interest in
recent years. This area is concerned with combining advancements in sensor technologies …

The number of connected smart devices has been increasing exponentially for different
Internet-of-Things (IoT) applications. Security has been a long run challenge in the IoT …

Machine learning has been heavily researched and widely used in many disciplines.
However, achieving high accuracy requires a large amount of data that is sometimes …

Deep Reinforcement Learning has made significant progress in multi-agent systems in
recent years. In this review article, we have focused on presenting recent approaches on …

Intrusion Detection Systems (IDSs) play a vital role in securing today's Data-Centric
Networks. In a dynamic environment such as the Internet of Things (IoT), which is vulnerable …

Thermal convection is ubiquitous in nature as well as in many industrial applications. The
identification of effective control strategies to, eg suppress or enhance the convective heat …

The study of new medical treatments, and sequences of treatments, is inextricably linked
with statistics. Without statistical estimation and inference, we are left with case studies and …

This paper presents a learning-based method that uses simulation data to learn an object
manipulation task using two model-free reinforcement learning (RL) algorithms. The …