This paper presents a comprehensive literature review on Reinforcement Learning (RL)
techniques used in Intrusion Detection Systems (IDS), Intrusion Prevention Systems (IPS) …

Nowadays, pressurized irrigation systems have been develo** in farms to increase water
use efficiency that are successful when the inflow is accurately supplied from water sources …

In recent years, water contamination incidents have happened frequently, causing serious
losses and impacts on society. Therefore, how to quickly respond to emergency pollution …

Contribution of Internet of things in water supply chain management: A bibliometric and content
analysis | Emerald Insight Books and journals Case studies Expert Briefings Open Access …

Many real-world control problems involve conflicting objectives. For different objectives, it is
necessary to obtain Pareto optimal solution sets for each one. Over recent years, multi …

We consider the challenge of policy simplification and verification in the context of policies
learned through reinforcement learning (RL) in continuous environments. In well-behaved …

Although deep reinforcement learning (DRL) has many success stories, the large-scale
deployment of policies learned through these advanced techniques in safety-critical …

Autonomous navigation of Unmanned Aerial Vehicles (UAVs) in large-scale complex
environments presents a significant challenge in modern aerospace engineering, as it …

Multi-objective reinforcement learning (MORL) addresses the challenge of optimizing
policies in environments with multiple conflicting objectives. Traditional approaches often …

Fuzzy SARSA learning (FSL) is a robust reinforcement learning (RL) technique that
represents successful solutions in various industrial problems. Water management in …