Hierarchical Reinforcement Learning (HRL) enables autonomous decomposition of
challenging long-horizon decision-making tasks into simpler subtasks. During the past …

In recent trends, artificial intelligence (AI) is used for the creation of complex automated
control systems. Still, researchers are trying to make a completely autonomous system that …

In light of the emergence of deep reinforcement learning (DRL) in recommender systems
research and several fruitful results in recent years, this survey aims to provide a timely and …

According to cognitive psychology and related disciplines, the development of complex
problem-solving behaviour in biological agents depends on hierarchical cognitive …

The Internet of Things (IoT) extends the Internet connectivity into billions of IoT devices
around the world, where the IoT devices collect and share information to reflect status of the …

This article addresses the problem of path following for underactuated unmanned surface
vessels (USVs) formation via a modified deep reinforcement learning with random braking …

This article is focused on the realtime monitoring and control aspects of ICPSs. Advanced
approaches and potential challenges are illustrated in the following sections. Especially, an …

Efficient exploration of unknown environments is a fundamental precondition for modern
autonomous mobile robot applications. Aiming to design robust and effective robotic …

After decades of unprecedented development, modern networks have evolved far beyond
expectations in terms of scale and complexity. In many cases, traditional traffic engineering …

Metaverse has gained increasing interest in education, with much of literature focusing on its
great potential to enhance both individual and social aspects of learning. However, little …