Towards future intelligent vehicular network, the machine learning as the promising artificial
intelligence tool is widely researched to intelligentize communication and networking …

Abstract Machine Learning (ML) has been enjoying an unprecedented surge in applications
that solve problems and enable automation in diverse domains. Primarily, this is due to the …

As a powerful tool, the vehicular network has been built to connect human communication
and transportation around the world for many years to come. However, with the rapid growth …

Reinforcement learning (RL), which is a class of machine learning, provides a framework by
which a system can learn from its previous interactions with its environment to efficiently …

Wireless sensor networks (WSNs) are networks of distributed autonomous devices that can
sense or monitor physical or environmental conditions cooperatively. WSNs face many …

The growing network density and unprecedented increase in network traffic, caused by the
massively expanding number of connected devices and online services, require intelligent …

In urban vehicular ad hoc networks (VANETs), the high mobility of vehicles along street
roads poses daunting challenges to routing protocols and has a great impact on network …

Vehicular-ad hoc networks (VANETs) hold great importance because of their potentials in
road safety improvement, traffic monitoring, and in-vehicle infotainment services. Due to high …

In this article, we investigate the routing problem of packet networks through multiagent
reinforcement learning (RL), which is a very challenging topic in distributed and autonomous …

In wireless networks, context awareness and intelligence are capabilities that enable each
host to observe, learn, and respond to its complex and dynamic operating environment in an …