In this survey paper, we characterize the learning problem in cognitive radios (CRs) and
state the importance of artificial intelligence in achieving real cognitive communications …

In recent years, the research on reinforcement learning (RL) has focused on function
approximation in learning prediction and control of Markov decision processes (MDPs). The …

Intelligent transport systems, efficient electric grids, and sensor networks for data collection
and analysis are some examples of the multiagent systems (MAS) that cooperate to achieve …

Dynamic spectrum access (DSA) is regarded as an effective and efficient technology to
share radio spectrum among different networks. As a secondary user (SU), a DSA device …

This paper proposes a reinforcement learning based approach to anti-jamming
communications with wideband autonomous cognitive radios (WACRs) in a multi-agent …

Nowadays, machine learning (ML), which is one of the most rapidly growing technical tools,
is extensively used to solve critical challenges in various domains. Vehicular ad hoc network …

Due to exponential growth in demand for radio spectrum for wireless communication
networking, the radio spectrum has become over-crowded. The fixed spectrum allocation …

In this study, the authors review various jamming and anti‐jamming strategies in the context
of cognitive radios (CRs). The study explores different jamming models and classifies them …

This paper presents a solution for building awareness of the electromagnetic situation in
cognitive mobile ad hoc networks (MANET) using the cooperative spectrum sensing method …

Cognitive Radio (CR) technology enables secondary users (SUs) to opportunistically access
unused licensed spectrum owned by the primary users (PUs). Therefore, it can potentially …