As one of the key communication scenarios in the fifth-generation and also the sixth-
generation (6G) mobile communication networks, ultrareliable and low-latency …

The interaction of multiple autonomous agents gives rise to highly dynamic and
nondeterministic environments, contributing to the complexity in applications such as …

Internet of Things (IoT) devices can apply mobile edge computing (MEC) and energy
harvesting (EH) to provide high-level experiences for computational intensive applications …

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 …

In the framework of fully cooperative multi-agent systems, independent (non-communicative)
agents that learn by reinforcement must overcome several difficulties to manage to …

Nonorthogonal multiple access (NOMA) systems are vulnerable to jamming attacks,
especially smart jammers who apply programmable and smart radio devices such as …

In real-world multi-agent reinforcement learning (MARL) applications, agents may not have
perfect state information (eg, due to inaccurate measurement or malicious attacks), which …

As accurate malware detection on mobile devices requires fast process of a large number of
application traces, cloud-based malware detection can utilize the data sharing and powerful …

This paper provides a new deterministic Q-learning with a presumed knowledge about the
distance from the current state to both the next state and the goal. This knowledge is …

Q-learning in single-agent environments is known to converge in the limit given sufficient
exploration. The same algorithm has been applied, with some success, in multiagent …