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 …

Unmanned aerial vehicle (UAV) networks are playing an important role in various areas due
to their agility and versatility, which have attracted significant attentions from both the …

Swarm intelligence (SI) algorithms, including ant colony optimization, particle swarm
optimization, bee-inspired algorithms, bacterial foraging optimization, firefly algorithms, fish …

Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving
systems with sophisticated collective intelligence. Composed of simple interacting agents …

Swarm intelligence is a relatively new approach to problem solving that takes inspiration
from the social behaviors of insects and of other animals. In particular, ants have inspired a …

Advances in processor, memory and radio technology will enable small and cheap nodes
capable of sensing, communication and computation. Networks of such nodes can …

This article presents an overview of recent work on ant algorithms, that is, algorithms for
discrete optimization that took inspiration from the observation of ant colonies' foraging …

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

A trusted routing scheme is very important to ensure the routing security and efficiency of
wireless sensor networks (WSNs). There are a lot of studies on improving the …

Cooperative multi-agent systems (MAS) are ones in which several agents attempt, through
their interaction, to jointly solve tasks or to maximize utility. Due to the interactions among the …