Link prediction is an important task in Social Network Analysis. The present paper
addresses predicting the emergence of future relationships among nodes in a social …

This book is written for computer engineers, scientists, and students studying/working in
reinforcement learning and artificial intelligence domains. The book collects recent …

Social networks are usually modeled and represented as deterministic graphs with a set of
nodes as users and edges as connection between users of networks. Due to the uncertain …

Recently, several studies have been conducted to design mobility-based multicast routing
protocols for wireless mobile ad hoc networks (MANET). These protocols assume that the …

A learning automaton (LA) is a powerful tool for reinforcement learning. Its action probability
vector plays two roles: 1) deciding when it converges, ie, total computing budget it has used …

In the last decade, numerous efforts have been devoted to design efficient algorithms for
clustering the wireless mobile ad-hoc networks (MANET) considering the network mobility …

Vertex coloring problem is a combinatorial optimization problem in which a color is assigned
to each vertex of the graph such that no two adjacent vertices have the same color. Cellular …

Learning automaton (LA) as one of artificial intelligence techniques is a stochastic model
operating in the framework of the reinforcement learning. LA has been found to be a useful …

Link prediction is a social network research area that tries to predict future links using
network structure. The main approaches in this area are based on predicting future links …

Wireless sensor networks (WSNs) consist of many sensor nodes (SNs) which may be
deployed at different geographical locations to perform multiple tasks such as monitoring …