Automata models of learning systems introduced in the 1960s were popularized as learning
automata (LA) in a survey paper by Narendra and Thathachar (1974). Since then, there …

The fastest learning automata (LA) algorithms currently available fall in the family of
estimator algorithms introduced by Thathachar and Sastry (1986). The pioneering work of …

With the increasing demand for real-time road safety services and infotainment applications
on vehicles, the development of an efficient wireless mobile communication became crucial …

LEARNING automata [1] have attracted a considerable in-terest in the last three decades.
They are adaptive decision making devices that operate in unknown stochastic …

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

In this paper, we formally present a novel estimation method, referred to as the Stochastic
Learning Weak Estimator (SLWE), which yields the estimate of the parameters of a binomial …

Honey bee colonies demonstrate robust adaptive efficient agent-based communications and
task allocations without centralized controls–desirable features in network design. This book …

Cooperative communication exploits spatial diversity via relay node antennas to increase
data rates in wireless networks. Relay node selection, therefore, plays a critical role in …

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 …

One of today's most serious social, economical and environmental problems is traffic
congestion. In addition to the financial cost of the problem, the number of traffic related …