Recent advances in learning automata 1st ed.

Author

• Rezvanian, Alireza

Additional Author(s)

• Saghiri, Ali Mohammad
• Vahidipour, Seyed Mehdi
• Esnaashari, Mehdi
• Meybodi, Mohammad Reza

Publisher

Cham, Switzerland : Springer International Publishing, 2018

Language

English

ISBN

9783319724287

Series

Studies in computational intelligence 754

Subject(s)

• ARTIFICIAL INTELLIGENCE
• COMPUTATIONAL INTELLIGENCE
• ENGINEERING

Notes

. .

Abstract

This book collects recent theoretical advances and concrete applications of learning automata (LAs) in various areas of computer science, presenting a broad treatment of the computer science field in a survey style. Learning automata (LAs) have proven to be effective decision-making agents, especially within unknown stochastic environments. The book starts with a brief explanation of LAs and their baseline variations. It subsequently introduces readers to a number of recently developed, complex structures used to supplement LAs, and describes their steady-state behaviors. These complex structures have been developed because, by design, LAs are simple units used to perform simple tasks; their full potential can only be tapped when several interconnected LAs cooperate to produce a group synergy. In turn, the next part of the book highlights a range of LA-based applications in diverse computer science domains, from wireless sensor networks, to peer-to-peer networks, to complex social networks, and finally to Petri nets. The book accompanies the reader on a comprehensive journey, starting from basic concepts, continuing to recent theoretical findings, and ending in the applications of LAs in problems from numerous research domains. As such, the book offers a valuable resource for all computer engineers, scientists, and students, especially those whose work involves the reinforcement learning and artificial intelligence domains.

Physical Dimension

Number of Page(s)

1 online resource (xix, 458 p.)

Dimension

-

Other Desc.

ill. (in color.)

Summary / Review / Table of Content

Learning automata theory --
Cellular learning automata --
Learning automata for wireless sensor networks --
Learning automata for cognitive Peer-to-peer networks --
Learning automata for Complex Social Networks --
Adaptive petri net based on learning automata --
Summary and future directions.

Exemplar(s)

#	Accession No.	Call Number	Location	Status
1.	01180/20	006.31 Rez R	Online !	Available