Recent Advances In Learning Automata

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Recent Advances in Learning Automata

Alireza Rezvanian,Ali Mohammad Saghiri,Seyed Mehdi Vahidipour,Mehdi Esnaashari,Mohammad Reza Meybodi
Recent Advances in Learning Automata Book PDF

Author : Alireza Rezvanian,Ali Mohammad Saghiri,Seyed Mehdi Vahidipour,Mehdi Esnaashari,Mohammad Reza Meybodi
Publisher : Springer
Page : 458 pages
File Size : 48,9 Mb
Release : 2018-01-17
Category : Technology & Engineering
ISBN : 9783319724287

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Recent Advances in Learning Automata by Alireza Rezvanian,Ali Mohammad Saghiri,Seyed Mehdi Vahidipour,Mehdi Esnaashari,Mohammad Reza Meybodi Pdf

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.

Advances in Learning Automata and Intelligent Optimization

Javidan Kazemi Kordestani,Mehdi Razapoor Mirsaleh,Alireza Rezvanian,Mohammad Reza Meybodi
Advances in Learning Automata and Intelligent Optimization Book PDF

Author : Javidan Kazemi Kordestani,Mehdi Razapoor Mirsaleh,Alireza Rezvanian,Mohammad Reza Meybodi
Publisher : Springer Nature
Page : 340 pages
File Size : 52,7 Mb
Release : 2021-06-23
Category : Technology & Engineering
ISBN : 9783030762919

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Advances in Learning Automata and Intelligent Optimization by Javidan Kazemi Kordestani,Mehdi Razapoor Mirsaleh,Alireza Rezvanian,Mohammad Reza Meybodi Pdf

This book is devoted to the leading research in applying learning automaton (LA) and heuristics for solving benchmark and real-world optimization problems. The ever-increasing application of the LA as a promising reinforcement learning technique in artificial intelligence makes it necessary to provide scholars, scientists, and engineers with a practical discussion on LA solutions for optimization. The book starts with a brief introduction to LA models for optimization. Afterward, the research areas related to LA and optimization are addressed as bibliometric network analysis. Then, LA's application in behavior control in evolutionary computation, and memetic models of object migration automata and cellular learning automata for solving NP hard problems are considered. Next, an overview of multi-population methods for DOPs, LA's application in dynamic optimization problems (DOPs), and the function evaluation management in evolutionary multi-population for DOPs are discussed. Highlighted benefits • Presents the latest advances in learning automata-based optimization approaches. • Addresses the memetic models of learning automata for solving NP-hard problems. • Discusses the application of learning automata for behavior control in evolutionary computation in detail. • Gives the fundamental principles and analyses of the different concepts associated with multi-population methods for dynamic optimization problems.

Advances in Learning Automata and Intelligent Optimization

Javidan Kazemi Kordestani,Mehdi Razapoor Mirsaleh,Alireza Rezvanian,Mohammad Reza Meybodi
Advances in Learning Automata and Intelligent Optimization Book PDF

Author : Javidan Kazemi Kordestani,Mehdi Razapoor Mirsaleh,Alireza Rezvanian,Mohammad Reza Meybodi
Publisher : Unknown
Page : 0 pages
File Size : 52,6 Mb
Release : 2021
Category : Electronic
ISBN : 3030762920

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Advances in Learning Automata and Intelligent Optimization by Javidan Kazemi Kordestani,Mehdi Razapoor Mirsaleh,Alireza Rezvanian,Mohammad Reza Meybodi Pdf

This book is devoted to the leading research in applying learning automaton (LA) and heuristics for solving benchmark and real-world optimization problems. The ever-increasing application of the LA as a promising reinforcement learning technique in artificial intelligence makes it necessary to provide scholars, scientists, and engineers with a practical discussion on LA solutions for optimization. The book starts with a brief introduction to LA models for optimization. Afterward, the research areas related to LA and optimization are addressed as bibliometric network analysis. Then, LA's application in behavior control in evolutionary computation, and memetic models of object migration automata and cellular learning automata for solving NP hard problems are considered. Next, an overview of multi-population methods for DOPs, LA's application in dynamic optimization problems (DOPs), and the function evaluation management in evolutionary multi-population for DOPs are discussed. Highlighted benefits • Presents the latest advances in learning automata-based optimization approaches. • Addresses the memetic models of learning automata for solving NP-hard problems. • Discusses the application of learning automata for behavior control in evolutionary computation in detail. • Gives the fundamental principles and analyses of the different concepts associated with multi-population methods for dynamic optimization problems. .

Cellular Learning Automata: Theory and Applications

Reza Vafashoar,Hossein Morshedlou,Alireza Rezvanian,Mohammad Reza Meybodi
Cellular Learning Automata Theory and Applications Book PDF

Author : Reza Vafashoar,Hossein Morshedlou,Alireza Rezvanian,Mohammad Reza Meybodi
Publisher : Springer Nature
Page : 377 pages
File Size : 41,6 Mb
Release : 2020-07-24
Category : Technology & Engineering
ISBN : 9783030531416

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Cellular Learning Automata: Theory and Applications by Reza Vafashoar,Hossein Morshedlou,Alireza Rezvanian,Mohammad Reza Meybodi Pdf

This book highlights both theoretical and applied advances in cellular learning automata (CLA), a type of hybrid computational model that has been successfully employed in various areas to solve complex problems and to model, learn, or simulate complicated patterns of behavior. Owing to CLA’s parallel and learning abilities, it has proven to be quite effective in uncertain, time-varying, decentralized, and distributed environments. The book begins with a brief introduction to various CLA models, before focusing on recently developed CLA variants. In turn, the research areas related to CLA are addressed as bibliometric network analysis perspectives. The next part of the book presents CLA-based solutions to several computer science problems in e.g. static optimization, dynamic optimization, wireless networks, mesh networks, and cloud computing. Given its scope, the book is well suited for all researchers in the fields of artificial intelligence and reinforcement learning.

Learning Automata Approach for Social Networks

Alireza Rezvanian,Behnaz Moradabadi,Mina Ghavipour,Mohammad Mehdi Daliri Khomami,Mohammad Reza Meybodi
Learning Automata Approach for Social Networks Book PDF

Author : Alireza Rezvanian,Behnaz Moradabadi,Mina Ghavipour,Mohammad Mehdi Daliri Khomami,Mohammad Reza Meybodi
Publisher : Springer
Page : 329 pages
File Size : 42,9 Mb
Release : 2019-01-22
Category : Technology & Engineering
ISBN : 9783030107673

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Learning Automata Approach for Social Networks by Alireza Rezvanian,Behnaz Moradabadi,Mina Ghavipour,Mohammad Mehdi Daliri Khomami,Mohammad Reza Meybodi Pdf

This book begins by briefly explaining learning automata (LA) models and a recently developed cellular learning automaton (CLA) named wavefront CLA. Analyzing social networks is increasingly important, so as to identify behavioral patterns in interactions among individuals and in the networks’ evolution, and to develop the algorithms required for meaningful analysis. As an emerging artificial intelligence research area, learning automata (LA) has already had a significant impact in many areas of social networks. Here, the research areas related to learning and social networks are addressed from bibliometric and network analysis perspectives. In turn, the second part of the book highlights a range of LA-based applications addressing social network problems, from network sampling, community detection, link prediction, and trust management, to recommender systems and finally influence maximization. Given its scope, the book offers a valuable guide for all researchers whose work involves reinforcement learning, social networks and/or artificial intelligence.

Learning Automata

K. Najim,A.S. Poznyak
Learning Automata Book PDF

Author : K. Najim,A.S. Poznyak
Publisher : Elsevier
Page : 236 pages
File Size : 54,5 Mb
Release : 2014-06-28
Category : Computers
ISBN : 9781483299402

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Learning Automata by K. Najim,A.S. Poznyak Pdf

Learning systems have made a significant impact on all areas of engineering problems. They are attractive methods for solving many problems which are too complex, highly non-linear, uncertain, incomplete or non-stationary, and have subtle and interactive exchanges with the environment where they operate. The main aim of the book is to give a systematic treatment of learning automata and to produce a guide to a wide variety of ideas and methods that can be used in learning systems, including enough theoretical material to enable the user of the relevant techniques and concepts to understand why and how they can be used. The book also contains the materials that are necessary for the understanding and development of learning automata for different purposes such as processes identification, optimization and control. Learning Automata: Theory and Applications may be recommended as a reference for courses on learning automata, modelling, control and optimization. The presentation is intended both for graduate students in control theory and statistics and for practising control engineers.

Recent Advances in Optimization and its Applications in Engineering

Moritz Diehl,Francois Glineur,Elias Jarlebring,Wim Michiels
Recent Advances in Optimization and its Applications in Engineering Book PDF

Author : Moritz Diehl,Francois Glineur,Elias Jarlebring,Wim Michiels
Publisher : Springer Science & Business Media
Page : 535 pages
File Size : 42,8 Mb
Release : 2010-09-21
Category : Technology & Engineering
ISBN : 9783642125980

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Recent Advances in Optimization and its Applications in Engineering by Moritz Diehl,Francois Glineur,Elias Jarlebring,Wim Michiels Pdf

Mathematical optimization encompasses both a rich and rapidly evolving body of fundamental theory, and a variety of exciting applications in science and engineering. The present book contains a careful selection of articles on recent advances in optimization theory, numerical methods, and their applications in engineering. It features in particular new methods and applications in the fields of optimal control, PDE-constrained optimization, nonlinear optimization, and convex optimization. The authors of this volume took part in the 14th Belgian-French-German Conference on Optimization (BFG09) organized in Leuven, Belgium, on September 14-18, 2009. The volume contains a selection of reviewed articles contributed by the conference speakers as well as three survey articles by plenary speakers and two papers authored by the winners of the best talk and best poster prizes awarded at BFG09. Researchers and graduate students in applied mathematics, computer science, and many branches of engineering will find in this book an interesting and useful collection of recent ideas on the methods and applications of optimization.

Intelligent Random Walk: An Approach Based on Learning Automata

Ali Mohammad Saghiri,M. Daliri Khomami,Mohammad Reza Meybodi
Intelligent Random Walk An Approach Based on Learning Automata Book PDF

Author : Ali Mohammad Saghiri,M. Daliri Khomami,Mohammad Reza Meybodi
Publisher : Springer
Page : 55 pages
File Size : 43,9 Mb
Release : 2019-01-02
Category : Technology & Engineering
ISBN : 9783030108830

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Intelligent Random Walk: An Approach Based on Learning Automata by Ali Mohammad Saghiri,M. Daliri Khomami,Mohammad Reza Meybodi Pdf

This book examines the intelligent random walk algorithms based on learning automata: these versions of random walk algorithms gradually obtain required information from the nature of the application to improve their efficiency. The book also describes the corresponding applications of this type of random walk algorithm, particularly as an efficient prediction model for large-scale networks such as peer-to-peer and social networks. The book opens new horizons for designing prediction models and problem-solving methods based on intelligent random walk algorithms, which are used for modeling and simulation in various types of networks, including computer, social and biological networks, and which may be employed a wide range of real-world applications.

Recent Advances in Reinforcement Learning

Leslie Pack Kaelbling
Recent Advances in Reinforcement Learning Book PDF

Author : Leslie Pack Kaelbling
Publisher : Springer Science & Business Media
Page : 286 pages
File Size : 48,7 Mb
Release : 1996-03-31
Category : Computers
ISBN : 9780792397052

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Recent Advances in Reinforcement Learning by Leslie Pack Kaelbling Pdf

Recent Advances in Reinforcement Learning addresses current research in an exciting area that is gaining a great deal of popularity in the Artificial Intelligence and Neural Network communities. Reinforcement learning has become a primary paradigm of machine learning. It applies to problems in which an agent (such as a robot, a process controller, or an information-retrieval engine) has to learn how to behave given only information about the success of its current actions. This book is a collection of important papers that address topics including the theoretical foundations of dynamic programming approaches, the role of prior knowledge, and methods for improving performance of reinforcement-learning techniques. These papers build on previous work and will form an important resource for students and researchers in the area. Recent Advances in Reinforcement Learning is an edited volume of peer-reviewed original research comprising twelve invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 22, Numbers 1, 2 and 3).

Recent Advances in Soft Computing

Radek Matoušek
Recent Advances in Soft Computing Book PDF

Author : Radek Matoušek
Publisher : Springer
Page : 278 pages
File Size : 53,6 Mb
Release : 2017-05-20
Category : Technology & Engineering
ISBN : 9783319580883

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Recent Advances in Soft Computing by Radek Matoušek Pdf

This proceeding book contains a collection of selected accepted papers of the Mendel conference held in Brno, Czech Republic in June 2016. The proceedings book contains three chapters which present recent advances in soft computing including intelligent image processing. The Mendel conference was established in 1995 and is named after the scientist and Augustinian priest Gregor J. Mendel who discovered the famous Laws of Heredity. The main aim of the conference is to create a regular possibility for students, academics and researchers to exchange ideas and novel research methods on a yearly basis.

Learning Automata and Their Applications to Intelligent Systems

JunQi Zhang,MengChu Zhou
Learning Automata and Their Applications to Intelligent Systems Book PDF

Author : JunQi Zhang,MengChu Zhou
Publisher : John Wiley & Sons
Page : 276 pages
File Size : 44,5 Mb
Release : 2023-12-12
Category : Technology & Engineering
ISBN : 9781394188499

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Learning Automata and Their Applications to Intelligent Systems by JunQi Zhang,MengChu Zhou Pdf

Comprehensive guide on learning automata, introducing two variants to accelerate convergence and computational update speed Learning Automata and Their Applications to Intelligent Systems provides a comprehensive guide on learning automata from the perspective of principles, algorithms, improvement directions, and applications. The text introduces two variants to accelerate the convergence speed and computational update speed, respectively; these two examples demonstrate how to design new learning automata for a specific field from the aspect of algorithm design to give full play to the advantage of learning automata. As noisy optimization problems exist widely in various intelligent systems, this book elaborates on how to employ learning automata to solve noisy optimization problems from the perspective of algorithm design and application. The existing and most representative applications of learning automata include classification, clustering, game, knapsack, network, optimization, ranking, and scheduling. They are well-discussed. Future research directions to promote an intelligent system are suggested. Written by two highly qualified academics with significant experience in the field, Learning Automata and Their Applications to Intelligent Systems covers such topics as: Mathematical analysis of the behavior of learning automata, along with suitable learning algorithms Two application-oriented learning automata: one to discover and track spatiotemporal event patterns, and the other to solve stochastic searching on a line Demonstrations of two pioneering variants of Optimal Computing Budge Allocation (OCBA) methods and how to combine learning automata with ordinal optimization How to achieve significantly faster convergence and higher accuracy than classical pursuit schemes via lower computational complexity of updating the state probability A timely text in a rapidly developing field, Learning Automata and Their Applications to Intelligent Systems is an essential resource for researchers in machine learning, engineering, operation, and management. The book is also highly suitable for graduate level courses on machine learning, soft computing, reinforcement learning and stochastic optimization.

Recent Advances in Information and Communication Technology

Sirapat Boonkrong,Herwig Unger,Phayung Meesad
Recent Advances in Information and Communication Technology Book PDF

Author : Sirapat Boonkrong,Herwig Unger,Phayung Meesad
Publisher : Springer Science & Business Media
Page : 346 pages
File Size : 41,8 Mb
Release : 2014-04-12
Category : Technology & Engineering
ISBN : 9783319065380

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Recent Advances in Information and Communication Technology by Sirapat Boonkrong,Herwig Unger,Phayung Meesad Pdf

Computer and Information Technology (CIT) are now involved in governmental, industrial, and business domains more than ever. Thus, it is important for CIT personnel to continue academic research to improve technology and its adoption to modern applications. The up-to-date research and technologies must be distributed to researchers and CIT community continuously to aid future development. The 10th International Conference on Computing and Information Technology (IC 2 IT2014) organized by King Mongkut's University of Technology North Bangkok (KMUTNB) and partners provides an exchange of the state of the art and future developments in the two key areas of this process: Computer Networking and Data Mining. Behind the background of the foundation of ASEAN, it becomes clear that efficient languages, business principles and communication methods need to be adapted, unified and especially optimized to gain a maximum benefit to the users and customers of future IT systems.

Combinatorial Algorithms

Cristina Bazgan,Henning Fernau
Combinatorial Algorithms Book PDF

Author : Cristina Bazgan,Henning Fernau
Publisher : Springer Nature
Page : 538 pages
File Size : 49,7 Mb
Release : 2022-05-29
Category : Computers
ISBN : 9783031066788

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Combinatorial Algorithms by Cristina Bazgan,Henning Fernau Pdf

This book constitutes the refereed proceedings of the 33rd International Workshop on Combinatorial Algorithms, IWOCA 2022, which took place as a hybrid event in Trier, Germany, during June 7-9, 2022.The 35 papers presented in these proceedings were carefully reviewed and selected from 86 submissions. They deal with diverse topics related to combinatorial algorithms, such as algorithms and data structures; algorithmic and combinatorical aspects of cryptography and information security; algorithmic game theory and complexity of games; approximation algorithms; complexity theory; combinatorics and graph theory; combinatorial generation, enumeration and counting; combinatorial optimization; combinatorics of words; computational biology; computational geometry; decompositions and combinatorial designs; distributed and network algorithms; experimental combinatorics; fine-grained complexity; graph algorithms and modelling with graphs; graph drawing and graph labelling; network theory and temporal graphs; quantum computing and algorithms for quantum computers; online algorithms; parameterized and exact algorithms; probabilistic andrandomized algorithms; and streaming algorithms.

Evolutionary Computation in Scheduling

Amir H. Gandomi,Ali Emrouznejad,Mo M. Jamshidi,Kalyanmoy Deb,Iman Rahimi
Evolutionary Computation in Scheduling Book PDF

Author : Amir H. Gandomi,Ali Emrouznejad,Mo M. Jamshidi,Kalyanmoy Deb,Iman Rahimi
Publisher : John Wiley & Sons
Page : 323 pages
File Size : 52,8 Mb
Release : 2020-04-09
Category : Mathematics
ISBN : 9781119573876

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Evolutionary Computation in Scheduling by Amir H. Gandomi,Ali Emrouznejad,Mo M. Jamshidi,Kalyanmoy Deb,Iman Rahimi Pdf

Presents current developments in the field of evolutionary scheduling and demonstrates the applicability of evolutionary computational techniques to solving scheduling problems This book provides insight into the use of evolutionary computations (EC) in real-world scheduling, showing readers how to choose a specific evolutionary computation and how to validate the results using metrics and statistics. It offers a spectrum of real-world optimization problems, including applications of EC in industry and service organizations such as healthcare scheduling, aircraft industry, school timetabling, manufacturing systems, and transportation scheduling in the supply chain. It also features problems with different degrees of complexity, practical requirements, user constraints, and MOEC solution approaches. Evolutionary Computation in Scheduling starts with a chapter on scientometric analysis to analyze scientific literature in evolutionary computation in scheduling. It then examines the role and impacts of ant colony optimization (ACO) in job shop scheduling problems, before presenting the application of the ACO algorithm in healthcare scheduling. Other chapters explore task scheduling in heterogeneous computing systems and truck scheduling using swarm intelligence, application of sub-population scheduling algorithm in multi-population evolutionary dynamic optimization, task scheduling in cloud environments, scheduling of robotic disassembly in remanufacturing using the bees algorithm, and more. This book: Provides a representative sampling of real-world problems currently being tackled by practitioners Examines a variety of single-, multi-, and many-objective problems that have been solved using evolutionary computations, including evolutionary algorithms and swarm intelligence Consists of four main parts: Introduction to Scheduling Problems, Computational Issues in Scheduling Problems, Evolutionary Computation, and Evolutionary Computations for Scheduling Problems Evolutionary Computation in Scheduling is ideal for engineers in industries, research scholars, advanced undergraduates and graduate students, and faculty teaching and conducting research in Operations Research and Industrial Engineering.

Learning Automata

Kumpati S. Narendra,Mandayam A.L. Thathachar
Learning Automata Book PDF

Author : Kumpati S. Narendra,Mandayam A.L. Thathachar
Publisher : Courier Corporation
Page : 498 pages
File Size : 54,8 Mb
Release : 2013-05-27
Category : Technology & Engineering
ISBN : 9780486268460

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Learning Automata by Kumpati S. Narendra,Mandayam A.L. Thathachar Pdf

This self-contained introductory text on the behavior of learning automata focuses on how a sequential decision-maker with a finite number of choices responds in a random environment. Topics include fixed structure automata, variable structure stochastic automata, convergence, 0 and S models, nonstationary environments, interconnected automata and games, and applications of learning automata. A must for all students of stochastic algorithms, this treatment is the work of two well-known scientists and is suitable for a one-semester graduate course in automata theory and stochastic algorithms. This volume also provides a fine guide for independent study and a reference for students and professionals in operations research, computer science, artificial intelligence, and robotics. The authors have provided a new preface for this edition.