Recent Advances In Learning Automata

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Recent Advances In Learning Automata
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Author : Alireza Rezvanian
language : en
Publisher: Springer
Release Date : 2018-01-17
Recent Advances In Learning Automata written by Alireza Rezvanian and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-17 with Technology & Engineering categories.
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.
Cellular Learning Automata Theory And Applications
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Author : Reza Vafashoar
language : en
Publisher: Springer Nature
Release Date : 2020-07-24
Cellular Learning Automata Theory And Applications written by Reza Vafashoar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-24 with Technology & Engineering categories.
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
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Author : Alireza Rezvanian
language : en
Publisher: Springer
Release Date : 2019-01-22
Learning Automata Approach For Social Networks written by Alireza Rezvanian and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-22 with Technology & Engineering categories.
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.
Advances In Learning Automata And Intelligent Optimization
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Author : Javidan Kazemi Kordestani
language : en
Publisher: Springer Nature
Release Date : 2021-06-23
Advances In Learning Automata And Intelligent Optimization written by Javidan Kazemi Kordestani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-23 with Technology & Engineering categories.
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.
Recent Advances In Optimization And Its Applications In Engineering
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Author : Moritz Diehl
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-21
Recent Advances In Optimization And Its Applications In Engineering written by Moritz Diehl and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-21 with Technology & Engineering categories.
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.
Recent Advances In Reinforcement Learning
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Author : Leslie Pack Kaelbling
language : en
Publisher: Springer
Release Date : 2007-08-28
Recent Advances In Reinforcement Learning written by Leslie Pack Kaelbling and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-28 with Computers categories.
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
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Author : Radek Matoušek
language : en
Publisher: Springer
Release Date : 2017-05-20
Recent Advances In Soft Computing written by Radek Matoušek and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-20 with Technology & Engineering categories.
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.
Recent Advances In Internet Of Things And Machine Learning
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Author : Valentina E. Balas
language : en
Publisher: Springer Nature
Release Date : 2022-02-14
Recent Advances In Internet Of Things And Machine Learning written by Valentina E. Balas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-14 with Technology & Engineering categories.
This book covers a domain that is significantly impacted by the growth of soft computing. Internet of Things (IoT)-related applications are gaining much attention with more and more devices which are getting connected, and they become the potential components of some smart applications. Thus, a global enthusiasm has sparked over various domains such as health, agriculture, energy, security, and retail. So, in this book, the main objective is to capture this multifaceted nature of IoT and machine learning in one single place. According to the contribution of each chapter, the book also provides a future direction for IoT and machine learning research. The objectives of this book are to identify different issues, suggest feasible solutions to those identified issues, and enable researchers and practitioners from both academia and industry to interact with each other regarding emerging technologies related to IoT and machine learning. In this book, we look for novel chapters that recommend new methodologies, recent advancement, system architectures, and other solutions to prevail over the limitations of IoT and machine learning.
Recent Advances In Big Data And Deep Learning
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Author : Luca Oneto
language : en
Publisher: Springer
Release Date : 2019-04-02
Recent Advances In Big Data And Deep Learning written by Luca Oneto and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-02 with Computers categories.
This book presents the original articles that have been accepted in the 2019 INNS Big Data and Deep Learning (INNS BDDL) international conference, a major event for researchers in the field of artificial neural networks, big data and related topics, organized by the International Neural Network Society and hosted by the University of Genoa. In 2019 INNS BDDL has been held in Sestri Levante (Italy) from April 16 to April 18. More than 80 researchers from 20 countries participated in the INNS BDDL in April 2019. In addition to regular sessions, INNS BDDL welcomed around 40 oral communications, 6 tutorials have been presented together with 4 invited plenary speakers. This book covers a broad range of topics in big data and deep learning, from theoretical aspects to state-of-the-art applications. This book is directed to both Ph.D. students and Researchers in the field in order to provide a general picture of the state-of-the-art on the topics addressed by the conference.
Combinatorial Algorithms
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Author : Cristina Bazgan
language : en
Publisher: Springer Nature
Release Date : 2022-05-29
Combinatorial Algorithms written by Cristina Bazgan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-29 with Computers categories.
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.