Evolutionary Learning

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Evolutionary Learning: Advances in Theories and Algorithms

Author : Zhi-Hua Zhou
Publisher : Springer
ISBN 13 : 9811359563
Total Pages : 361 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Evolutionary Learning: Advances in Theories and Algorithms by : Zhi-Hua Zhou

Download or read book Evolutionary Learning: Advances in Theories and Algorithms written by Zhi-Hua Zhou and published by Springer. This book was released on 2019-05-22 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many machine learning tasks involve solving complex optimization problems, such as working on non-differentiable, non-continuous, and non-unique objective functions; in some cases it can prove difficult to even define an explicit objective function. Evolutionary learning applies evolutionary algorithms to address optimization problems in machine learning, and has yielded encouraging outcomes in many applications. However, due to the heuristic nature of evolutionary optimization, most outcomes to date have been empirical and lack theoretical support. This shortcoming has kept evolutionary learning from being well received in the machine learning community, which favors solid theoretical approaches. Recently there have been considerable efforts to address this issue. This book presents a range of those efforts, divided into four parts. Part I briefly introduces readers to evolutionary learning and provides some preliminaries, while Part II presents general theoretical tools for the analysis of running time and approximation performance in evolutionary algorithms. Based on these general tools, Part III presents a number of theoretical findings on major factors in evolutionary optimization, such as recombination, representation, inaccurate fitness evaluation, and population. In closing, Part IV addresses the development of evolutionary learning algorithms with provable theoretical guarantees for several representative tasks, in which evolutionary learning offers excellent performance.

Evolutionary Learning Algorithms for Neural Adaptive Control

Author : Dimitris C. Dracopoulos
Publisher : Springer
ISBN 13 : 1447109031
Total Pages : 214 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Evolutionary Learning Algorithms for Neural Adaptive Control by : Dimitris C. Dracopoulos

Download or read book Evolutionary Learning Algorithms for Neural Adaptive Control written by Dimitris C. Dracopoulos and published by Springer. This book was released on 2013-12-21 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary Learning Algorithms for Neural Adaptive Control is an advanced textbook, which investigates how neural networks and genetic algorithms can be applied to difficult adaptive control problems which conventional results are either unable to solve , or for which they can not provide satisfactory results. It focuses on the principles involved, rather than on the modelling of the applications themselves, and therefore provides the reader with a good introduction to the fundamental issues involved.

Evolutionary Machine Learning Techniques

Author : Seyedali Mirjalili
Publisher : Springer Nature
ISBN 13 : 9813299908
Total Pages : 286 pages
Book Rating : 4.8/5 (132 download)

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Book Synopsis Evolutionary Machine Learning Techniques by : Seyedali Mirjalili

Download or read book Evolutionary Machine Learning Techniques written by Seyedali Mirjalili and published by Springer Nature. This book was released on 2019-11-11 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews, and the training algorithms for machine learning using classical and modern nature-inspired techniques. It also investigates the pros and cons of classical training algorithms. It features a range of proven and recent nature-inspired algorithms used to train different types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization algorithm, ant lion optimizer, moth flame algorithm, dragonfly algorithm, salp swarm algorithm, multi-verse optimizer, and sine cosine algorithm. The book also covers applications of the improved artificial neural networks to solve classification, clustering, prediction and regression problems in diverse fields.

Evolutionary Approach to Machine Learning and Deep Neural Networks

Author : Hitoshi Iba
Publisher : Springer
ISBN 13 : 9811302006
Total Pages : 245 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Evolutionary Approach to Machine Learning and Deep Neural Networks by : Hitoshi Iba

Download or read book Evolutionary Approach to Machine Learning and Deep Neural Networks written by Hitoshi Iba and published by Springer. This book was released on 2018-06-15 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides theoretical and practical knowledge about a methodology for evolutionary algorithm-based search strategy with the integration of several machine learning and deep learning techniques. These include convolutional neural networks, Gröbner bases, relevance vector machines, transfer learning, bagging and boosting methods, clustering techniques (affinity propagation), and belief networks, among others. The development of such tools contributes to better optimizing methodologies. Beginning with the essentials of evolutionary algorithms and covering interdisciplinary research topics, the contents of this book are valuable for different classes of readers: novice, intermediate, and also expert readers from related fields. Following the chapters on introduction and basic methods, Chapter 3 details a new research direction, i.e., neuro-evolution, an evolutionary method for the generation of deep neural networks, and also describes how evolutionary methods are extended in combination with machine learning techniques. Chapter 4 includes novel methods such as particle swarm optimization based on affinity propagation (PSOAP), and transfer learning for differential evolution (TRADE), another machine learning approach for extending differential evolution. The last chapter is dedicated to the state of the art in gene regulatory network (GRN) research as one of the most interesting and active research fields. The author describes an evolving reaction network, which expands the neuro-evolution methodology to produce a type of genetic network suitable for biochemical systems and has succeeded in designing genetic circuits in synthetic biology. The author also presents real-world GRN application to several artificial intelligent tasks, proposing a framework of motion generation by GRNs (MONGERN), which evolves GRNs to operate a real humanoid robot.

Evolution and Learning

Author : Bruce H. Weber
Publisher : MIT Press
ISBN 13 : 9780262232296
Total Pages : 360 pages
Book Rating : 4.2/5 (322 download)

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Book Synopsis Evolution and Learning by : Bruce H. Weber

Download or read book Evolution and Learning written by Bruce H. Weber and published by MIT Press. This book was released on 2003 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essays on the contributions to historical and contemporary evolutionary theory of the Baldwin effect, which postulates the effects of learned behaviors on evolutionary change.

Signals

Author : Brian Skyrms
Publisher : Oxford University Press
ISBN 13 : 0199580820
Total Pages : 208 pages
Book Rating : 4.1/5 (995 download)

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Book Synopsis Signals by : Brian Skyrms

Download or read book Signals written by Brian Skyrms and published by Oxford University Press. This book was released on 2010-04-08 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brian Skyrms offers a fascinating demonstration of how fundamental signals are to our world. He uses various scientific tools to investigate how meaning and communication develop. Signals operate in networks of senders and receivers at all levels of life, transmitting and processing information. That is how humans and animals think and interact.

Rule-Based Evolutionary Online Learning Systems

Author : Martin V. Butz
Publisher : Springer Science & Business Media
ISBN 13 : 3540253793
Total Pages : 279 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Rule-Based Evolutionary Online Learning Systems by : Martin V. Butz

Download or read book Rule-Based Evolutionary Online Learning Systems written by Martin V. Butz and published by Springer Science & Business Media. This book was released on 2005-11-24 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rule-basedevolutionaryonlinelearningsystems,oftenreferredtoasMichig- style learning classi?er systems (LCSs), were proposed nearly thirty years ago (Holland, 1976; Holland, 1977) originally calling them cognitive systems. LCSs combine the strength of reinforcement learning with the generali- tion capabilities of genetic algorithms promising a ?exible, online general- ing, solely reinforcement dependent learning system. However, despite several initial successful applications of LCSs and their interesting relations with a- mal learning and cognition, understanding of the systems remained somewhat obscured. Questions concerning learning complexity or convergence remained unanswered. Performance in di?erent problem types, problem structures, c- ceptspaces,andhypothesisspacesstayednearlyunpredictable. Thisbookhas the following three major objectives: (1) to establish a facetwise theory - proachforLCSsthatpromotessystemanalysis,understanding,anddesign;(2) to analyze, evaluate, and enhance the XCS classi?er system (Wilson, 1995) by the means of the facetwise approach establishing a fundamental XCS learning theory; (3) to identify both the major advantages of an LCS-based learning approach as well as the most promising potential application areas. Achieving these three objectives leads to a rigorous understanding of LCS functioning that enables the successful application of LCSs to diverse problem types and problem domains. The quantitative analysis of XCS shows that the inter- tive, evolutionary-based online learning mechanism works machine learning competitively yielding a low-order polynomial learning complexity. Moreover, the facetwise analysis approach facilitates the successful design of more - vanced LCSs including Holland’s originally envisioned cognitive systems. Martin V.

Learning

Author : Jerome Frieman
Publisher : SAGE Publications
ISBN 13 : 1483359220
Total Pages : 609 pages
Book Rating : 4.4/5 (833 download)

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Book Synopsis Learning by : Jerome Frieman

Download or read book Learning written by Jerome Frieman and published by SAGE Publications. This book was released on 2015-07-29 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning: A Behavioral, Cognitive, and Evolutionary Synthesis by Jerome Frieman and Steve Reilly provides an integrated account of the psychological processes involved in learning and conditioning and their influence on human behavior. With a skillful blend of behavioral, cognitive, and evolutionary themes, the text explores various types of learning as adaptive specialization that evolved through natural selection. Robust pedagogy and relevant examples bring concepts to life in this unique and accessible approach to the field.

Population Games and Evolutionary Dynamics

Author : William H. Sandholm
Publisher : MIT Press
ISBN 13 : 0262195879
Total Pages : 618 pages
Book Rating : 4.2/5 (621 download)

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Book Synopsis Population Games and Evolutionary Dynamics by : William H. Sandholm

Download or read book Population Games and Evolutionary Dynamics written by William H. Sandholm and published by MIT Press. This book was released on 2010-12-17 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary game theory studies the behaviour of large populations of strategically interacting agents & is used by economists to predict in settings where traditional assumptions about the rationality of agents & knowledge may be inapplicable.

Deep Neural Evolution

Author : Hitoshi Iba
Publisher : Springer Nature
ISBN 13 : 9811536856
Total Pages : 437 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Deep Neural Evolution by : Hitoshi Iba

Download or read book Deep Neural Evolution written by Hitoshi Iba and published by Springer Nature. This book was released on 2020-05-20 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book delivers the state of the art in deep learning (DL) methods hybridized with evolutionary computation (EC). Over the last decade, DL has dramatically reformed many domains: computer vision, speech recognition, healthcare, and automatic game playing, to mention only a few. All DL models, using different architectures and algorithms, utilize multiple processing layers for extracting a hierarchy of abstractions of data. Their remarkable successes notwithstanding, these powerful models are facing many challenges, and this book presents the collaborative efforts by researchers in EC to solve some of the problems in DL. EC comprises optimization techniques that are useful when problems are complex or poorly understood, or insufficient information about the problem domain is available. This family of algorithms has proven effective in solving problems with challenging characteristics such as non-convexity, non-linearity, noise, and irregularity, which dampen the performance of most classic optimization schemes. Furthermore, EC has been extensively and successfully applied in artificial neural network (ANN) research —from parameter estimation to structure optimization. Consequently, EC researchers are enthusiastic about applying their arsenal for the design and optimization of deep neural networks (DNN). This book brings together the recent progress in DL research where the focus is particularly on three sub-domains that integrate EC with DL: (1) EC for hyper-parameter optimization in DNN; (2) EC for DNN architecture design; and (3) Deep neuroevolution. The book also presents interesting applications of DL with EC in real-world problems, e.g., malware classification and object detection. Additionally, it covers recent applications of EC in DL, e.g. generative adversarial networks (GAN) training and adversarial attacks. The book aims to prompt and facilitate the research in DL with EC both in theory and in practice.

Evolution Education Re-considered

Author : Ute Harms
Publisher : Springer
ISBN 13 : 3030146987
Total Pages : 347 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Evolution Education Re-considered by : Ute Harms

Download or read book Evolution Education Re-considered written by Ute Harms and published by Springer. This book was released on 2019-07-16 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection presents research-based interventions using existing knowledge to produce new pedagogies to teach evolution to learners more successfully, whether in schools or elsewhere. ‘Success’ here is measured as cognitive gains, as acceptance of evolution or an increased desire to continue to learn about it. Aside from introductory and concluding chapters by the editors, each chapter consists of a research-based intervention intended to enable evolution to be taught successfully; all these interventions have been researched and evaluated by the chapters’ authors and the findings are presented along with discussions of the implications. The result is an important compendium of studies from around the word conducted both inside and outside of school. The volume is unique and provides an essential reference point and platform for future work for the foreseeable future.

Evolutionary Optimization

Author : Ruhul Sarker
Publisher : Springer Science & Business Media
ISBN 13 : 0306480417
Total Pages : 416 pages
Book Rating : 4.3/5 (64 download)

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Book Synopsis Evolutionary Optimization by : Ruhul Sarker

Download or read book Evolutionary Optimization written by Ruhul Sarker and published by Springer Science & Business Media. This book was released on 2006-04-11 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary computation techniques have attracted increasing att- tions in recent years for solving complex optimization problems. They are more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. E- lutionary computation techniques can deal with complex optimization problems better than traditional optimization techniques. However, most papers on the application of evolutionary computation techniques to Operations Research /Management Science (OR/MS) problems have scattered around in different journals and conference proceedings. They also tend to focus on a very special and narrow topic. It is the right time that an archival book series publishes a special volume which - cludes critical reviews of the state-of-art of those evolutionary com- tation techniques which have been found particularly useful for OR/MS problems, and a collection of papers which represent the latest devel- ment in tackling various OR/MS problems by evolutionary computation techniques. This special volume of the book series on Evolutionary - timization aims at filling in this gap in the current literature. The special volume consists of invited papers written by leading - searchers in the field. All papers were peer reviewed by at least two recognised reviewers. The book covers the foundation as well as the practical side of evolutionary optimization.

Data-Driven Evolutionary Optimization

Author : Yaochu Jin
Publisher : Springer Nature
ISBN 13 : 3030746402
Total Pages : 393 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Data-Driven Evolutionary Optimization by : Yaochu Jin

Download or read book Data-Driven Evolutionary Optimization written by Yaochu Jin and published by Springer Nature. This book was released on 2021-06-28 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning, and metaheuristics. Written by world-leading academic researchers who are extremely experienced in industrial applications, this self-contained book is the first of its kind that provides comprehensive background knowledge, particularly practical guidelines, and state-of-the-art techniques. New algorithms are carefully explained, further elaborated with pseudocode or flowcharts, and full working source code is made freely available. This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms. Applications of data-driven optimization ranging from aerodynamic design, optimization of industrial processes, to deep neural architecture search are included.

Anticipatory Learning Classifier Systems

Author : Martin V. Butz
Publisher : Springer Science & Business Media
ISBN 13 : 1461508916
Total Pages : 197 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Anticipatory Learning Classifier Systems by : Martin V. Butz

Download or read book Anticipatory Learning Classifier Systems written by Martin V. Butz and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: Anticipatory Learning Classifier Systems describes the state of the art of anticipatory learning classifier systems-adaptive rule learning systems that autonomously build anticipatory environmental models. An anticipatory model specifies all possible action-effects in an environment with respect to given situations. It can be used to simulate anticipatory adaptive behavior. Anticipatory Learning Classifier Systems highlights how anticipations influence cognitive systems and illustrates the use of anticipations for (1) faster reactivity, (2) adaptive behavior beyond reinforcement learning, (3) attentional mechanisms, (4) simulation of other agents and (5) the implementation of a motivational module. The book focuses on a particular evolutionary model learning mechanism, a combination of a directed specializing mechanism and a genetic generalizing mechanism. Experiments show that anticipatory adaptive behavior can be simulated by exploiting the evolving anticipatory model for even faster model learning, planning applications, and adaptive behavior beyond reinforcement learning. Anticipatory Learning Classifier Systems gives a detailed algorithmic description as well as a program documentation of a C++ implementation of the system.

Leading the Evolution

Author : Mike Ruyle
Publisher : Marzano Resources
ISBN 13 : 9781943360222
Total Pages : 0 pages
Book Rating : 4.3/5 (62 download)

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Book Synopsis Leading the Evolution by : Mike Ruyle

Download or read book Leading the Evolution written by Mike Ruyle and published by Marzano Resources. This book was released on 2018-08-31 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now is the time to evolve from the existing model of schooling into one that is more innovative, relevant, effective, and successful. Leading the Evolution introduces a three-pronged approach to driving substantive change (called the evolutionary triad) that connects transformative educational leadership, student engagement, and teacher optimism around personalized competency-based education. Each chapter includes supporting research and theory, as well as clear direction and strategies for putting the evolutionary triad into practice. Learn how and why to implement a personalized competency-based approach for academic achievement and student engagement: Understand the current state of education and why changing to a competency-based approach is imperative. Identify the instructional leadership behaviors that lead to the organizational and cultural shift necessary to transform the current education paradigm. Consider in detail all three points of the evolutionary triad: transformational instructional leadership, teacher optimism, and student engagement. Examine the central focus of the evolutionary triad: personalized, competency-based education. Explore educational leadership practices that support successfully implementing the evolutionary triad and learning competencies in schools. Contents: Introduction Chapter 1: Foundations for Evolution Chapter 2: The Transformational Instructional Leader Chapter 3: The Optimistic Teacher Chapter 4: The Engaged Student Chapter 5: The High-Impact School Epilogue References and Resources Index

The Evolution of the Sensitive Soul

Author : Simona Ginsburg
Publisher : MIT Press
ISBN 13 : 0262039303
Total Pages : 665 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis The Evolution of the Sensitive Soul by : Simona Ginsburg

Download or read book The Evolution of the Sensitive Soul written by Simona Ginsburg and published by MIT Press. This book was released on 2019-03-12 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new theory about the origins of consciousness that finds learning to be the driving force in the evolutionary transition to basic consciousness. What marked the evolutionary transition from organisms that lacked consciousness to those with consciousness—to minimal subjective experiencing, or, as Aristotle described it, “the sensitive soul”? In this book, Simona Ginsburg and Eva Jablonka propose a new theory about the origin of consciousness that finds learning to be the driving force in the transition to basic consciousness. Using a methodology similar to that used by scientists when they identified the transition from non-life to life, Ginsburg and Jablonka suggest a set of criteria, identify a marker for the transition to minimal consciousness, and explore the far-reaching biological, psychological, and philosophical implications. After presenting the historical, neurobiological, and philosophical foundations of their analysis, Ginsburg and Jablonka propose that the evolutionary marker of basic or minimal consciousness is a complex form of associative learning, which they term unlimited associative learning (UAL). UAL enables an organism to ascribe motivational value to a novel, compound, non-reflex-inducing stimulus or action, and use it as the basis for future learning. Associative learning, Ginsburg and Jablonka argue, drove the Cambrian explosion and its massive diversification of organisms. Finally, Ginsburg and Jablonka propose symbolic language as a similar type of marker for the evolutionary transition to human rationality—to Aristotle's “rational soul.”

Evolutionary Algorithms for Solving Multi-Objective Problems

Author : Carlos Coello Coello
Publisher : Springer Science & Business Media
ISBN 13 : 0387367977
Total Pages : 810 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis Evolutionary Algorithms for Solving Multi-Objective Problems by : Carlos Coello Coello

Download or read book Evolutionary Algorithms for Solving Multi-Objective Problems written by Carlos Coello Coello and published by Springer Science & Business Media. This book was released on 2007-08-26 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.