Context Sensitive Grammatical Evolution
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Context Sensitive Grammatical Evolution
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Author : James Vincent Patten
language : en
Publisher:
Release Date : 2020
Context Sensitive Grammatical Evolution written by James Vincent Patten and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Grammatical Evolution
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Author : Michael O'Neill
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Grammatical Evolution written by Michael O'Neill 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 2012-12-06 with Computers categories.
Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language provides the first comprehensive introduction to Grammatical Evolution, a novel approach to Genetic Programming that adopts principles from molecular biology in a simple and useful manner, coupled with the use of grammars to specify legal structures in a search. Grammatical Evolution's rich modularity gives a unique flexibility, making it possible to use alternative search strategies - whether evolutionary, deterministic or some other approach - and to even radically change its behavior by merely changing the grammar supplied. This approach to Genetic Programming represents a powerful new weapon in the Machine Learning toolkit that can be applied to a diverse set of problem domains.
Handbook Of Grammatical Evolution
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Author : Conor Ryan
language : en
Publisher: Springer
Release Date : 2018-09-11
Handbook Of Grammatical Evolution written by Conor Ryan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-11 with Computers categories.
This handbook offers a comprehensive treatise on Grammatical Evolution (GE), a grammar-based Evolutionary Algorithm that employs a function to map binary strings into higher-level structures such as programs. GE's simplicity and modular nature make it a very flexible tool. Since its introduction almost twenty years ago, researchers have applied it to a vast range of problem domains, including financial modelling, parallel programming and genetics. Similarly, much work has been conducted to exploit and understand the nature of its mapping scheme, triggering additional research on everything from different grammars to alternative mappers to initialization. The book first introduces GE to the novice, providing a thorough description of GE along with historical key advances. Two sections follow, each composed of chapters from international leading researchers in the field. The first section concentrates on analysis of GE and its operation, giving valuable insight into set up and deployment. The second section consists of seven chapters describing radically different applications of GE. The contributions in this volume are beneficial to both novices and experts alike, as they detail the results and researcher experiences of applying GE to large scale and difficult problems. Topics include: • Grammar design • Bias in GE • Mapping in GE • Theory of disruption in GE · Structured GE · Geometric semantic GE · GE and semantics · Multi- and Many-core heterogeneous parallel GE · Comparing methods to creating constants in GE · Financial modelling with GE · Synthesis of parallel programs on multi-cores · Design, architecture and engineering with GE · Computational creativity and GE · GE in the prediction of glucose for diabetes · GE approaches to bioinformatics and system genomics · GE with coevolutionary algorithms in cybersecurity · Evolving behaviour trees with GE for platform games · Business analytics and GE for the prediction of patient recruitment in multicentre clinical trials
State Of The Art On Grammatical Inference Using Evolutionary Method
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Author : Hari Mohan Pandey
language : en
Publisher: Academic Press
Release Date : 2021-11-13
State Of The Art On Grammatical Inference Using Evolutionary Method written by Hari Mohan Pandey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-13 with Science categories.
State of the Art on Grammatical Inference Using Evolutionary Method presents an approach for grammatical inference (GI) using evolutionary algorithms. Grammatical inference deals with the standard learning procedure to acquire grammars based on evidence about the language. It has been extensively studied due to its high importance in various fields of engineering and science. The book's prime purpose is to enhance the current state-of-the-art of grammatical inference methods and present new evolutionary algorithms-based approaches for context free grammar induction. The book's focus lies in the development of robust genetic algorithms for context free grammar induction. The new algorithms discussed in this book incorporate Boolean-based operators during offspring generation within the execution of the genetic algorithm. Hence, the user has no limitation on utilizing the evolutionary methods for grammatical inference. Discusses and summarizes the latest developments in Grammatical Inference, with a focus on Evolutionary Methods Provides an understanding of premature convergence as well as genetic algorithms Presents a performance analysis of genetic algorithms as well as a complete look into the wide range of applications of Grammatical Inference methods Demonstrates how to develop a robust experimental environment to conduct experiments using evolutionary methods and algorithms
Grammars For Programming Languages
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Author : J. Craig Cleaveland
language : en
Publisher: Elsevier Publishing Company
Release Date : 1977
Grammars For Programming Languages written by J. Craig Cleaveland and has been published by Elsevier Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1977 with Computers categories.
Thus, the organization of the book as it finally evolved contains two introductory chapters that can be read by anyone familiar with a programming language. These chapters provide a general background in the commonly-used grammatical notations describing the syntax of a programming language. This is information that should be familiar to anyone who programs-unfortunately, it is familiar to only a very few. With the information contained in these first two chapters, the programmer should have confident access to the syntactic portions of programming-language reference manuals. This includes an understanding of what will not appear in the syntax as well as what should appear there. The remainder of the book builds on this basic foundation exploring the limits of definitional possibilities using a grammatical formalism. To this end, the third chapter introduces the ALGOL 68 grammatical formalism with extensive examples. The fourth chapter gives four grammars describing a simple programming language. This illustrates the evolution of grammatical definitions from ALGOL 60 to ALGOL 68 and beyond. The third grammar in the fourth chapter successfully supplies an answer to Martin Kay's germinal challenge.
Grammar Based Feature Generation For Time Series Prediction
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Author : Anthony Mihirana De Silva
language : en
Publisher: Springer
Release Date : 2015-02-14
Grammar Based Feature Generation For Time Series Prediction written by Anthony Mihirana De Silva and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-14 with Technology & Engineering categories.
This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series continues to attract considerable attention due to the difficulty of the prediction problems compounded by the non-linear and non-stationary nature of the real world time-series. The performance of machine learning techniques, among other things, depends on suitable engineering of features. This book proposes a systematic way for generating suitable features using context-free grammar. A number of feature selection criteria are investigated and a hybrid feature generation and selection algorithm using grammatical evolution is proposed. The book contains graphical illustrations to explain the feature generation process. The proposed approaches are demonstrated by predicting the closing price of major stock market indices, peak electricity load and net hourly foreign exchange client trade volume. The proposed method can be applied to a wide range of machine learning architectures and applications to represent complex feature dependencies explicitly when machine learning cannot achieve this by itself. Industrial applications can use the proposed technique to improve their predictions.
Foundations In Grammatical Evolution For Dynamic Environments
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Author : Ian Dempsey
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-07
Foundations In Grammatical Evolution For Dynamic Environments written by Ian Dempsey 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 2009-04-07 with Mathematics categories.
Dynamic environments abound, encompassing many real-world problems in fields as diverse as finance, engineering, biology and business. A vibrant research literature has emerged which takes inspiration from evolutionary processes to develop problem-solvers for these environments. 'Foundations in Grammatical Evolution for Dynamic Environments' is a cutting edge volume illustrating current state of the art in applying grammar-based evolutionary computation to solve real-world problems in dynamic environments. The book provides a clear introduction to dynamic environments and the types of change that can occur. This is followed by a detailed description of evolutionary computation, concentrating on the powerful Grammatical Evolution methodology. It continues by addressing fundamental issues facing all Evolutionary Algorithms in dynamic problems, such as how to adapt and generate constants, how to enhance evolvability and maintain diversity. Finally, the developed methods are illustrated with application to the real-world dynamic problem of trading on financial time-series. The book was written to be accessible to a wide audience and should be of interest to practitioners, academics and students, who are seeking to apply grammar-based evolutionary algorithms to solve problems in dynamic environments. 'Foundations in Grammatical Evolution for Dynamic Environments' is the second book dedicated to the topic of Grammatical Evolution.
Encyclopedia Of Artificial Intelligence
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Author : Juan Ramon Rabunal
language : en
Publisher: IGI Global
Release Date : 2009-01-01
Encyclopedia Of Artificial Intelligence written by Juan Ramon Rabunal and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-01 with Computers categories.
"This book is a comprehensive and in-depth reference to the most recent developments in the field covering theoretical developments, techniques, technologies, among others"--Provided by publisher.
Genetic Programming
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Author : James A. Foster
language : en
Publisher: Springer
Release Date : 2003-07-31
Genetic Programming written by James A. Foster and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-07-31 with Computers categories.
Thisvolumerecordstheproceedingsofthe?fthEuropeanconferenceonGenetic Programming(EuroGP2002)whichtookplaceinKinsale,IrelandonApril3–5, 2002, continuing an established tradition of yearly meetings among the most prominent researchers on Genetic Programming in Europe and beyond; their proceedings have always been published in the LNCS series by Springer-Verlag. EuroGP began life in Paris in 1998 as an international workshop (April 14– 15, LNCS 1391); a second workshop took place in G ̈ oteborg in 1999 (May 26– 27, LNCS 1598). Its ?rst appearance as a conference was in the year 2000 in Edinburgh (April 15–16, LNCS 1802), followed by last year’s conference held at Lake Como (April 18–19, LNCS 2038). Since the beginning, EuroGP has been co-located with a series of specialist workshops on applications of evolutionary algorithms (LNCS 1468, 1596, 1803, and 2037). In keeping with that tradition, the EvoWorkshops were also held in Kinsale this year at the same time (LNCS 2279). Genetic Programming (GP) is a branch of Evolutionary Computation in which populations of computer programs are made to evolve and adapt to so- ing a particular problem or task by a process that draws its inspiration from Biology and Darwinian evolution. GP is a very versatile technique, which has been applied to a wide range of tasks, as a quick inspection of the 32 papers in these proceedings will easily reveal: economics, robotics, engineering, statistics, pharmacology,electronics,and?nancearebutsomeofthedomainsinwhichthey havebeenemployed.AlthoughtherateofapplicationofGPtoproblemsisst- dily growing, this conference is characterized by its concern with the theoretical foundations of GP: investigation of these issues is attaining an ever increasing depth and maturity.
Information Processing With Evolutionary Algorithms
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Author : Manuel Grana
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-03-30
Information Processing With Evolutionary Algorithms written by Manuel Grana 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 2006-03-30 with Computers categories.
Provides a broad sample of current information processing applications Includes examples of successful applications that will encourage practitioners to apply the techniques described in the book to real-life problems