Advances In Genetic Programming
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Advances In Genetic Programming
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Author : Kenneth E. Kinnear
language : en
Publisher: MIT Press
Release Date : 1994
Advances In Genetic Programming written by Kenneth E. Kinnear and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Computers categories.
Advances in Genetic Programming reports significant results in improving the power of genetic programming, presenting techniques that can be employed immediately in the solution of complex problems in many areas, including machine learning and the simulation of autonomous behavior. Popular languages such as C and C++ are used in manu of the applications and experiments, illustrating how genetic programming is not restricted to symbolic computing languages such as LISP. Researchers interested in getting started in genetic programming will find information on how to begin, on what public-domain code is available, and on how to become part of the active genetic programming community via electronic mail.
Evolutionary Algorithms In Engineering And Computer Science
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Author : K. Miettinen
language : en
Publisher: John Wiley & Sons
Release Date : 1999-07-09
Evolutionary Algorithms In Engineering And Computer Science written by K. Miettinen and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-07-09 with Computers categories.
Evolutionary Algorithms in Engineering and Computer Science Edited by K. Miettinen, University of Jyväskylä, Finland M. M. Mäkelä, University of Jyväskylä, Finland P. Neittaanmäki, University of Jyväskylä, Finland J. Périaux, Dassault Aviation, France What is Evolutionary Computing? Based on the genetic message encoded in DNA, and digitalized algorithms inspired by the Darwinian framework of evolution by natural selection, Evolutionary Computing is one of the most important information technologies of our times. Evolutionary algorithms encompass all adaptive and computational models of natural evolutionary systems - genetic algorithms, evolution strategies, evolutionary programming and genetic programming. In addition, they work well in the search for global solutions to optimization problems, allowing the production of optimization software that is robust and easy to implement. Furthermore, these algorithms can easily be hybridized with traditional optimization techniques. This book presents state-of-the-art lectures delivered by international academic and industrial experts in the field of evolutionary computing. It bridges artificial intelligence and scientific computing with a particular emphasis on real-life problems encountered in application-oriented sectors, such as aerospace, electronics, telecommunications, energy and economics. This rapidly growing field, with its deep understanding and assesssment of complex problems in current practice, provides an effective, modern engineering tool. This book will therefore be of significant interest and value to all postgraduates, research scientists and practitioners facing complex optimization problems.
Advances In Genetic Programming V 2
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Author : Peter J. Angeline
language : en
Publisher:
Release Date : 1996
Advances In Genetic Programming V 2 written by Peter J. Angeline and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computer programming categories.
A Field Guide To Genetic Programming
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Author :
language : en
Publisher: Lulu.com
Release Date : 2008
A Field Guide To Genetic Programming written by and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computers categories.
Genetic programming (GP) is a systematic, domain-independent method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. Using ideas from natural evolution, GP starts from an ooze of random computer programs, and progressively refines them through processes of mutation and sexual recombination, until high-fitness solutions emerge. All this without the user having to know or specify the form or structure of solutions in advance. GP has generated a plethora of human-competitive results and applications, including novel scientific discoveries and patentable inventions. This unique overview of this exciting technique is written by three of the most active scientists in GP. See www.gp-field-guide.org.uk for more information on the book.
Genetic Programming And Data Structures
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Author : W.B. Langdon
language : en
Publisher: Springer Science & Business Media
Release Date : 1998-04-30
Genetic Programming And Data Structures written by W.B. Langdon 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 1998-04-30 with Computers categories.
Computers that `program themselves' has long been an aim of computer scientists. Recently genetic programming (GP) has started to show its promise by automatically evolving programs. Indeed in a small number of problems GP has evolved programs whose performance is similar to or even slightly better than that of programs written by people. The main thrust of GP has been to automatically create functions. While these can be of great use they contain no memory and relatively little work has addressed automatic creation of program code including stored data. This issue is the main focus of Genetic Programming, and Data Structures: Genetic Programming + Data Structures = Automatic Programming!. This book is motivated by the observation from software engineering that data abstraction (e.g., via abstract data types) is essential in programs created by human programmers. This book shows that abstract data types can be similarly beneficial to the automatic production of programs using GP. Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming! shows how abstract data types (stacks, queues and lists) can be evolved using genetic programming, demonstrates how GP can evolve general programs which solve the nested brackets problem, recognises a Dyck context free language, and implements a simple four function calculator. In these cases, an appropriate data structure is beneficial compared to simple indexed memory. This book also includes a survey of GP, with a critical review of experiments with evolving memory, and reports investigations of real world electrical network maintenance scheduling problems that demonstrate that Genetic Algorithms can find low cost viable solutions to such problems. Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming! should be of direct interest to computer scientists doing research on genetic programming, genetic algorithms, data structures, and artificial intelligence. In addition, this book will be of interest to practitioners working in all of these areas and to those interested in automatic programming.
Genetic Algorithms And Genetic Programming
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Author : Michael Affenzeller
language : en
Publisher: CRC Press
Release Date : 2009-04-09
Genetic Algorithms And Genetic Programming written by Michael Affenzeller and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-09 with Computers categories.
Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications discusses algorithmic developments in the context of genetic algorithms (GAs) and genetic programming (GP). It applies the algorithms to significant combinatorial optimization problems and describes structure identification using HeuristicLab as a platform for al
Genetic Programming And Data Structures
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Author : William B. Langdon
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Genetic Programming And Data Structures written by William B. Langdon 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.
Computers that `program themselves' has long been an aim of computer scientists. Recently genetic programming (GP) has started to show its promise by automatically evolving programs. Indeed in a small number of problems GP has evolved programs whose performance is similar to or even slightly better than that of programs written by people. The main thrust of GP has been to automatically create functions. While these can be of great use they contain no memory and relatively little work has addressed automatic creation of program code including stored data. This issue is the main focus of Genetic Programming, and Data Structures: Genetic Programming + Data Structures = Automatic Programming!. This book is motivated by the observation from software engineering that data abstraction (e.g., via abstract data types) is essential in programs created by human programmers. This book shows that abstract data types can be similarly beneficial to the automatic production of programs using GP. Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming! shows how abstract data types (stacks, queues and lists) can be evolved using genetic programming, demonstrates how GP can evolve general programs which solve the nested brackets problem, recognises a Dyck context free language, and implements a simple four function calculator. In these cases, an appropriate data structure is beneficial compared to simple indexed memory. This book also includes a survey of GP, with a critical review of experiments with evolving memory, and reports investigations of real world electrical network maintenance scheduling problems that demonstrate that Genetic Algorithms can find low cost viable solutions to such problems. Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming! should be of direct interest to computer scientists doing research on genetic programming, genetic algorithms, data structures, and artificial intelligence. In addition, this book will be of interest to practitioners working in all of these areas and to those interested in automatic programming.
Advances In Genetic Programming
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Author : Kenneth E. Kinnear (Jr.)
language : en
Publisher: MIT Press
Release Date : 1994
Advances In Genetic Programming written by Kenneth E. Kinnear (Jr.) and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Computers categories.
Advances in Genetic Programming reports significant results in improving the power of genetic programming, presenting techniques that can be employed immediately in the solution of complex problems in many areas, including machine learning and the simulation of autonomous behavior. Popular languages such as C and C++ are used in manu of the applications and experiments, illustrating how genetic programming is not restricted to symbolic computing languages such as LISP. Researchers interested in getting started in genetic programming will find information on how to begin, on what public-domain code is available, and on how to become part of the active genetic programming community via electronic mail.
Handbook Of Genetic Programming Applications
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Author : Amir H. Gandomi
language : en
Publisher: Springer
Release Date : 2015-11-06
Handbook Of Genetic Programming Applications written by Amir H. Gandomi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-06 with Computers categories.
This contributed volume, written by leading international researchers, reviews the latest developments of genetic programming (GP) and its key applications in solving current real world problems, such as energy conversion and management, financial analysis, engineering modeling and design, and software engineering, to name a few. Inspired by natural evolution, the use of GP has expanded significantly in the last decade in almost every area of science and engineering. Exploring applications in a variety of fields, the information in this volume can help optimize computer programs throughout the sciences. Taking a hands-on approach, this book provides an invaluable reference to practitioners, providing the necessary details required for a successful application of GP and its branches to challenging problems ranging from drought prediction to trading volatility. It also demonstrates the evolution of GP through major developments in GP studies and applications. It is suitable for advanced students who wish to use relevant book chapters as a basis to pursue further research in these areas, as well as experienced practitioners looking to apply GP to new areas. The book also offers valuable supplementary material for design courses and computation in engineering.
Advances And Trends In Genetic Programming
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Author : Arpit Bhardwaj
language : en
Publisher: Academic Press
Release Date : 2021-03-15
Advances And Trends In Genetic Programming written by Arpit Bhardwaj and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-15 with Science categories.
Advances and Trends in Genetic Programming, Volume One: Classification Techniques and Life Cycles presents the reader with complete coverage of the most current developments in Genetic Programming for Artificial Intelligence. The book provides a thorough look at classification as a systematic way of predicting class membership for a set of examples or instances using the properties of those examples. Classification arises in a wide variety of real life situations, such as detecting faces from large database, finding vehicles, matching fingerprints and diagnosing medical conditions. A classification algorithm requires huge amount of accuracy and reliability that is very difficult for human programmers. Therefore, there is a need to develop an automated computer-based classification system that can classify the required objects. Presents the latest advances in Genetic Programming for Artificial Intelligence Discusses automated computer-based classification algorithms and systems, including comparison of different types of machine learning and two-class versus multi-class classification Includes discussions of tree-based Genetic Programming, the Intron problem, Dynamic Fitness Evaluation, Crossover and Mutation Operators, and a presentation of an integrated model-based Genetic Programming Algorithm for multi-class classification
