Genetic Programming And Data Structures


Genetic Programming And Data Structures
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Genetic Programming And Data Structures


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 Data Structures Evolution Programs


Genetic Algorithms Data Structures Evolution Programs
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Author : Zbigniew Michalewicz
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

Genetic Algorithms Data Structures Evolution Programs written by Zbigniew Michalewicz 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 2013-03-09 with Computers categories.


Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques is still growing, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science. The book is self-contained and the only prerequisite is basic undergraduate mathematics. This third edition has been substantially revised and extended by three new chapters and by additional appendices containing working material to cover recent developments and a change in the perception of evolutionary computation.



Genetic Programming And Data Structures


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.



Genetic Programming And Data Structures


Genetic Programming And Data Structures
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Author : W.B. Langdon
language : en
Publisher: Springer
Release Date : 2012-10-29

Genetic Programming And Data Structures written by W.B. Langdon and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-29 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.



Foundations Of Genetic Programming


Foundations Of Genetic Programming
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Author : William B. Langdon
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

Foundations Of Genetic Programming 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 2013-03-09 with Computers categories.


This is one of the only books to provide a complete and coherent review of the theory of genetic programming (GP). In doing so, it provides a coherent consolidation of recent work on the theoretical foundations of GP. A concise introduction to GP and genetic algorithms (GA) is followed by a discussion of fitness landscapes and other theoretical approaches to natural and artificial evolution. Having surveyed early approaches to GP theory it presents new exact schema analysis, showing that it applies to GP as well as to the simpler GAs. New results on the potentially infinite number of possible programs are followed by two chapters applying these new techniques.



Genetic Algorithms Data Structures Evolution Programs


Genetic Algorithms Data Structures Evolution Programs
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Author : Zbigniew Michalewicz
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29

Genetic Algorithms Data Structures Evolution Programs written by Zbigniew Michalewicz 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 2013-06-29 with Mathematics categories.


'What does your Master teach?' asked a visitor. 'Nothing,' said the disciple. 'Then why does he give discourses?' 'He only points the way - he teaches nothing.' Anthony de Mello, One Minute Wisdom During the last three decades there has been a growing interest in algorithms which rely on analogies to natural processes. The emergence of massively par allel computers made these algorithms of practical interest. The best known algorithms in this class include evolutionary programming, genetic algorithms, evolution strategies, simulated annealing, classifier systems, and neural net works. Recently (1-3 October 1990) the University of Dortmund, Germany, hosted the First Workshop on Parallel Problem Solving from Nature [164]. This book discusses a subclass of these algorithms - those which are based on the principle of evolution (survival of the fittest). In such algorithms a popu lation of individuals (potential solutions) undergoes a sequence of unary (muta tion type) and higher order (crossover type) transformations. These individuals strive for survival: a selection scheme, biased towards fitter individuals, selects the next generation. After some number of generations, the program converges - the best individual hopefully represents the optimum solution. There are many different algorithms in this category. To underline the sim ilarities between them we use the common term "evolution programs" .



Genetic Algorithms Data Structures


Genetic Algorithms Data Structures
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Author :
language : en
Publisher:
Release Date : 1992

Genetic Algorithms Data Structures written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with categories.




Genetic Algorithms Data Structures Evolution Programs 3e


Genetic Algorithms Data Structures Evolution Programs 3e
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Author : Michalewicz
language : en
Publisher:
Release Date : 2008-11-01

Genetic Algorithms Data Structures Evolution Programs 3e written by Michalewicz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-01 with categories.




Genetic Algorithms Data Structures


Genetic Algorithms Data Structures
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Author : Zbigniew Michalewicz
language : en
Publisher:
Release Date : 1996

Genetic Algorithms Data Structures written by Zbigniew Michalewicz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Data structures (Computer science) categories.




Genetic Programming Theory And Practice


Genetic Programming Theory And Practice
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Author : Rick Riolo
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-11-30

Genetic Programming Theory And Practice written by Rick Riolo 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 2003-11-30 with Computers categories.


Genetic Programming Theory and Practice explores the emerging interaction between theory and practice in the cutting-edge, machine learning method of Genetic Programming (GP). The material contained in this contributed volume was developed from a workshop at the University of Michigan's Center for the Study of Complex Systems where an international group of genetic programming theorists and practitioners met to examine how GP theory informs practice and how GP practice impacts GP theory. The contributions cover the full spectrum of this relationship and are written by leading GP theorists from major universities, as well as active practitioners from leading industries and businesses. Chapters include such topics as John Koza's development of human-competitive electronic circuit designs; David Goldberg's application of "competent GA" methodology to GP; Jason Daida's discovery of a new set of factors underlying the dynamics of GP starting from applied research; and Stephen Freeland's essay on the lessons of biology for GP and the potential impact of GP on evolutionary theory. The book also includes chapters on the dynamics of GP, the selection of operators and population sizing, specific applications such as stock selection in emerging markets, predicting oil field production, modeling chemical production processes, and developing new diagnostics from genomic data. Genetic Programming Theory and Practice is an excellent reference for researchers working in evolutionary algorithms and for practitioners seeking innovative methods to solve difficult computing problems.