A Field Guide to Genetic Programming

Author:

Publisher: Lulu.com

ISBN:

Category: Computers

Page: 233

View: 507

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

14th European Conference, EuroGP 2011, Torino, Italy, April 27-29, 2011, Proceedings

Author: Sara Silva

Publisher: Springer Science & Business Media

ISBN:

Category: Computers

Page: 348

View: 664

This book constitutes the refereed proceedings of the 14th European Conference on Genetic Programming, EuroGP 2011, held in Torino, Italy, in April 2011 co-located with the Evo* 2011 events. This 20 revised full papers presented together with 9 poster papers were carefully reviewed and selected from 59 submissions. The wide range of topics in this volume reflect the current state of research in the field, including representations, theory, novel operators and techniques, self organization, and applications.

Genetic Algorithms and Genetic Programming

Modern Concepts and Practical Applications

Author: Michael Affenzeller

Publisher: CRC Press

ISBN:

Category: Computers

Page: 379

View: 937

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 algorithm development. The book focuses on both theoretical and empirical aspects. The theoretical sections explore the important and characteristic properties of the basic GA as well as main characteristics of the selected algorithmic extensions developed by the authors. In the empirical parts of the text, the authors apply GAs to two combinatorial optimization problems: the traveling salesman and capacitated vehicle routing problems. To highlight the properties of the algorithmic measures in the field of GP, they analyze GP-based nonlinear structure identification applied to time series and classification problems. Written by core members of the HeuristicLab team, this book provides a better understanding of the basic workflow of GAs and GP, encouraging readers to establish new bionic, problem-independent theoretical concepts. By comparing the results of standard GA and GP implementation with several algorithmic extensions, it also shows how to substantially increase achievable solution quality.

Genetic Programming and Data Structures

Genetic Programming + Data Structures = Automatic Programming!

Author: William B. Langdon

Publisher: Springer Science & Business Media

ISBN:

Category: Computers

Page: 279

View: 253

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

On the Programming of Computers by Means of Natural Selection

Author: John R. Koza

Publisher: MIT Press

ISBN:

Category: Computers

Page: 819

View: 899

In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic programming may be more powerful than neural networks and other machine learning techniques, able to solve problems in a wider range of disciplines. In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic Programming contains a great many worked examples and includes a sample computer code that will allow readers to run their own programs.In getting computers to solve problems without being explicitly programmed, Koza stresses two points: that seemingly different problems from a variety of fields can be reformulated as problems of program induction, and that the recently developed genetic programming paradigm provides a way to search the space of possible computer programs for a highly fit individual computer program to solve the problems of program induction. Good programs are found by evolving them in a computer against a fitness measure instead of by sitting down and writing them.

Genetic Programming

12th European Conference, EuroGP 2009 Tübingen, Germany, April, 15-17, 2009 Proceedings

Author: Leonardo Vanneschi

Publisher: Springer Science & Business Media

ISBN:

Category: Computers

Page: 363

View: 489

The 12th European Conference on Genetic Programming, EuroGP 2009, took place in Tu ¨bingen, Germany during April 15–17 at one of the oldest univer- ties in Germany, the Eberhard Karls Universitat ¨ Tubing ¨ en. This volume c- tains manuscripts of the 21 oral presentations held during the day, and the nine posters that were presented during a dedicated evening session and reception. The topics covered in this volume re?ectthecurrentstateoftheartofgenetic programming, including representations, theory, operators and analysis, feature selection, generalization, coevolution, and numerous applications. A rigorous, double-blind peer-review process was used, with each submission reviewed by at least three members of the international ProgramCommittee. In total, 57 papers were submitted with an acceptance rate of 36% for full papers and an overall acceptance rate of 52% including posters. The MyReview m- agement software originally developed by Philippe Rigaux, Bertrand Chardon, and other colleagues from the Universit´ e Paris-Sud Orsay, France was used for the reviewing process. We are sincerely grateful to Marc Schoenauer from IN- RIA, France for his continued assistance in hosting and managing the software. Paper review assigments were largely done by an optimization process matching paper keywords to keywords of expertise submitted by reviewers.

Genetic Programming

13th European Conference, EuroGP 2010, Istanbul, Turkey, April 7-9, 2010, Proceedings

Author: Anna Isabel Esparcia-Alcazar

Publisher: Springer Science & Business Media

ISBN:

Category: Computers

Page: 336

View: 741

rangefromsolvingdi?erentialequations,routingproblems to ?le type detection, object-oriented testing, agents. This year we received 48 submissions, of which 47 were sent to the reviewers.

Genetic Programming

7th European Conference, EuroGP 2004, Coimbra, Portugal, April 5-7, 2004, Proceedings

Author: Maarten Keijzer

Publisher: Springer Science & Business Media

ISBN:

Category: Computers

Page: 410

View: 781

This book constitutes the refereed proceedings of the 7th European Conference on Genetic Programming, EuroGP 2004, held in Coimbra, Portugal, in April 2004. The 38 revised papers presented were carefully reviewed and selected from 61 submissions. The papers deal with a variety of foundational and methodological issues as well as with advanced applications in areas like engineering, computer science, language understanding, bioinformatics, and design.

Genetic Programming Theory and Practice VI

Author: Rick Riolo

Publisher: Springer Science & Business Media

ISBN:

Category: Computers

Page: 274

View: 496

Genetic Programming Theory and Practice VI was developed from the sixth workshop at the University of Michigan’s Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming (GP). Contributions from the foremost international researchers and practitioners in the GP arena examine the similarities and differences between theoretical and empirical results on real-world problems. The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application. These contributions address several significant interdependent themes which emerged from this year’s workshop, including: (1) Making efficient and effective use of test data. (2) Sustaining the long-term evolvability of our GP systems. (3) Exploiting discovered subsolutions for reuse. (4) Increasing the role of a Domain Expert.

Advances in Genetic Programming

Author: Kenneth E. Kinnear

Publisher: MIT Press

ISBN:

Category: Computers

Page: 476

View: 971

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.

Cartesian Genetic Programming

Author: Julian F. Miller

Publisher: Springer Science & Business Media

ISBN:

Category: Computers

Page: 346

View: 203

Cartesian Genetic Programming (CGP) is a highly effective and increasingly popular form of genetic programming. It represents programs in the form of directed graphs, and a particular characteristic is that it has a highly redundant genotype–phenotype mapping, in that genes can be noncoding. It has spawned a number of new forms, each improving on the efficiency, among them modular, or embedded, CGP, and self-modifying CGP. It has been applied to many problems in both computer science and applied sciences. This book contains chapters written by the leading figures in the development and application of CGP, and it will be essential reading for researchers in genetic programming and for engineers and scientists solving applications using these techniques. It will also be useful for advanced undergraduates and postgraduates seeking to understand and utilize a highly efficient form of genetic programming.

Linear Genetic Programming

Author: Markus F. Brameier

Publisher: Springer Science & Business Media

ISBN:

Category: Computers

Page: 316

View: 407

Linear Genetic Programming presents a variant of Genetic Programming that evolves imperative computer programs as linear sequences of instructions, in contrast to the more traditional functional expressions or syntax trees. Typical GP phenomena, such as non-effective code, neutral variations, and code growth are investigated from the perspective of linear GP. This book serves as a reference for researchers; it includes sufficient introductory material for students and newcomers to the field.

Genetic Programming

11th European Conference, EuroGP 2008, Naples, Italy, March 26-28, 2008, Proceedings

Author: Michael O'Neill

Publisher: Springer Science & Business Media

ISBN:

Category: Computers

Page: 373

View: 846

This book constitutes the refereed proceedings of the 11th European Conference on Genetic Programming, EuroGP 2008, held in Naples, Italy, in March 2008 colocated with EvoCOP 2008. The 21 revised plenary papers and 10 revised poster papers were carefully reviewed and selected from a total of 61 submissions. A great variety of topics are presented reflecting the current state of research in the field of genetic programming, including the latest work on representations, theory, operators and analysis, evolvable hardware, agents and numerous applications.

Genetic Programming

10th European Conference, EuroGP 2007, Valencia, Spain, April 11-13, 2007, Proceedings

Author: Marc Ebner

Publisher: Springer Science & Business Media

ISBN:

Category: Computers

Page: 380

View: 761

This book constitutes the refereed proceedings of the 10th European Conference on Genetic Programming, EuroGP 2007, held in Valencia, Spain in April 2007 colocated with EvoCOP 2007. The 21 revised plenary papers and 14 revised poster papers were carefully reviewed and selected from 71 submissions. The papers address fundamental and theoretical issues, along with a wide variety of papers dealing with different application areas.

Genetic Programming Theory and Practice

Author: Rick Riolo

Publisher: Springer Science & Business Media

ISBN:

Category: Computers

Page: 317

View: 299

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.

Foundations of Genetic Programming

Author: William B. Langdon

Publisher: Springer Science & Business Media

ISBN:

Category: Computers

Page: 260

View: 174

Genetic programming (GP), one of the most advanced forms of evolutionary computation, has been highly successful as a technique for getting computers to automatically solve problems without having to tell them explicitly how. Since its inceptions more than ten years ago, GP has been used to solve practical problems in a variety of application fields. Along with this ad-hoc engineering approaches interest increased in how and why GP works. This book 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 Programming

19th European Conference, EuroGP 2016, Porto, Portugal, March 30 - April 1, 2016, Proceedings

Author: Malcolm I. Heywood

Publisher: Springer

ISBN:

Category: Computers

Page: 311

View: 755

This book constitutes the refereed proceedings of the 19th European Conference on Genetic Programming, EuroGP 2016, held in Porto, Portugal, in March/April 2016 co-located with the Evo*2016 events: EvoCOP, EvoMUSART, and EvoApplications. The 11 revised full papers presented together with 8 poster papers were carefully reviewed and selected from 36 submissions. The wide range of topics in this volume reflects the current state of research in the field. Thus, we see topics as diverse as semantic methods, recursive programs, grammatical methods, coevolution, Cartesian GP, feature selection, metaheuristics, evolvability, and fitness predictors; and applications including image processing, one-class classification, SQL injection attacks, numerical modelling, streaming data classification, creation and optimisation of circuits, multi-class classification, scheduling in manufacturing and wireless networks.

Genetic Algorithms

Concepts and Designs

Author: Kim-Fung Man

Publisher: Springer Science & Business Media

ISBN:

Category: Mathematics

Page: 344

View: 742

This comprehensive book gives a overview of the latest discussions in the application of genetic algorithms to solve engineering problems. Featuring real-world applications and an accompanying disk, giving the reader the opportunity to use an interactive genetic algorithms demonstration program.