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Author: Markus F. Brameier Publisher: Springer Science & Business Media ISBN: 0387310304 Category : Computers Languages : en Pages : 323
Book Description
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.
Author: Markus F. Brameier Publisher: Springer Science & Business Media ISBN: 0387310304 Category : Computers Languages : en Pages : 323
Book Description
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.
Author: Markus F. Brameier Publisher: Springer ISBN: 9781441940483 Category : Computers Languages : en Pages : 0
Book Description
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.
Author: Publisher: Lulu.com ISBN: 1409200736 Category : Computers Languages : en Pages : 252
Book Description
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.
Author: Amir H. Gandomi Publisher: Springer ISBN: 3319208837 Category : Computers Languages : en Pages : 589
Book Description
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.
Author: Julian F. Miller Publisher: Springer Science & Business Media ISBN: 3642173101 Category : Computers Languages : en Pages : 358
Book Description
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.
Author: Rick Riolo Publisher: Springer ISBN: 3319970887 Category : Computers Languages : en Pages : 233
Book Description
These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Chapters in this volume include: Similarity-based Analysis of Population Dynamics in GP Performing Symbolic Regression Hybrid Structural and Behavioral Diversity Methods in GP Multi-Population Competitive Coevolution for Anticipation of Tax Evasion Evolving Artificial General Intelligence for Video Game Controllers A Detailed Analysis of a PushGP Run Linear Genomes for Structured Programs Neutrality, Robustness, and Evolvability in GP Local Search in GP PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification Relational Structure in Program Synthesis Problems with Analogical Reasoning An Evolutionary Algorithm for Big Data Multi-Class Classification Problems A Generic Framework for Building Dispersion Operators in the Semantic Space Assisting Asset Model Development with Evolutionary Augmentation Building Blocks of Machine Learning Pipelines for Initialization of a Data Science Automation Tool Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
Author: Kenneth E. Kinnear (Jr.) Publisher: MIT Press ISBN: 9780262111881 Category : Computers Languages : en Pages : 544
Book Description
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.
Author: Shu-Heng Chen Publisher: Springer Science & Business Media ISBN: 1461508355 Category : Business & Economics Languages : en Pages : 491
Book Description
After a decade of development, genetic algorithms and genetic programming have become a widely accepted toolkit for computational finance. Genetic Algorithms and Genetic Programming in Computational Finance is a pioneering volume devoted entirely to a systematic and comprehensive review of this subject. Chapters cover various areas of computational finance, including financial forecasting, trading strategies development, cash flow management, option pricing, portfolio management, volatility modeling, arbitraging, and agent-based simulations of artificial stock markets. Two tutorial chapters are also included to help readers quickly grasp the essence of these tools. Finally, a menu-driven software program, Simple GP, accompanies the volume, which will enable readers without a strong programming background to gain hands-on experience in dealing with much of the technical material introduced in this work.
Author: Sebastian Ventura Soto Publisher: BoD – Books on Demand ISBN: 9535108093 Category : Computers Languages : en Pages : 302
Book Description
Genetic programming (GP) is a branch of Evolutionary Computing that aims the automatic discovery of programs to solve a given problem. Since its appearance, in the earliest nineties, GP has become one of the most promising paradigms for solving problems in the artificial intelligence field, producing a number of human-competitive results and even patentable new inventions. And, as other areas in Computer Science, GP continues evolving quickly, with new ideas, techniques and applications being constantly proposed. The purpose of this book is to show recent advances in the field of GP, both the development of new theoretical approaches and the emergence of applications that have successfully solved different real world problems. The volume is primarily aimed at postgraduates, researchers and academics, although it is hoped that it may be useful to undergraduates who wish to learn about the leading techniques in GP.
Author: Markus F. Brameier
Author: Markus F. Brameier
Author: Markus F. Brameier
Author: Markus Brameier
Author: 
Author: Amir H. Gandomi
Author: Julian F. Miller
Author: Rick Riolo
Author: Kenneth E. Kinnear (Jr.)
Author: Shu-Heng Chen
Author: Sebastian Ventura Soto