Genetic Programming
Ebook Download | Genetic Programming | This is a great "how to" book loaded with examples of how to implement genetic algorithms. The two main points this book makes is that many seemingly different problems can be reformulated as problems of program induction and that the genetic programming paradigm described in this book provides a way to do that program induction. No prior knowledge of conventional genetic algorithms is assumed. Thus the first three chapters are introductory material. In particular, chapter three describes the conventional genetic algorithm and introduces certain terms common to the conventional genetic algorithm and genetic programming. If you are already familiar with genetic algorithms you can skip ahead.
Chapter 4 discusses the representation problem for the conventional genetic algorithm operating on fixed-length character strings and variations of the conventional genetic algorithm dealing with structures more complex and flexible than fixed-length character strings. Since this book assumes no prior knowledge of the LISP programming language, section 4.2 describes LISP and section 4.3 outlines the reasons behind the choice of LISP for the implementation of solutions in this book. Chapter 5 provides an informal overview of the genetic programming paradigm and chapter 6 provides a detailed description of the techniques of genetic programming. Some readers may prefer to rely on chapter 5 and hold off on reading the detailed discussion in chapter 6 until they have read chapter 7 and the later chapters that contain examples.
Chapter 7 provides a detailed description of how to apply genetic programming to four introductory examples thus laying the groundwork for all of the problems to be described later in the book. Chapter 8 discusses the amount of computer processing required by the genetic programming paradigm to solve certain problems. Chapter 9 shows that the results obtained from genetic programming are not the fruits of a random search. Chapters 10 through 21 illustrate how to use genetic programming to solve a wide variety of problems from varying disciplines and are defined by the table of contents. The examples in these 12 chapters make up the heart of the book.
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Chapter 4 discusses the representation problem for the conventional genetic algorithm operating on fixed-length character strings and variations of the conventional genetic algorithm dealing with structures more complex and flexible than fixed-length character strings. Since this book assumes no prior knowledge of the LISP programming language, section 4.2 describes LISP and section 4.3 outlines the reasons behind the choice of LISP for the implementation of solutions in this book. Chapter 5 provides an informal overview of the genetic programming paradigm and chapter 6 provides a detailed description of the techniques of genetic programming. Some readers may prefer to rely on chapter 5 and hold off on reading the detailed discussion in chapter 6 until they have read chapter 7 and the later chapters that contain examples.
Chapter 7 provides a detailed description of how to apply genetic programming to four introductory examples thus laying the groundwork for all of the problems to be described later in the book. Chapter 8 discusses the amount of computer processing required by the genetic programming paradigm to solve certain problems. Chapter 9 shows that the results obtained from genetic programming are not the fruits of a random search. Chapters 10 through 21 illustrate how to use genetic programming to solve a wide variety of problems from varying disciplines and are defined by the table of contents. The examples in these 12 chapters make up the heart of the book.
Download Ebook Genetic Programming
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