@book{poli08:fieldguide,
	title = {A field guide to genetic programming},
	author = {Riccardo Poli and William B. Langdon and Nicholas Freitag McPhee},
	note = {(With contributions by J. R. Koza)},
	publisher = {Published via \texttt{http://lulu.com} and freely
                 available at
                 \texttt{http://www.gp-field-guide.org.uk}},
	url = {http://www.gp-field-guide.org.uk},
	year = {2008},
	biburl = {http://www.bibsonomy.org/bibtex/2f48362d42a42bda317f0bbc62617bec4/brazovayeye},
	abstract = {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.

                 Table of Contents

                 1 Introduction

                 1.1 Genetic Programming in a Nutshell

                 1.2 Getting Started

                 1.3 Prerequisites

                 1.4 Overview of this Field Guide

                 Part I Basics

                 2 Representation, Initialisation and Operators in
                 Tree-based GP

                 2.1 Representation

                 2.2 Initialising the Population

                 2.3 Selection

                 2.4 Recombination and Mutation},
	isbn13 = {978-1-4092-0073-4}, notes = {http://www.gp-field-guide.org.uk/}, size = {250 pages},
	keywords = {algorithms, artificial automatic computation evolutionary genetic intelligence, learning, machine programming, }
}