A field guide to genetic programming
By: Riccardo Poli, William B. Langdon and Nicholas F. McPhee, with contributions by John R. Koza
Contributors: Langdon, W. B. (William B.); McPhee, Nicholas F.; Koza, John R.
Publisher: [Lulu Press], lulu.com
Published: 2008
Place of publication: [S.I.]
Language: eng
Number of pages: 233
ISBN-13: 9781409200734
Subjects: Genetic programming (Computer science)
Notes: Includes bibliographical references (p. 167-223) and index.
Table of contents: title: Contents
pagenum: xi; label: 1
title: Introduction
pagenum: 1; label: 1.1
title: Genetic Programming in a Nutshell
pagenum: 2; label: 1.2
title: Getting Started
pagenum: 2; label: 1.3
title: Prerequisites
pagenum: 3; label: 1.4
title: Overview of This Field Guide
pagenum: 4; label: I
title: Basics
pagenum: 7; label: 2
title: Representation, Initialisation and Operators in Tree-based GP
pagenum: 9; label: 2.1
title: Representation
pagenum: 9; label: 2.2
title: Initialising the Population
pagenum: 11; label: 2.3
title: Selection
pagenum: 14; label: 2.4
title: Recombination and Mutation
pagenum: 15; label: 3
title: Getting Ready to Run Genetic Programming
pagenum: 19; label: 3.1
title: Step 1: Terminal Set
pagenum: 19; label: 3.2
title: Step 2: Function Set
pagenum: 20; label: 3.2.1
title: Closure
pagenum: 21; label: 3.2.2
title: Sufficiency
pagenum: 23; label: 3.2.3
title: Evolving Structures Other Than Programs
pagenum: 23; label: 3.3
title: Step 3: Fitness Function
pagenum: 24; label: 3.4
title: Step 4: GP Parameters
pagenum: 26; label: 3.5
title: Step 5: Termination and Solution Designation
pagenum: 27; label: 4
title: Example Genetic Programming Run
pagenum: 29; label: 4.1
title: Preparatory Steps
pagenum: 29; label: 4.2
title: Step-by-Step Sample Run
pagenum: 31; label: 4.2.1
title: Initialisation
pagenum: 31; label: 4.2.2
title: Fitness Evaluation
pagenum: 32; label: 4.2.3
title: Selection, Crossover and Mutation
pagenum: 32; label: 4.2.4
title: Termination and Solution Designation
pagenum: 35; label: II
title: Advanced Genetic Programming
pagenum: 37; label: 5
title: Alternative Initialisations and Operators in Tree-based GP
pagenum: 39; label: 5.1
title: Constructing the Initial Population
pagenum: 39; label: 5.1.1
title: Uniform Initialisation
pagenum: 40; label: 5.1.2
title: Initialisation May Affect Bloat
pagenum: 40; label: 5.1.3
title: Seeding
pagenum: 41; label: 5.2
title: GP Mutation
pagenum: 42; label: 5.2.1
title: Is Mutation Necessary?
pagenum: 42; label: 5.2.2
title: Mutation Cookbook
pagenum: 42; label: 5.3
title: GP Crossover
pagenum: 44; label: 5.4
title: Other Techniques
pagenum: 46; label: 6
title: Modular, Grammatical and Developmental Tree-based GP
pagenum: 47; label: 6.1
title: Evolving Modular and Hierarchical Structures
pagenum: 47; label: 6.1.1
title: Automatically Defined Functions
pagenum: 48; label: 6.1.2
title: Program Architecture and Architecture-Altering
pagenum: 50; label: 6.2
title: Constraining Structures
pagenum: 51; label: 6.2.1
title: Enforcing Particular Structures
pagenum: 52; label: 6.2.2
title: Strongly Typed GP
pagenum: 52; label: 6.2.3
title: Grammar-based Constraints
pagenum: 53; label: 6.2.4
title: Constraints and Bias
pagenum: 55; label: 6.3
title: Developmental Genetic Programming
pagenum: 57; label: 6.4
title: Strongly Typed Autoconstructive GP with PushGP
pagenum: 59; label: 7
title: Linear and Graph Genetic Programming
pagenum: 61; label: 7.1
title: Linear Genetic Programming
pagenum: 61; label: 7.1.1
title: Motivations
pagenum: 61; label: 7.1.2
title: Linear GP Representations
pagenum: 62; label: 7.1.3
title: Linear GP Operators
pagenum: 64; label: 7.2
title: Graph-Based Genetic Programming
pagenum: 65; label: 7.2.1
title: Parallel Distributed GP (PDGP)
pagenum: 65; label: 7.2.2
title: PADO
pagenum: 67; label: 7.2.3
title: Cartesian GP
pagenum: 67; label: 7.2.4
title: Evolving Parallel Programs Using Indirect Encodings
pagenum: 68; label: 8
title: Probabilistic Genetic Programming
pagenum: 69; label: 8.1
title: Estimation of Distribution Algorithms
pagenum: 69; label: 8.2
title: Pure EDA GP
pagenum: 71; label: 8.3
title: Mixing Grammars and Probabilities
pagenum: 74; label: 9
title: Multi-objective Genetic Programming
pagenum: 75; label: 9.1
title: Combining Multiple Objectives into a Scalar Fitness Function
pagenum: 75; label: 9.2
title: Keeping the Objectives Separate
pagenum: 76; label: 9.2.1
title: Multi-objective Bloat and Complexity Control
pagenum: 77; label: 9.2.2
title: Other Objectives
pagenum: 78; label: 9.2.3
title: Non-Pareto Criteria
pagenum: 80; label: 9.3
title: Multiple Objectives via Dynamic and Staged Fitness Functions
pagenum: 80; label: 9.4
title: Multi-objective Optimisation via Operator Bias
pagenum: 81; label: 10
title: Fast and Distributed Genetic Programming
pagenum: 83; label: 10.1
title: Reducing Fitness Evaluations/Increasing Their Effectiveness
pagenum: 83; label: 10.2
title: Reducing Cost of Fitness with Caches
pagenum: 86; label: 10.3
title: Parallel and Distributed GP Are Not Equivalent
pagenum: 88; label: 10.4
title: Running GP on Parallel Hardware
pagenum: 89; label: 10.4.1
title: Master-slave GP
pagenum: 89; label: 10.4.2
title: GP Running on GPUs
pagenum: 90; label: 10.4.3
title: GP on FPGAs
pagenum: 92; label: 10.4.4
title: Sub-machine-code GP
pagenum: 93; label: 10.5
title: Geographically Distributed GP
pagenum: 93; label: 11
title: GP Theory and Its Applications
pagenum: 97; label: 11.1
title: Mathematical Models
pagenum: 98; label: 11.2
title: Search Spaces
pagenum: 99; label: 11.3
title: Bloat
pagenum: 101; label: 11.3.1
title: Bloat in Theory
pagenum: 101; label: 11.3.2
title: Bloat Control in Practice
pagenum: 104; label: III
title: Practical Genetic Programming
pagenum: 109; label: 12
title: Applications
pagenum: 111; label: 12.1
title: Where GP Has Done Well
pagenum: 111; label: 12.2
title: Curve Fitting, Data Modelling and Symbolic Regression
pagenum: 113; label: 12.3
title: Human Competitive Results - the Humies
pagenum: 117; label: 12.4
title: Image and Signal Processing
pagenum: 121; label: 12.5
title: Financial Trading, Time Series, and Economic Modelling
pagenum: 123; label: 12.6
title: Industrial Process Control
pagenum: 124; label: 12.7
title: Medicine, Biology and Bioinformatics
pagenum: 125; label: 12.8
title: GP to Create Searchers and Solvers - Hyper-heuristics
pagenum: 126; label: 12.9
title: Entertainment and Computer Games
pagenum: 127; label: 12.10
title: The Arts
pagenum: 127; label: 12.11
title: Compression
pagenum: 128; label: 13
title: Troubleshooting GP
pagenum: 131; label: 13.1
title: Is There a Bug in the Code?
pagenum: 131; label: 13.2
title: Can You Trust Your Results?
pagenum: 132; label: 13.3
title: There Are No Silver Bullets
pagenum: 132; label: 13.4
title: Small Changes Can Have Big Effects
pagenum: 133; label: 13.5
title: Big Changes Can Have No Effect
pagenum: 133; label: 13.6
title: Study Your Populations
pagenum: 134; label: 13.7
title: Encourage Diversity
pagenum: 136; label: 13.8
title: Embrace Approximation
pagenum: 137; label: 13.9
title: Control Bloat
pagenum: 139; label: 13.10
title: Checkpoint Results
pagenum: 139; label: 13.11
title: Report Well
pagenum: 139; label: 13.12
title: Convince Your Customers
pagenum: 140; label: 14
title: Conclusions
pagenum: 141; label: IV
title: Tricks of the Trade
pagenum: 143; label: A
title: Resources
pagenum: 145; label: A.1
title: Key Books
pagenum: 146; label: A.2
title: Key Journals
pagenum: 147; label: A.3
title: Key International Meetings
pagenum: 147; label: A.4
title: GP Implementations
pagenum: 147; label: A.5
title: On-Line Resources
pagenum: 148; label: B
title: TinyGP
pagenum: 151; label: B.1
title: Overview of TinyGP
pagenum: 151; label: B.2
title: Input Data Files for TinyGP
pagenum: 153; label: B.3
title: Source Code
pagenum: 154; label: B.4
title: Compiling and Running TinyGP
pagenum: 162; title: Bibliography
pagenum: 167; title: Index
pagenum: 225