Clever Algorithms, Nature-Inspired Programming Recipies

Clever Algorithms, Nature-Inspired Programming Recipies -...

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Unformatted text preview: Jason Brownlee Clever Algorithms Nature-Inspired Programming Recipes ii Jason Brownlee, PhD Jason Brownlee studied Applied Science at Swinburne University in Melbourne, Australia, going on to complete a Masters in Information Technology focusing on Niching Genetic Algorithms, and a PhD in the field of Artificial Immune Systems. Jason has worked for a number of years as a Consultant and Software Engineer for a range of Corporate and Government organizations. When not writing books, Jason likes to compete in Machine Learning competitions. Cover Image Copyright 2011 Jason Brownlee. All Reserved. Clever Algorithms: Nature-Inspired Programming Recipes Copyright 2011 Jason Brownlee. Some Rights Reserved. First Edition. LuLu. January 2011 ISBN: 978-1-4467-8506-5 This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 2.5 Australia License. The full terms of the license are located online at http://creativecommons.org/licenses/by-nc-sa/2.5/au/legalcode Webpage Source code and additional resources can be downloaded from the books companion website online at http://www.CleverAlgorithms.com Contents Foreword vii Preface ix I Background 1 1 Introduction 3 1.1 What is AI . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Problem Domains . . . . . . . . . . . . . . . . . . . . . . . . 9 1.3 Unconventional Optimization . . . . . . . . . . . . . . . . . 13 1.4 Book Organization . . . . . . . . . . . . . . . . . . . . . . . 16 1.5 How to Read this Book . . . . . . . . . . . . . . . . . . . . 19 1.6 Further Reading . . . . . . . . . . . . . . . . . . . . . . . . 20 1.7 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . 21 II Algorithms 27 2 Stochastic Algorithms 29 2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.2 Random Search . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.3 Adaptive Random Search . . . . . . . . . . . . . . . . . . . 34 2.4 Stochastic Hill Climbing . . . . . . . . . . . . . . . . . . . . 39 2.5 Iterated Local Search . . . . . . . . . . . . . . . . . . . . . . 43 2.6 Guided Local Search . . . . . . . . . . . . . . . . . . . . . . 49 2.7 Variable Neighborhood Search . . . . . . . . . . . . . . . . . 55 2.8 Greedy Randomized Adaptive Search . . . . . . . . . . . . . 60 2.9 Scatter Search . . . . . . . . . . . . . . . . . . . . . . . . . 66 2.10 Tabu Search . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 2.11 Reactive Tabu Search . . . . . . . . . . . . . . . . . . . . . 79 iii iv Contents 3 Evolutionary Algorithms 87 3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 3.2 Genetic Algorithm . . . . . . . . . . . . . . . . . . . . . . . 92 3.3 Genetic Programming . . . . . . . . . . . . . . . . . . . . . 99 3.4 Evolution Strategies . . . . . . . . . . . . . . . . . . . . . . 108 3.5 Differential Evolution . . . . . . . . . . . . . . . . . . . . . 114 3.6 Evolutionary Programming . . . . . . . . . . . . . . . . . . 120 3.7 Grammatical Evolution...
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This note was uploaded on 02/12/2011 for the course CSCI 4051 taught by Professor Sips during the Spring '11 term at North Texas.

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Clever Algorithms, Nature-Inspired Programming Recipies -...

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