Genetic algorithms and machine learning for programmers: create AI models and evolve solutions PDF
Preview Genetic algorithms and machine learning for programmers: create AI models and evolve solutions
Early Praise for Genetic Algorithms and Machine Learning for Programmers I really like the book; it’s pitched nicely at the interested beginner and doesn’t make undue assumptions about background knowledge. ➤ Burkhard Kloss Director, Applied Numerical Research Labs A unique take on the subject and should very much appeal to programmers looking to get started with various machine learning techniques. ➤ Christopher L. Simons Senior Lecturer, University of the West of England, Bristol, UK Turtles, paper bags, escape, AI, fun whilst learning: it’s turtles all the way out. ➤ Russel Winder Retired Consultant, Self-Employed This book lifts the veil on the complexity and magic of machine learning techniques for ordinary programmers. Simple examples and interactive programs really show you not just how these algorithms work, but bring real-world problems to life. ➤ Steve Love Programmer, Freelance We've left this page blank to make the page numbers the same in the electronic and paper books. We tried just leaving it out, but then people wrote us to ask about the missing pages. Anyway, Eddy the Gerbil wanted to say “hello.” Genetic Algorithms and Machine Learning for Programmers Create AI Models and Evolve Solutions Frances Buontempo The Pragmatic Bookshelf Raleigh, North Carolina Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and The Pragmatic Programmers, LLC was aware of a trademark claim, the designations have been printed in initial capital letters or in all capitals. The Pragmatic Starter Kit, The Pragmatic Programmer, Pragmatic Programming, Pragmatic Bookshelf, PragProg and the linking g device are trade- marks of The Pragmatic Programmers, LLC. Every precaution was taken in the preparation of this book. However, the publisher assumes no responsibility for errors or omissions, or for damages that may result from the use of information (including program listings) contained herein. Our Pragmatic books, screencasts, and audio books can help you and your team create better software and have more fun. Visit us at https://pragprog.com. The team that produced this book includes: Publisher: Andy Hunt VP of Operations: Janet Furlow Managing Editor: Susan Conant Development Editor: Tammy Coron Copy Editor: Jasmine Kwityn Indexing: Potomac Indexing, LLC Layout: Gilson Graphics For sales, volume licensing, and support, please contact [email protected]. For international rights, please contact [email protected]. Copyright © 2019 The Pragmatic Programmers, LLC. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form, or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior consent of the publisher. ISBN-13: 978-1-68050-620-4 Book version: P1.0—January 2019 Contents Preface . . . . . . . . . . . . . . ix 1. Escape! Code Your Way Out of a Paper Bag . . . . . 1 Let’s Begin 3 Your Mission: Find a Way Out 4 How to Help the Turtle Escape 6 Let’s Save the Turtle 7 Did It Work? 11 Over to You 13 2. Decide! Find the Paper Bag . . . . . . . . . 15 Your Mission: Learn from Data 16 How to Grow a Decision Tree 18 Let’s Find That Paper Bag 23 Did It Work? 27 Over to You 31 3. Boom! Create a Genetic Algorithm . . . . . . . 33 Your Mission: Fire Cannonballs 35 How to Breed Solutions 37 Let’s Fire Some Cannons 40 Did It Work? 48 Over to You 53 4. Swarm! Build a Nature-Inspired Swarm . . . . . . 57 Your Mission: Crowd Control 58 How to Form a Swarm 66 Let’s Make a Swarm 69 Did It Work? 76 Over to You 78 Contents • vi 5. Colonize! Discover Pathways . . . . . . . . 79 Your Mission: Lay Pheromones 80 How to Create Pathways 83 Let’s March Some Ants 85 Did It Work? 93 Over to You 97 6. Diffuse! Employ a Stochastic Model . . . . . . . 99 Your Mission: Make Small Random Steps 100 How to Cause Diffusion 109 Let’s Diffuse Some Particles 111 Did It Work? 119 Over to You 125 7. Buzz! Converge on One Solution . . . . . . . 127 Your Mission: Beekeeping 128 How to Feed the Bees 131 Let’s Make Some Bees Swarm 133 Did It Work? 143 Over to You 145 8. Alive! Create Artificial Life . . . . . . . . . 147 Your Mission: Make Cells Come Alive 149 How to Create Artificial Life 152 Let’s Make Cellular Automata 154 Did It Work? 160 Over to You 161 9. Dream! Explore CA with GA . . . . . . . . 163 Your Mission: Find the Best 164 How to Explore a CA 167 Let’s Find the Best Starting Row 169 Did It Work? 181 Over to You 185 10. Optimize! Find the Best . . . . . . . . . 187 Your Mission: Move Turtles 188 How to Get a Turtle into a Paper Bag 189 Let’s Find the Bottom of the Bag 193 Did It Work? 198 Extension to More Dimensions 203 Over to You 205 Contents • vii Bibliography . . . . . . . . . . . . 207 Index . . . . . . . . . . . . . . 209 Preface Have you ever heard the phrase “Coding your way out of a paper bag”? In this book, you’ll do exactly that. In each chapter, you’ll examine different machine learning techniques that you can use to programmatically get parti- cles, ants, bees, and even turtles out of a paper bag. While the metaphor itself may be silly, it’s a great way to demonstrate how algorithms find solutions over time. Who Is This Book For? If you’re a beginner to intermediate programmer keen to understand machine learning, this book is for you. Inside its pages, you’ll create genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. You’ll also learn how to test your code as you dive into even more advanced topics. Experts in machine learning may still enjoy the “programming out of a paper bag” metaphor, though they are unlikely to learn new things. What’s in This Book? In this book, you will: • Use heuristics and design fitness functions • Build genetic algorithms • Make nature-inspired swarms with ants, bees, and particles • Create Monte Carlo simulations • Investigate cellular automata • Find minima and maxima using hill climbing and simulated annealing • Try selection methods, including tournament and roulette wheels • Learn about heuristics, fitness functions, metrics, and clusters You’ll also test your code, get inspired to solve new problems, and work through scenarios to code your way out of a paper bag—an important skill for any competent programmer. Beyond that, you’ll see how the algorithms report erratum • discuss
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