Название: Practical Swarm Intelligence in Python: Using Swarm Intelligence and Evolutionary Algorithms to Solve Problems in Engineering and ScienceАвтор: Ronald T. Kneusel, Ph.D.
Издательство: Independently published
Год: 2021
Страниц: 250
Язык: английский
Формат: pdf (true)
Размер: 17.1 MB
Swarm intelligence and evolutionary algorithms are powerful approaches to solving optimization problems, or anything that can be cast as an optimization problem. This includes everything from designing neural network architectures (AutoML) to arranging products in a grocery store to maximize profit. This book introduces the reader to these techniques via a Python toolkit and many experiments.
This book is the result of my experience with swarm algorithms and continues my fascination with the power of randomness and how it can generate order from disorder – witness biological evolution. We’ll define what we mean by swarm algorithm or swarm optimization more rigorously in Chapter 1.1. But, for now, think of a swarm optimization as a way to find the best set of parameters to solve a problem. Finding the parameters is the optimization part. The swarm is how the optimization happens – think of a flock of birds wandering through a space where each point in the space represents a possible solution to the problem.
This book is meant as a practical introduction to using swarms to solve optimization problems. I added emphasis on the word practical because the goal is to introduce you to the thought process behind using swarms. At the same time, we’ll present a representative set of swarm algorithms, explain how they work, and provide implementations in Python along with all the other parts necessary to quickly build solutions to problems.
This book is not, however, a scholarly treatment of the subject. We won’t be proving theorems or diving into deep mathematical formulations. Instead, we’ll learn by doing, by experimentation, and by empirical observation of how our algorithms perform. It’s my sincere hope that by the time you put this book down, you’ve learned how to apply swarm optimization algorithms to your own problems using the Python framework as a guide.
Who Is This Book For?
This book is for people who need to solve problems expressable as locating the best set of parameters. These are often problems in engineering, like where to place a set of cell towers with specific characteristics. Or, they are problems in commerce: how should I arrange the products in my grocery store to maximize my profit? As we’ll see in Part II, we can use swarms for creative efforts, like generating melodies from scratch. I have even heard of brewers using optimization techniques to improve the quality of their beer; something of which I wholeheartedly approve.
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