Clever Algorithms: Nature-Inspired Programming Recipes

By Jason Brownlee PhD. First Edition, Lulu Enterprises, January 2011. ISBN: 978-1-4467-8506-5.

Implementing an Artificial Intelligence algorithm is difficult. Algorithm descriptions may be incomplete, inconsistent, and distributed across a number of papers, chapters and even websites. This can result in varied interpretations of algorithms, undue attrition of algorithms, and ultimately bad science.

This book is an effort to address these issues by providing a handbook of algorithmic recipes drawn from the fields of Metaheuristics, Biologically Inspired Computation and Computational Intelligence, described in a complete, consistent, and centralized manner. These standardized descriptions were carefully designed to be accessible, usable, and understandable. Most of the algorithms described were originally inspired by biological and natural systems, such as the adaptive capabilities of genetic evolution and the acquired immune system, and the foraging behaviors of birds, bees, ants and bacteria. An encyclopedic algorithm reference, this book is intended for research scientists, engineers, students, and interested amateurs. Each algorithm description provides a working code example in the Ruby Programming Language.

Metaheuristics are hard!

• Feel overwhelmed by the large number of Metaheuristics algorithms?
• Don't know where to start in optimizing a difficult scientific or engineering problem?
• Need some code to get started with a Genetic Algorithm or Neural Network algorithm?

The BENEFITS of this book are...

• Massive 45 algorithms described from across the field of Metahuristics in one book so you don't have to go rifling through your book case.
• Rules-of-thumb on when to apply and how to configure each algorithm, so you don't have to figure it out yourself.
• Code for each algorithm in the Ruby programming language to save you the time of having to write it yourself.
• Extensive references for each algorithm, summarizing both the primary sources for when you need detail on where an algorithm came from, and modern reviews for digging deeper into the state-of-the-art.
• Advanced topics on programming paradigms, devising new algorithms, algorithm testing, visualization and benchmarking to take your new found knowledge of Metaheuristic algorithms to the next level.

You MUST have this book if...

• You have a difficult engineering or scientific problem and you need an optimization algorithm, this book will tell you which algorithms are suitable for your problem and how to configure them.
• You need some code to get started with a Genetic Algorithm, Particle Swarm, Neural Network or other modern Metaheuristic, this book provides complete and working examples of each algorithm in the Ruby Programming language.
• You are interested or just getting started in the field of Computational Intelligence and Biologically Inspired Computation and feel overwhelmed by the size of the field, this book describes 45 nature-inspired algorithms from across the field of Metahuristics in a consistent manner and groups them by theme.

Clever Algorithms: Statistical Machine Learning Recipes

By Jason Brownlee PhD. First Edition, Lulu Enterprises, [Expected mid 2012]. ISBN: xxx.

Implementing an Machine Learning algorithms is difficult. Algorithm descriptions may be incomplete, inconsistent, and distributed across a number of papers, chapters and even websites. This can result in varied interpretations of algorithms, undue attrition of algorithms, and ultimately bad science.

This book is an effort to address these issues by providing a handbook of algorithmic recipes drawn from the field of Machine Learning, described in a complete, consistent, and centralized manner. These standardized descriptions were carefully designed to be accessible, usable, and understandable.

An encyclopedic algorithm reference, this book is intended for research scientists, engineers, students, and interested amateurs. Each algorithm description provides a working code example in R.

Coming soon...

Get early access to the Table of Contents and early Sample Chapters: Read online