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Genetic Algorithms in Elixir (PragProg)

Sean Moriarity @seanmor5

edited by Tammy Coron @Paradox927

From finance to artificial intelligence, genetic algorithms are a powerful tool with a wide array of applications. But you don’t need an exotic new language or framework to get started; you can learn about genetic algorithms in a language you’re already familiar with. Join us for an in-depth look at the algorithms, techniques, and methods that go into writing a genetic algorithm. From introductory problems to real-world applications, you’ll learn the underlying principles of problem solving using genetic algorithms.

Evolutionary algorithms are a unique and often overlooked subset of machine learning and artificial intelligence. Because of this, most of the available resources are outdated or too academic in nature, and none of them are made with Elixir programmers in mind.

Start from the ground up with genetic algorithms in a language you are familiar with. Discover the power of genetic algorithms through simple solutions to challenging problems. Use Elixir features to write genetic algorithms that are concise and idiomatic. Learn the complete life cycle of solving a problem using genetic algorithms. Understand the different techniques and fine-tuning required to solve a wide array of problems. Plan, test, analyze, and visualize your genetic algorithms with real-world applications.

Open your eyes to a unique and powerful field—without having to learn a new language or framework.


Sean Moriarity graduated from the United States Military Academy with a degree in Computer Science. Sean was first introduced to genetic algorithms while on a summer internship which inspired him to write Genex, a library for writing evolutionary algorithms in Elixir. Many of the problems and solutions you’ll encounter in this book were inspired from the lessons learned while developing Genex. Sean’s passions include functional programming, artificial intelligence, mathematics, and, of course, evolutionary algorithms.


Don’t forget you can get 35% off with your Devtalk discount! Just use the coupon code “devtalk.com" at checkout :+1:


Posted via Devtalk.

First Post!

PragmaticBookshelf

PragmaticBookshelf

Forum Sponsor

Sean Moriarity @seanmor5

edited by Tammy Coron @Paradox927

From finance to artificial intelligence, genetic algorithms are a powerful tool with a wide array of applications. But you don’t need an exotic new language or framework to get started; you can learn about genetic algorithms in a language you’re already familiar with. Join us for an in-depth look at the algorithms, techniques, and methods that go into writing a genetic algorithm. From introductory problems to real-world applications, you’ll learn the underlying principles of problem solving using genetic algorithms.

Evolutionary algorithms are a unique and often overlooked subset of machine learning and artificial intelligence. Because of this, most of the available resources are outdated or too academic in nature, and none of them are made with Elixir programmers in mind.

Start from the ground up with genetic algorithms in a language you are familiar with. Discover the power of genetic algorithms through simple solutions to challenging problems. Use Elixir features to write genetic algorithms that are concise and idiomatic. Learn the complete life cycle of solving a problem using genetic algorithms. Understand the different techniques and fine-tuning required to solve a wide array of problems. Plan, test, analyze, and visualize your genetic algorithms with real-world applications.

Open your eyes to a unique and powerful field—without having to learn a new language or framework.


Sean Moriarity graduated from the United States Military Academy with a degree in Computer Science. Sean was first introduced to genetic algorithms while on a summer internship which inspired him to write Genex, a library for writing evolutionary algorithms in Elixir. Many of the problems and solutions you’ll encounter in this book were inspired from the lessons learned while developing Genex. Sean’s passions include functional programming, artificial intelligence, mathematics, and, of course, evolutionary algorithms.


Don’t forget you can get 35% off with your Devtalk discount! Just use the coupon code “devtalk.com" at checkout :+1:


Posted via Devtalk.

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seanmor5

seanmor5

Author of Genetic Algorithms in Elixir

@kokolegorille Author here. Thanks for sharing! If anybody has any questions or comments about the book, feel free to PM me!

28
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kokolegorille

kokolegorille

A new Elixir resource is available

13
Post #1
qhwa

qhwa

Exactly correct for me :smiley: I’ve been using genetic algorithm in one of our products where we needed to solve a problem similar to the Vehicle Routing Problem and this book helped a lot. While there are a lot of solutions for VRP, I think genetic algorithm is still interesting as the fitness function can be easily extended as the business evolves.

One thing I find hard when using genetic algorithms is modeling the problem, or how to present the solution better. I would be very happy If the book can provide more help on it.

Last Post!

pragprog

pragprog

If you liked the book, please leave a review at Amazon or Goodreads. It means a lot to the author and helps spread the word. Thank you!

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