Genetic Algorithms in Elixir: Solve Problems Using Evolution

Moriarity, Sean

商品描述

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 Because of this, most of the available resources are outdated or too academic in nature, and none of them are made with Elixir programmers in mind.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.

What You Need:

You'll need a macOS, Windows, or Linux distribution with an up-to-date Elixir installation.

商品描述(中文翻譯)

從金融到人工智慧,遺傳演算法是一種功能強大且應用廣泛的工具。但你並不需要學習一種新的奇特語言或框架,你可以在你已經熟悉的語言中學習遺傳演算法。加入我們,深入研究遺傳演算法的演算法、技巧和方法。從入門問題到實際應用,你將學習使用遺傳演算法解決問題的基本原理。

進化演算法是機器學習和人工智慧中獨特且常被忽視的子集。因此,大部分可用的資源已經過時或過於學術化,而且沒有一個是針對 Elixir 程式設計師而製作的。

從你熟悉的語言開始學習遺傳演算法。通過簡單的解決方案來挑戰困難的問題,發現遺傳演算法的威力。使用 Elixir 的特性來撰寫簡潔且符合慣用法的遺傳演算法。了解使用遺傳演算法解決問題的完整生命週期。理解解決各種問題所需的不同技巧和微調。使用真實應用程式來計劃、測試、分析和視覺化你的遺傳演算法。

打開你的眼界,進入一個獨特而強大的領域 - 而不需要學習一種新的語言或框架。

你需要一台安裝最新版 Elixir 的 macOS、Windows 或 Linux 發行版。

作者簡介

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.

作者簡介(中文翻譯)

Sean Moriarity畢業於美國陸軍學院,獲得計算機科學學位。Sean在暑期實習期間首次接觸到遺傳算法,這激發了他寫Elixir的演化算法庫Genex的靈感。本書中許多問題和解決方案都受到開發Genex時所學到的教訓的啟發。Sean的興趣包括函數式編程、人工智慧、數學,當然還有演化算法。