Gain insights into building genetic algorithm frameworks in Elixir. Learn about statistics, genealogy tracking, and solving practical problems with customizable genetic algorithm frameworks.

elixir.tar.gz

Default-elixir

Elixir-genetic

Elixir-genetic-v1

Elixir-genetic-v2

Elixir-breaker

Mix-command

Elixir-encode

Elixir-evaluate

Elixir-encode-speller

Elixir-evaluate-complete

Elixir-evaluate-v2

Elixir-evaluate-v3

Elixir-evaluate-portfolio

Elixir-selection

Elixir-generate

Elixir-generate-orderone

Elixir-selection-random

Elixir-selection-tournament

Elixir-selection-roulette

Elixir-generate-singlepoint

Elixir-generate-uniform

Elixir-generate-whole

Elixir-prematureconverge

Elixir-prematureconverge-complete

Elixir-prematureconverge-complete-nqueens

Elixir-replacing

Elixir-tiger

Elixir-tiger_nogene

Elixir-tiger_gene

Elixir-tiger_visualize-gui

Elixir-tiger_visualize-gui-two

Elixir-tetris

Elixir-benchee

Elixir-profiling

Elixir-pmap

Elixir-nifs

Elixir-testing

Elixir-testing-credo

Elixir-testing-dialyzer

Elixir-tiger_visualize-mtpaint

Elixir-tetris-copy

Elixir-agent-onemax

Elixir-testing-dialyzer-updated

Elixir-tiger_deps.get

Elixir-writing_deps

This course has been designed to introduce you to a field of programming you might have never been exposed to. In this course, you’ll learn everything you need to know to start working with genetic algorithms. As you work through the course, you’ll build a framework for problems using genetic algorithms. By the end, you’ll have a full-featured, customizable framework complete with statistics, genealogy tracking, and more, and you’ll have learned everything you need to solve practical problems with genetic algorithms.

Genetic Algorithms in Elixir

# What is Arcade Learning Environment (ALE)?

The **Arcade Learning Environment (ALE)** is a framework designed to allow programmers to easily develop AI agents for Atari 2600 games. The ALE was originally written in C++ with interfaces to Python, Java, and other languages. The ALE supports numerous Atari ROMs, including popular titles like Tetris, Space Invaders, and Pac-Man.

ALEx stands for Arcade Learning Environment in Elixir. ALEx uses NIFs to create an Elixir wrapper around the ALE to allow Elixir programmers to develop agents for the ALE. ALEx offers all of the same functionality as the ALE, conveniently packaged in an Elixir library.

In this lesson, we’ll use ALEx to evolve agents to play Tetris. The agents we design in this chapter will be naive;  the purpose of this project is simply to see how genetic algorithms can integrate with visual tools to produce real results.


# Installing and compiling ALEx

The ALE, and subsequently ALEx, requires [libsdl1.25](https://www.libsdl.org/) and [cmake](https://cmake.org/). If you don’t have either, install them like this:

```
$ sudo apt-get install libsdl1.2-dev libsdl-gfx1.2-dev \
    libsdl-image1.2-dev cmake
```

Next, add ALEx to your dependencies in `mix.exs`:

Learn what ALE is and how it can be incorporated into our framework. 

Playing Tetris with Genetic Algorithms

Learn what ALE is and how it can be incorporated into our framework.

Introduction

Writing Your First Genetic Algorithm

Breaking Down Genetic Algorithms

Encoding Problems and Solutions

Evaluating Solutions and Populations

Selecting the Best

Generating New Solutions

Preventing Premature Convergence

Replacing and Transitioning

Tracking Genetic Algorithms

Visualizing the Results

Optimizing Your Algorithms

Writing Tests and Code Quality

Moving Forward

Playing Tetris with Genetic Algorithms

What is Arcade Learning Environment (ALE)?