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

# Tracking statistics using GenServer and ETS

During an evolution, we may want to track statistics about fitness, age, or variation in your population over the course of the evolution. For example, perhaps we want to determine the distribution of a particular gene at different generations during evolution.
In this lesson, we’ll create a statistics server using a GenServer and an ETS table.


> A GenServer is an abstraction around a state that models client-server behavior. It allows us to spin up a long-running process and alter its state through message passing. “ETS” stands for “Erlang Term Storage” and offers a built-in storage API through Erlang interpolation. 
<br/><br/>
> The GenServer will allow us to supervise the ETS table which in turn, will allow us to quickly and easily insert and lookup statistics across generations. In addition, it’ll be easy to expand this approach to all kinds of statistics and metrics.

# Creating the statistics server

Start by creating a new `utilities` directory inside `lib`, and inside that new directory, add a new file named `statistics.ex`. This file will contain the implementation for the statistics server. Over here, start by defining a bare-bones GenServer implementation:

Learn how to create a statistics server for tracking progress using GenServer and ETS.

Logging Statistics Using ETS

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

Logging Statistics Using ETS

Tracking statistics using GenServer and ETS