Playing Tetris with Genetic Algorithms
Explore how to leverage ALEx, the Elixir wrapper for the Arcade Learning Environment, to create genetic algorithm-driven AI agents that play Tetris. Learn to compile ALEx, set up game agents, and visualize genetic algorithm outcomes in real-time gameplay, gaining practical skills in AI development within Elixir.
We'll cover the following...
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 ...