The Game Boy Learning Environment

In this article, we introduce the Game Boy Learning Environment (GLE), an innovative suite based on Nintendo Game Boy games, crafted to advance and evaluate deep reinforcement learning algorithms on rich and varied gameplay tasks. GLE offers a comprehensive selection of eleven Game Boy environments, spanning nine distinct titles. These environments represent a significant leap in complexity compared to previous endeavors, like the Arcade Learning Environment, presenting challenges for reinforcement learning like intricate long-term planning, strategic foresight, and hierarchical decision-making, posing substantial difficulties even for proficient human players. We delineate the spectrum of available environments and furnish initial baseline results obtained through the development and assessment of intelligent agents, employing established AI methodologies to address individual levels or subtasks within these environments. All software is openly accessible to the public via <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/edofazza/GameBoyLearningEnvironment</uri>.