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.

The Game Boy learning environment

Fazzari E.;Falchi F.;
2025

Abstract

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.
2025
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Artificial Intelligence
Deep Reinforcement Learning
Game Boy
Learning Environments
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/552087
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