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The Game Boy Learning Environment
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DOI：10.1109/TG.2025.3575527.png)
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Abstract
En 中文
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 11 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, such as 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.
Keywords:
Games
Artificial intelligence
Video games
Training
Decision making
Visualization
Navigation
Robots
Q-learning
Observability
deep reinforcement learning (RL)
game boy
learning environments
Journal
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2.8
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