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JAXtari: High-Throughput and Easy-to-Modify Arcade Learning Environment
The Arcade Learning Environment (ALE) has been a cornerstone of Deep Reinforcement Learning research, providing a standardized benchmark for evaluating general agents. However, its lack of native support for object-extraction and environment modification restricts research into evaluating whether ag
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