AINeutralarXiv – CS AI · 7h ago6/10
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Task diversity produces systematic transfer but inhibits continual reinforcement learning
Researchers introduce Banyan, a benchmark for studying continual reinforcement learning that reveals task diversity improves immediate transfer between tasks but fails to sustain learning across multiple distribution shifts. While agents trained on diverse tasks generalize well to new task distributions, they forget earlier tasks and struggle with longer-horizon objectives as training continues.