This paper introduces A-RSI, a method that helps AI models decide when to stop learning from their current experience and introduce new tasks, without relying on external validation or human feedback. By monitoring the model's learning signal and accuracy, A-RSI can automatically refresh the task pool, leading to improved performance.
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