<ul><li>Humans can continuously acquire new skills and knowledge by exploiting existing ones for improved learning, without forgetting them.</li><li>'Continual learning' in machine learning aims to learn new information while preserving the previously acquired knowledge.</li><li>A new method is proposed that interleaves tasks based on their 'learning progress' and energy consumption, mimicking human task learning.</li><li>Experiments conducted with a robot learning setting show that the proposed method achieves better performance and reduces energy consumption for learning tasks.</li></ul>

Energy Weighted Learning Progress Guided Interleaved Multi-Task Learning

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