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Abstract:

This paper explores the different understandings of the term "open world" in AI research, categorizing them into partially open world and fully open world. By distinguishing between intelligence and skills, I argue that a fully open world is essential for evaluating intelligence, while a partially open world risks shifting focus towards problem-specific skills. However, both partially open and closed worlds can still be valuable research tools if the underlying assumptions of AI systems are carefully examined.

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