Fact-Free Learning
指出人们能从已有知识中发现规律，即无需新事实也能学习，并从计算复杂性角度解释这一现象，证明在知识库中寻找小变量集以获得特定R²值是计算困难的。
People may be surprised to notice certain regularities that hold in existing knowledge they have had for some time. That is, they may learn without getting new factual information. We argue that this can be partly explained by computational complexity. We show that, given a knowledge base, finding a small set of variables that obtain a certain value of R 2 is computationally hard, in the sense that this term is used in computer science. We discuss some of the implications of this result and of fact-free learning in general.