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When intelligence is just a matter of copying

机译:当智力只是复制的问题时

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The paper investigates a general approach that allows us to solve IQ tests based on Raven's progressive matrices automatically. The 3×3 Raven matrices exhibit 8 geometric pictures displayed in 8 cells of the matrix, which have to be logically completed with a 9th picture to be put in the remaining empty matrix cell. In these tests, a set of candidate pictures for the solution is also given. The suggested approach is based on a logical view of analogical proportions (i.e., statements of the form "A is to B as C is to D"). The reading of Raven matrices in terms of such proportions can be applied to a feature-based description of the pictures, but also, in a number of cases, to a very low level representation, i.e., the pixel level. It appears that the analogical proportion reading just amounts here to a recopy of patterns of feature values that already appear in the data (after checking that there is no conflicting patterns). Implementing this principle, the proposed algorithm computes the 9th picture, without the help of any set of candidate solutions, but only on the basis of the 8 known cells of the Raven matrices. A comparison with other approaches is provided, and we emphasize the generality of the approach which is able to provide a simple and uniform mechanism applicable in many situations.
机译:本文研究了一种通用方法,该方法使我们能够基于Raven的渐进矩阵自动解决IQ测试。 3×3 Raven矩阵显示在矩阵的8个单元中显示的8个几何图形,必须在逻辑上完成第9个图形才能放入剩余的空矩阵单元中。在这些测试中,还给出了该解决方案的一组候选图片。建议的方法基于类比比例的逻辑视图(即,形式为“ A对B就像C对D一样”)。以这种比例表示的Raven矩阵的读取可以应用于图片的基于特征的描述,但是在许多情况下,还可以应用于非常低级的表示,即像素级。看起来,类比比例在这里仅相当于对已经出现在数据中的特征值的模式进行重新复制(在检查没有冲突的模式之后)。实现此原理后,所提出的算法无需借助任何候选解集即可计算第9张图片,而仅基于Raven矩阵的8个已知像元进行计算。提供了与其他方法的比较,并且我们强调了该方法的一般性,该方法能够提供适用于许多情况的简单且统一的机制。

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