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Symmetry as a Representation of Intuitive Geometry?

arXiv 2206.02019 ↗First posted 4 Jun 2022cs.AIcited by 0

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Abstract (arXiv)

Recognition of geometrical patterns seems to be an important aspect of human intelligence. Geometric pattern recognition is used in many intelligence tests, including Dehaene's odd-one-out test of Core Geometry (CG)) based on intuitive geometrical concepts (Dehaene et al., 2006). Earlier work has developed a symmetry-based cognitive model of Dehaene's test and demonstrated performance comparable to that of humans. In this work, we further investigate the role of symmetry in geometrical intuition and build a cognitive model for the 2-Alternative Forced Choice (2-AFC) variation of the CG test (Marupudi & Varma 2021). In contrast to Dehaene's test, 2-AFC leaves almost no space for cognitive models based on generalization over multiple examples. Our symmetry-based model achieves an accuracy comparable to the human average on the 2-AFC test and appears to capture an essential part of intuitive geometry.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 28 references that are in the map. First posted on arXiv 4 Jun 2022.

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References · 4

  1. 2017A simple neural network module for relational reasoningcited by 346
  2. 2019RAVEN: A Dataset for Relational and Analogical Visual rEasoNingcited by 226
  3. 2018Measuring abstract reasoning in neural networkscited by 166
  4. 2019Learning Perceptual Inference by Contrastingcited by 57

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