Symmetry as a Representation of Intuitive Geometry?

2022/06/04 by Wangcheng Xu, Xu, Wangcheng, Snejana Shegheva +3
Computer Science · #Artificial Intelligence (cs.AI) #Artificial Intelligence in Education #Cognitive Computing and Networks #Cognitive Science and Mapping #FOS: Computer and information sciences

paper · pdf · doi:10.48550/arxiv.2206.02019

openalex publication_date 2022/06/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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.

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