  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.

Artificial Intelligence