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Discovering Geometry Theorems in Regular Polygons

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Artificial Intelligence and Symbolic Computation (AISC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11110))

Abstract

By using a systematic, automated way, we discover a large amount of geometry statements on regular polygons. Given a regular n-gon, its diagonals are taken, two pairs of them may determine a pair of intersection points that define a segment. By considering all possible segments defined in this way, we can compute the lengths of them symbolically, and, depending on the simplicity of the symbolic result we classify the segment either as “interesting” or “not interesting”.

Among others, we prove that in a regular 11-gon with unit sides the only rational lengths appearing the way described above, are 1 and 2, and the only quadratic surd is \(\sqrt{3}\). The applied way of proving is exhaustion, by using the freely available software tool RegularNGons, programmed by the author. The combinatorial explosion, however, calls for future improvements involving methods in artificial intelligence.

The symbolic method being used is Wu’s algebraic geometry approach [1], combined with the discovery algorithm communicated by Recio and Vélez [2]. The heavy computations are performed by a recent version of the Giac computer algebra software, running in a web browser with the support of the recent technology WebAssembly. Visual communication of the obtained results is operated by the dynamic geometry software GeoGebra.

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Acknowledgements

The author was partially supported by a grant MTM2017-88796-P from the Spanish MINECO (Ministerio de Economia y Competitividad) and the ERDF (European Regional Development Fund). Many thanks to Tomás Recio and Francisco Botana for their valuable comments and suggestions. The JavaScript implementation in RegularNGons was supported by Gábor Ancsin and the GeoGebra Team.

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Correspondence to Zoltán Kovács .

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Kovács, Z. (2018). Discovering Geometry Theorems in Regular Polygons. In: Fleuriot, J., Wang, D., Calmet, J. (eds) Artificial Intelligence and Symbolic Computation. AISC 2018. Lecture Notes in Computer Science(), vol 11110. Springer, Cham. https://doi.org/10.1007/978-3-319-99957-9_10

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  • DOI: https://doi.org/10.1007/978-3-319-99957-9_10

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