FGeo-SSS: A Search-Based Symbolic Solver for Human-like Automated Geometric Reasoning

• Published in: Symmetry (Basel) Vol. 16; no. 4; p. 404
• Main Authors: Zhang, Xiaokai, Zhu, Na, He, Yiming, Zou, Jia, Qin, Cheng, Li, Yang, Leng, Tuo
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2024
• Subjects: Algebra; Algorithms; Artificial intelligence; Asymmetry; Automated reasoning; Automation; Computational linguistics; Construction; Design; Geometric reasoning; Geometry; Heuristic; Language; Language processing; Methods; Natural language; Natural language interfaces; Predicate logic; Problem solving; Python; Readability; Search methods; Solvers; Symmetry; Technology application; Theorems; Germany
• ISSN: 2073-8994; 2073-8994
• DOI: 10.3390/sym16040404

Geometric problem solving (GPS) has always been a long-standing challenge in the fields of automated reasoning. Its problem representation and solution process embody rich symmetry. This paper is the second in a series of our works. Based on the Geometry Formalization Theory and the FormalGeo geometric formal system, we have developed the Formal Geometric Problem Solver (FGPS) in Python 3.10, which can serve as an interactive assistant or as an automated problem solver. FGPS is capable of executing geometric predicate logic and performing relational reasoning and algebraic computation, ultimately achieving readable, traceable, and verifiable automated solutions for geometric problems. We observed that symmetry phenomena exist at various levels within FGPS and utilized these symmetries to further refine the system’s design. FGPS employs symbols to represent geometric shapes and transforms various geometric patterns into a set of symbolic operation rules. This maintains symmetry in basic transformations, shape constructions, and the application of theorems. Moreover, we also have annotated the formalgeo7k dataset, which contains 6981 geometry problems with detailed formal language descriptions and solutions. Experiments on formalgeo7k validate the correctness and utility of the FGPS. The forward search method with random strategy achieved a 39.71% problem-solving success rate.