2021/06/27 by J. Macke, Jiří Sedlář, Macke, J. +6 · 1 citation
Computer Science · Engineering · #Advanced Numerical Analysis Techniques #Artificial Intelligence (cs.AI) #Computational Geometry (cs.CG) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image and Object Detection Techniques #Logic in Computer Science (cs.LO) #Machine Learning (cs.LG) #Robotic Mechanisms and Dynamics
paper · pdf · doi:10.48550/arxiv.2106.14195
openalex publication_date 2021/06/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We describe a purely image-based method for finding geometric constructions with a ruler and compass in the Euclidea geometric game. The method is based on adapting the Mask R-CNN state-of-the-art image processing neural architecture and adding a tree-based search procedure to it. In a supervised setting, the method learns to solve all 68 kinds of geometric construction problems from the first six level packs of Euclidea with an average 92% accuracy. When evaluated on new kinds of problems, the method can solve 31 of the 68 kinds of Euclidea problems. We believe that this is the first time that a purely image-based learning has been trained to solve geometric construction problems of this difficulty.