Publication at Faculty of Mathematics and Physics |
2020
Abstract
Analysis of two-dimensional (picture) formal languages is of similar importance as analysis of their one-dimensional (string) counterparts but is lacking state-of-the-art algorithms for their learning. In this paper, we introduce a new representation of picture languages based on mapping pictures to strings.
The representation enables to learn picture languages by applying methods of grammatical inference for string languages. We propose a learning protocol and evaluate it on several picture languages.