Learning Picture Languages Using Dimensional Reduction
One-dimensional (string) formal languages and their learning have been studied in considerable depth. However, the knowledge of their two-dimensional (picture) counterpart, which retains similar importance, is lacking. We investigate the problem of learning formal two-dimensional picture languages...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Asociación Española para la Inteligencia Artificial
2023-04-01
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| Series: | Inteligencia Artificial |
| Subjects: | |
| Online Access: | https://journal.iberamia.org/index.php/intartif/article/view/1051 |
| Summary: | One-dimensional (string) formal languages and their learning have been studied in considerable depth. However, the knowledge of their two-dimensional (picture) counterpart, which retains similar importance, is lacking. We investigate the problem of learning formal two-dimensional picture languages by applying learning methods for one-dimensional (string) languages. We formalize the transcription process from a two-dimensional input picture into a string and propose a few adaptations to it. These proposals are then tested in a series of experiments, and their outcomes are compared. Finally, these methods are applied to a practical problem and an automaton for recognizing a part of the MNIST dataset is learned. The obtained results show improvements in the topic and the potential to use the learning of automata in fitting problems.
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| ISSN: | 1137-3601 1988-3064 |