Gelder, Jeroen van (2021) A Twitter Bot Based on A Tableau Solver for GL Logic. Bachelor's Thesis, Artificial Intelligence.
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Abstract
In 2017 a tableau solver for provability logic (GL) was built, which faced a number of memory issues. In an attempt to improve memory efficiency, a new tableau solver is built for GL using an object-oriented approach in Python, as well as implementing both depth-first search and culling of closed branches. Alongside, a procedural generator for formulas of GL is built, and a Twitter bot is made that tweets all found theorems of GL at an interval of three hours. Depth-first search is implemented in order to find the easy answer the quickest, as a complete tableau is not required. The culling of closed branches is implemented in an attempt to keep memory usage to a minimum. After testing the system with more than one million formulas, no out-of-memory issues are found, indicating that memory efficiency has improved.
| Item Type: | Thesis (Bachelor's Thesis) |
|---|---|
| Supervisor name: | Verbrugge, L.C. |
| Degree programme: | Artificial Intelligence |
| Thesis type: | Bachelor's Thesis |
| Language: | English |
| Date Deposited: | 20 Jul 2021 13:15 |
| Last Modified: | 20 Jul 2021 13:15 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/25345 |
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