Abstract
We are developing a machine reasoning engine that can learn arbitrary concepts from small number of training samples, and generate explainable models which can be visualized graphically. In this article, we present our intermediate results by experimenting with problems that require reasoning with simple arithmetic, geometric shapes, logical operators, simple program syntax, and regular and context-free languages.
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Notes
- 1.
This work has been supported by TÜBİTAK under 2232 International Fellowship for Outstanding Researchers Program (Project No: 118C228). However, the responsibility of the paper belongs to the author. The financial support does not mean that the content of the publication is approved in a scientific sense by TÜBİTAK.
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Erbas, C. (2023). A General-Purpose Machine Reasoning Engine. In: Goertzel, B., Iklé, M., Potapov, A., Ponomaryov, D. (eds) Artificial General Intelligence. AGI 2022. Lecture Notes in Computer Science(), vol 13539. Springer, Cham. https://doi.org/10.1007/978-3-031-19907-3_1
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