GENERATIV SUN'IY INTELLEKT ASOSIDA MATEMATIK MASALALARNI AVTOMATIK YECHISH USULLARI

Authors

  • Fayzullayeva E’zoza Shahrisabz davlat pedagogika instituti, Aniq fanlar oliy pedagogika maktabi, Matematika yo‘nalishi, 2-kurs talabasi Author

DOI:

https://doi.org/10.65164/2svewa12

Keywords:

generativ sun'iy intellekt, transformer modeli, neyron-simvolik tizim, LLM

Abstract

Ushbu maqolada generativ sun'iy intellekt (GSI) texnologiyalarining matematik masalalarni avtomatik yechishdagi qo'llanilishi nazariy va tahliliy nuqtai nazardan o'rganilgan. Transformer arxitekturasiga asoslangan katta til modellari (LLM), neyron-simvolik gibrid tizimlar va matematik muhokama granularligini ta'minlovchi yangi yondashuvlar tahlil qilingan. Tadqiqot maqsadi – mavjud GSI tizimlarining matematik masalalarni yechish samaradorligini qiyosiy tahlil qilish va pedagogik amaliyotda qo'llash uchun metodik tavsiyalar ishlab chiqishdan iborat.

References

1. Bubeck S. et al. (2023). Sparks of Artificial General Intelligence: Early experiments with GPT-4. arXiv:2303.12712.

2. Wei J. et al. (2022). Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. NeurIPS 2022.

3. Brown T. et al. (2020). Language Models are Few-Shot Learners (GPT-3). NeurIPS 2020.

4. Vaswani A. et al. (2017). Attention Is All You Need. NeurIPS 2017.

5. Yao S. et al. (2023). Tree of Thoughts: Deliberate Problem Solving with Large Language Models. arXiv:2305.10601.

6. Gao L. et al. (2023). PAL: Program-aided Language Models. ICML 2023.

7. Hendrycks D. et al. (2021). Measuring Mathematical Problem Solving With the MATH Dataset. NeurIPS 2021.

8. Trinh T. H. et al. (2024). Solving olympiad geometry without human demonstrations (AlphaGeometry). Nature, 625, 476–482.

9. Wolfram S. (2002). A New Kind of Science. Wolfram Media.

10. Mirzayev A. (2023). Raqamli ta'lim texnologiyalari va ularning O'zbekiston maktablarida joriy etilishi. Pedagogika jurnali, 4, 45–52.

Downloads

Published

2026-05-15