TEXNIKANING RIVOJLANTIRISHDA SUN`IY INTELEKTLARDAN FOYDALANISH.
Ключевые слова:
Kalit so'zlar: Sun'iy intellekt, texnikani ishlab chiqish, mashinani o'rganish, neyron tarmoqlar, avtomatlashtirish, optimallashtirish.Аннотация
Annotatsiya. Ushbu maqola sun'iy intellektning texnikani ishlab chiqishda
integratsiyasini o'rganadi, uning salohiyati, muammolari va oqibatlarini ta'kidlaydi.
Mashinani o'rganish va neyron tarmoqlari kabi sun'iy intellekt texnologiyalaridan
foydalangan holda tadqiqotchilar texnikani ishlab chiqish jarayonlarining
samaradorligi, aniqligi va ko'lamini oshirishi mumkin. Adabiyotlarni tahlil qilish orqali
ushbu maqola sun'iy intellektga asoslangan texnikani rivojlantirishning hozirgi holatini
o'rganadi, asosiy metodologiyalarni muhokama qiladi, empirik natijalarni taqdim etadi
va kelajakdagi yo'nalishlar haqida tushuncha beradi. Umuman olganda, u texnikani
rivojlantirishda sun'iy intellektning muhim rolini ta'kidlaydi va tegishli muammolarni
hal qilishda uning afzalliklarini maksimal darajada oshirish strategiyasini taklif qiladi.
Библиографические ссылки
Adabiyotlar.
A. M. Turing. “Computing machinery and intelligence”. In: Parsing the Turing
Test. Springer, 2009, pp. 23–65.
S. Russell et al. Artificial Intelligence: A Modern Approach. 3rd ed. Prentice Hall,
D. Chen et al. Autonomous Driving using Safe Reinforcement Learning by
Incorporating a Regret-based Human Lane-Changing Decision Model. 2019.
arXiv: 1910.04803 [cs.RO].
P. Palanisamy. Multi-Agent Connected Autonomous Driving using Deep
Reinforcement Learning. 2019. arXiv: 1911.04175 [cs.LG].
S. Wang et al. “Deep Reinforcement Learning for Autonomous Driving”. In: arXiv
preprint arXiv:1811.11329 (2018).
A. E. Sallab et al. “Deep reinforcement learning framework for autonomous
driving”. In: Electronic Imaging 2017.19 (2017), pp. 70–76.
Z. Xu et al. “Zero-shot Deep Reinforcement Learning Driving Policy Transfer for
Autonomous Vehicles based on Robust Control”. In: 2018 21st International
Conference on Intelligent Transportation Systems (ITSC). IEEE. 2018, pp. 2865–
D. Silver et al. “Mastering the game of Go with deep neural networks and tree
search”. In: nature 529.7587 (2016), p. 484.
