Обучение агентов в виртуальной среде KukaDiversObjectEnv
| Parent link: | Курзина, И. А. (химик ; 1972-). Перспективы развития фундаментальных наук=Prospects of Fundamental Sciences Development: сборник научных трудов XXI Международной конференции студентов, аспирантов и молодых ученых, г. Томск, 23-26 апреля 2024 г..— .— Томск: Изд-во ТПУ Т. 7 : IT-технологии и электроника.— 2024.— С. 42-44 |
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| Summary: | Заглавие с экрана The present study implements and compares the DQN, PPO, Parallel PPO, and Modified PPO algorithms in the PyBullet KukaDiverseObjectEnv environment. The algorithms are tested and evaluated in a simulated test mode to assess their performance. The experiments focus on metrics such as learning speed, stability, and task completion success rate. The results provide insights into the effectiveness of each algorithm in the tested environment, aiding in the optimization of reinforcement learning algorithms for complex environments and robotics Текстовый файл |
| Language: | Russian |
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2024
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| Online Access: | http://earchive.tpu.ru/handle/11683/80462 |
| Format: | Electronic Book Chapter |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=674286 |