title: ÐÐ½Ð¾Ð³Ð¾Ð¿Ð¾ÑÐ¾ÑÐ½Ð°Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð° Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð³ÐµÐ½ÐµÑÐ¸ÑÐµÑÐºÐ¸Ñ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¸ Taichi
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: multi-threaded training program for neural networks using genetic algorithms and taichi
Creators: name: Ð¡ÐµÑÐ¸ÐºÑÐ»Ñ, ÐÐ¸ÑÐ°Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
Ð³ÐµÐ½ÐµÑÐ¸ÑÐµÑÐºÐ¸Ðµ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ
Ð¸Ð³ÑÐ° Ð·Ð¼ÐµÐ¹ÐºÐ°
Python
Taichi
PyQt5
neural networks
genetic algorithms
snake game

description: ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐµ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½ÑÑ ÑÑÐµÐ´ÑÑÐ² Ð¸ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÐ¾Ð² Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÑÑÐ¸Ñ ÑÐµÑÐ°ÑÑ Ð·Ð°Ð´Ð°ÑÐ¸ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð³ÐµÐ½ÐµÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð°. ÐÐ°Ð´Ð°ÑÐ¸, ÐºÐ¾ÑÐ¾ÑÑÐµ ÑÐµÑÐ°Ð»Ð¸ÑÑ Ð² ÑÐ¾Ð´Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ: 1. Ð ÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ Ð³ÐµÐ½ÐµÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð½Ð° ÑÐ·ÑÐºÐµ Python Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Taichi. 2. ÐÐ½Ð°Ð»Ð¸Ð· Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð´Ð¸ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸, ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ Ñ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐºÐ¾Ð¹ PyGAD. 3. Ð ÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð³ÐµÐ½ÐµÑÐ¸ÑÐµ-ÑÐºÐ¸Ñ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð². 4. Ð ÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ Ð³ÑÐ°ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð¿ÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ñ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ PyQt5 Ð´Ð»Ñ Ð´Ðµ-Ð¼Ð¾Ð½ÑÑÑÐ°ÑÐ¸Ð¸ ÑÑÐµÐ´Ñ Ð¸ Ð¿ÑÐ¾ÑÐµÑÑÐ° Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½Ð° Ð·Ð°Ð´Ð°ÑÐµ Ñ Ð¿Ð¾Ð´ÐºÑÐµÐ¿Ð»ÐµÐ½Ð¸ÐµÐ¼. 5. ÐÐ½Ð°Ð»Ð¸Ð· Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½ÑÑ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð². Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ»Ð¾ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð¾ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ðµ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ðµ Ñ Ð³ÑÐ°ÑÐ¸ÑÐµ-ÑÐºÐ¸Ð¼ Ð¸Ð½ÑÐµÑÑÐµÐ¹ÑÐ¾Ð¼, Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ¸ÑÑÑÑÐµÐµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð³ÐµÐ½Ðµ-ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð½Ð° Ð·Ð°Ð´Ð°ÑÐµ Ñ Ð¿Ð¾Ð´ÐºÑÐµÐ¿Ð»ÐµÐ½Ð¸ÐµÐ¼. Ð ÐºÐ°ÑÐµÑÑÐ²Ðµ Ð¿ÑÐ¸Ð¼ÐµÑÐ° Ð±ÑÐ»Ð° Ð²ÑÐ±ÑÐ°Ð½Ð° Ð¸Ð³ÑÐ° âÐÐ¼ÐµÐ¹ÐºÐ°â. ÐÑÐ¸Ð»Ð¾Ð¶ÐµÐ½Ð¸Ðµ Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÐµÑ Ð½Ð°Ð±Ð»ÑÐ´Ð°ÑÑ Ð·Ð° Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ð¼ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð°Ð³ÐµÐ½ÑÐ¾Ð² Ð² Ð¾Ð±ÑÑÐ°ÑÑÐµÐ¹ ÑÑÐµÐ´Ðµ.
description: This work is devoted to the development of software and tools to solve the problem of training neural networks using a genetic algorithm. The tasks that were solved during the research were: 1. Implementation of genetic algorithm in Python using Taichi. 2. Performance analysis, comparison with PyGAD library. 3. Implementation of neural network learning algorithm using genetic algorithms. 4. Implementation of a graphical application using PyQt5 to demonstrate the environÂ¬ment and learning process on a reinforcement task. 5. Analysis of the results obtained. As a result of the work, software with graphical interface was developed to demon-strate the training of neural network using genetic algorithm on the task with reinforce-ment. The game "Snake" was chosen as an example. The application allows you to observe the learning process of the agents in a learning environment.