title: ÐÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¸ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¸Ð¼Ð¸ÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð°Ð²ÑÐ¾Ð½Ð¾Ð¼Ð½Ð¾Ð³Ð¾ Ð¿Ð¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ Ð°Ð³ÐµÐ½ÑÐ° Ð½Ð° Ð¿ÑÐ¸Ð¼ÐµÑÐµ Ð²Ð¸Ð´ÐµÐ¾Ð¸Ð³ÑÐ¾Ð²Ð¾Ð¹ ÑÑÐµÐ´Ñ
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: Research and implementation of a imitation learning method for creating an agent using a video game environment as an example
Creators: name: Ð¯ÑÐ¾ÑÐµÐ²Ð¸Ñ, ÐÐ³Ð¾Ñ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: 2025
Subjects: Ð¸Ð¼Ð¸ÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ Ñ Ð¿Ð¾Ð´ÐºÑÐµÐ¿Ð»ÐµÐ½Ð¸ÐµÐ¼
Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ
imitation learning
machine learning
reinforcement learning
algorithms

description: ÐÐ°ÑÑÐ¾ÑÑÐ°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¸Ð¼Ð¸ÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð°Ð²ÑÐ¾Ð½Ð¾Ð¼Ð½Ð¾Ð³Ð¾ Ð°Ð³ÐµÐ½ÑÐ° Ð² ÑÐ¸Ð¼ÑÐ»ÑÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÑÐµÐ´Ðµ. Ð ÑÐ¾Ð´Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð° Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð°Ñ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ Ð¿Ð¾ÑÑÐ°Ð¿Ð½Ð¾Ð³Ð¾ Ð¿ÑÐ¾ÑÐµÑÑÐ° Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð°Ð³ÐµÐ½ÑÐ° Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° DAgger (Dataset Aggregation), Ð° ÑÐ°ÐºÐ¶Ðµ Ð¿ÑÐµÐ´ÑÑÐ°Ð²Ð»ÐµÐ½ Ð½Ð¾Ð²ÑÐ¹ Ð³Ð¸Ð±ÑÐ¸Ð´Ð½ÑÐ¹ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼, Ð¾Ð±ÑÐµÐ´Ð¸Ð½ÑÑÑÐ¸Ð¹ Ð¿Ð¾Ð´ÑÐ¾Ð´Ñ DAgger Ð¸ GAIL (Generative Adversarial Imitation Learning). ÐÑÐµÐ´Ð¼ÐµÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ: Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ Ð¸Ð¼Ð¸ÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸ Ð¸Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð² Ð·Ð°Ð´Ð°ÑÐ°Ñ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð°Ð³ÐµÐ½ÑÐ°Ð¼Ð¸. Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ: ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð°Ð²ÑÐ¾Ð½Ð¾Ð¼Ð½Ð¾Ð³Ð¾ Ð°Ð³ÐµÐ½ÑÐ° Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ð¸Ð¼Ð¸ÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ Ð²Ð·Ð°Ð¸Ð¼Ð¾Ð´ÐµÐ¹ÑÑÐ²Ð¸Ñ Ð² Ð²Ð¸Ð´ÐµÐ¾Ð¸Ð³ÑÐ¾Ð²Ð¾Ð¹ ÑÑÐµÐ´Ðµ. ÐÐµÑÐ¾Ð´Ñ Ð¸ Ð¼ÐµÑÐ¾Ð´Ð¾Ð»Ð¾Ð³Ð¸Ñ: Ð°Ð½Ð°Ð»Ð¸Ð· ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð², ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ðµ Ð½Ð° Ð¸Ñ Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¼Ð¾Ð´Ð¸ÑÐ¸ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð³Ð¾ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð°, ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð°Ð³ÐµÐ½ÑÐ° Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐº Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð½Ð° ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ ÐºÐ¾Ð½ÑÐ¸Ð³ÑÑÐ°ÑÐ¸ÑÑ Ð¾ÐºÑÑÐ¶ÐµÐ½Ð¸Ñ, ÑÑÐ°Ð²Ð½Ð¸ÑÐµÐ»ÑÐ½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½ÑÑ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð². Ð ÐµÐ·ÑÐ»ÑÑÐ°ÑÑ: ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½ Ð°Ð²ÑÐ¾Ð½Ð¾Ð¼Ð½ÑÐ¹ Ð°Ð³ÐµÐ½Ñ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¸Ð¼Ð¸ÑÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ ÑÐ²ÐµÑÑÐ¾ÑÐ½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸, ÑÐ¿Ð¾ÑÐ¾Ð±Ð½ÑÐ¹ Ð¾ÑÐ¸ÐµÐ½ÑÐ¸ÑÐ¾Ð²Ð°ÑÑÑÑ Ð² ÑÐ»Ð¾Ð¶Ð½Ð¾Ð¹ ÑÐ¸Ð¼ÑÐ»ÑÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÑÐµÐ´Ðµ. ÐÐ±Ð»Ð°ÑÑÑ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ: Ð°Ð²ÑÐ¾Ð½Ð¾Ð¼Ð½ÑÐµ ÑÑÐ°Ð½ÑÐ¿Ð¾ÑÑÐ½ÑÐµ ÑÑÐµÐ´ÑÑÐ²Ð°, ÑÐ¾Ð±Ð¾ÑÐ¾ÑÐµÑÐ½Ð¸ÐºÐ°, Ð²Ð¸Ð´ÐµÐ¾Ð¸Ð³ÑÐ¾Ð²Ð°Ñ ÑÑÐµÑÐ°. ÐÑÐ²Ð¾Ð´Ñ: Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½Ð½ÑÐ¹ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼, Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð½ÑÐ¹ Ð½Ð° ÐºÐ¾Ð¼Ð±Ð¸Ð½Ð°ÑÐ¸Ð¸ DAgger Ð¸ GAIL, Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÐµÑ ÑÑÐºÐ¾ÑÐ¸ÑÑ Ð¿ÑÐ¾ÑÐµÑÑ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð°Ð³ÐµÐ½ÑÐ° Ð·Ð° ÑÑÐµÑ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾Ð³Ð¾ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ°ÑÐ¸Ð¹ ÑÐºÑÐ¿ÐµÑÑÐ°. Ð ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ð¸ Ñ Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ñ Ð¿Ð¾Ð´ÐºÑÐµÐ¿Ð»ÐµÐ½Ð¸ÐµÐ¼, Ð¼Ð¾Ð´ÐµÐ»Ñ Ð´Ð¾ÑÑÐ¸Ð³Ð°ÐµÑ ÑÑÐ°Ð²Ð½Ð¸Ð¼ÑÑ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð² Ð¿ÑÐ¸ Ð¼ÐµÐ½ÑÑÐ¸Ñ Ð²ÑÑÐ¸ÑÐ»Ð¸ÑÐµÐ»ÑÐ½ÑÑ Ð·Ð°ÑÑÐ°ÑÐ°Ñ Ð¸ Ð¼ÐµÐ½ÑÑÐµÐ¼ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ðµ Ð¸ÑÐµÑÐ°ÑÐ¸Ð¹.
description: his study focuses on the exploration of imitation learning algorithms for developing an autonomous agent in a simulation environment. As part of the research, a step-by-step training process for an agent using the DAgger (Dataset Aggregation) algorithm was implemented, and a novel hybrid algorithm combining DAgger and GAIL (Generative Adversarial Imitation Learning) was proposed. Research subject: Imitation learning algorithms and their application in agent control tasks. Objective: Development of an autonomous agent based on imitation learning algorithms for interaction in a video game environment. Methods and methodology: Analysis of existing algorithms, development of a modified algorithm based on them, implementation of an agent using machine learning libraries, testing on various environment configurations, and comparative analysis of the obtained results. Results: An autonomous agent based on imitation learning with a convolutional neural network was developed, capable of navigating a complex simulation environment. Application areas: Autonomous transportation, robotics, video game industry. Conclusions: The proposed algorithm, based on a combination of DAgger and GAIL, accelerates the agent training process through efficient use of expert demonstrations. Compared to reinforcement learning methods, the model achieves comparable performance with lower computational costs and fewer iterations.