Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: International Scientific and Research Conference on Topical Issues in Aeronautics and Astronautics, TIAA 2016; Krasnoyarsk; Krasnoyarsk
Год издания: 2016
Идентификатор DOI: 10.1088/1757-899X/155/1/012001
Аннотация: This paper presents algorithm for generating neuroevolutionary multi-agent system that allows agents to learn from high-quality activities. Dissimilar traditional learning algorithms proposed algorithm combines student-teacher of-line learning and teaching agents based on sufficient activities producing by any agent in its subcultuПоказать полностьюre. The simulation studies demonstrated that the proposed algorithm is effective at rapidly generating near-optimal control agents.
Журнал: IOP Conference Series: Materials Science and Engineering
Выпуск журнала: 155
Номера страниц: 012001
Издатель: Institute of Physics Publishing