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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">vavilov</journal-id><journal-title-group><journal-title xml:lang="ru">Вавиловский журнал генетики и селекции</journal-title><trans-title-group xml:lang="en"><trans-title>Vavilov Journal of Genetics and Breeding</trans-title></trans-title-group></journal-title-group><issn pub-type="epub">2500-3259</issn><publisher><publisher-name>Institute of Cytology and Genetics of Siberian Branch of the RAS</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.18699/VJGB-22-94</article-id><article-id custom-type="elpub" pub-id-type="custom">vavilov-3579</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ЭВОЛЮЦИОННАЯ КОМПЬЮТЕРНАЯ БИОЛОГИЯ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>EVOLUTIONARY COMPUTATIONAL BIOLOGY</subject></subj-group></article-categories><title-group><article-title>Программная система на основе 3D симулятора  для моделирования эволюции в популяции организмов, обладающих зрительной системой</article-title><trans-title-group xml:lang="en"><trans-title>A software system for modeling evolution  in a population of organisms with vision,  interacting with each other in 3D simulator</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Девятериков</surname><given-names>А. П.</given-names></name><name name-style="western" xml:lang="en"><surname>Devyaterikov</surname><given-names>A. P.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Новосибирск</p></bio><bio xml:lang="en"><p>Novosibirsk</p></bio><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-1108-1486</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Пальянов</surname><given-names>А. Ю.</given-names></name><name name-style="western" xml:lang="en"><surname>Palyanov</surname><given-names>A. Yu.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Новосибирск</p></bio><bio xml:lang="en"><p>Novosibirsk</p></bio><email xlink:type="simple">palyanov@iis.nsk.su</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">Институт систем информатики им. А.П. Ершова Сибирского отделения Российской академии наук; Новосибирский национальный исследовательский государственный университет<country>Россия</country></aff><aff xml:lang="en">A.P. Ershov Institute of Informatics Systems of the Siberian Branch of the Russian Academy of Sciences; Novosibirsk State University<country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru">Институт систем информатики им. А.П. Ершова Сибирского отделения Российской академии наук<country>Россия</country></aff><aff xml:lang="en">A.P. Ershov Institute of Informatics Systems of the Siberian Branch of the Russian Academy of Sciences<country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2022</year></pub-date><pub-date pub-type="epub"><day>04</day><month>01</month><year>2023</year></pub-date><volume>26</volume><issue>8</issue><fpage>780</fpage><lpage>786</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Девятериков А.П., Пальянов А.Ю., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Девятериков А.П., Пальянов А.Ю.</copyright-holder><copyright-holder xml:lang="en">Devyaterikov A.P., Palyanov A.Y.</copyright-holder><license license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://vavilov.elpub.ru/jour/article/view/3579">https://vavilov.elpub.ru/jour/article/view/3579</self-uri><abstract><p>Создание компьютерных моделей, имитирующих работу нервных систем живых организмов с учетом их морфологии и электрофизиологии, – один из важных и перспективных разделов вычислительной нейробиологии. При наличии возможности стремятся моделировать не только нервную систему, но и тело, мышцы, сенсорные системы и виртуальную трехмерную физическую среду, в которой можно наблюдать поведение организма и которая обеспечивает его сенсорные системы адекватными потоками данных, изменяющимися в ответ на движение организма. Для системы из сотен или тысяч нейронов еще можно надеяться задать необходимые параметры и получить функционирование нервной системы, более-менее сходное с таковым для живого организма, как, например, в недавней работе по моделированию головастика Xenopus. Однако наибольший интерес, как практический, так и фундаментальный, представляют организмы, обладающие зрением, более сложной нервной системой и, соответственно, значительно более развитыми когнитивными способностями. Определить структуру и параметры нервных систем таких организмов представляется исключительно сложной задачей. Более того, они изменяются с течением времени, в том числе под воздействием воспринимаемых ими потоков сенсорных сигналов и полученного жизненного опыта, включая последствия собственных действий при тех или иных обстоятельствах. Зная структуру нервной системы и число образующих ее нервных клеток хотя бы приблизительно, можно попытаться оптимизировать начальные параметры модели посредством искусственной эволюции, в процессе которой виртуальные организмы будут взаимодействовать и выживать – каждый под управлением собственной версии нервной системы. Помимо этого, эволюционировать могут и правила, по которым мозг изменяется на протяжении жизни организма. Данная работа посвящена созданию нейроэволюционного симулятора, способного осуществлять одновременное функционирование виртуальных организмов, обладающих зрительной системой, которые взаимодействуют между собой. Приведены расчеты, показывающие, сколько вычислительных ресурсов требуется для работы моделей физического тела организма, нервной системы и виртуальной среды обитания, а также определена производительность симулятора на современной настольной вычислительной системе в зависимости от числа одновременно моделируемых организмов.</p></abstract><trans-abstract xml:lang="en"><p>Development of computer models imitating the work of the nervous systems of living organisms, taking into account their morphology and electrophysiology, is one of the important and promising branches of computational neurobiology. It is often sought to model not only the nervous system, but also the body, muscles, sensory systems, and a virtual three-dimensional physical environment in which the behavior of an organism can be observed and which provides its sensory systems with adequate data streams that change in response to the movement of the organism. For a system of hundreds or thousands of neurons, one can still hope to determine the necessary parameters and get the functioning of the nervous system more or less similar to that of a living organism – as, for example, in a recent work on the modeling of the Xenopus tadpole. However, of greatest interest, both practical and fundamental, are organisms that have vision, a more complex nervous system, and, accordingly, significantly more advanced cognitive abilities. Determining the structure and parameters of the nervous systems of such organisms is an extremely difficult task. Moreover, at the cellular level they change over time, these including changes under the influence of the streams of sensory signals they perceive and the life experience gained, including the consequences of their own actions under certain circumstances. Knowing the structure of the nervous system and the number of nerve cells forming it, at least approximately, one can try to optimize the initial parameters of the model through artificial evolution, during which virtual organisms will interact and survive, each under the control of its own version of the nervous system. In addition, in principle, the rules by which the brain changes during the life of the organism can also evolve. This work is devoted to the development of a neuroevolutionary simulator capable of performing simultaneous functioning of virtual organisms that have a visual system and are able to interact with each other. The amount of computational resources required for the operation of models of the physical body of an organism, the nervous system and the virtual environment was estimated, and the performance of the simulator on a modern desktop computing system was determined depending on the number of simultaneously simulated organisms.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>нервная система</kwd><kwd>зрительная система</kwd><kwd>виртуальный организм</kwd><kwd>популяция</kwd><kwd>компьютерное моделирование</kwd><kwd>нейроэволюционный симулятор</kwd></kwd-group><kwd-group xml:lang="en"><kwd>nervous system</kwd><kwd>vision system</kwd><kwd>virtual organism</kwd><kwd>population</kwd><kwd>computational modeling</kwd><kwd>neuroevolution simulator</kwd></kwd-group><funding-group xml:lang="en"><funding-statement>The study was performed according to the Russian Federation Government research assignment for A.P. 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