<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<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">vguit</journal-id><journal-title-group><journal-title xml:lang="ru">Вестник Воронежского государственного университета инженерных технологий</journal-title><trans-title-group xml:lang="en"><trans-title>Proceedings of the Voronezh State University of Engineering Technologies</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2226-910X</issn><issn pub-type="epub">2310-1202</issn><publisher><publisher-name>VSUET</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.20914/2310-1202-2019-3-339-359</article-id><article-id custom-type="elpub" pub-id-type="custom">vguit-2333</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>Экономика и управление</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>Economics and Management</subject></subj-group></article-categories><title-group><article-title>Применение социального моделирования с использованием агент-ориентированного подхода в приложении к научно-техническому развитию, реализации НИОКР и поддержанию инновационного потенциала</article-title><trans-title-group xml:lang="en"><trans-title>Application of social modeling using agent based approach in scientific and technical development, implementation of R&amp;D and maintenance of innovative potential</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-5714-2358</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Абрамов</surname><given-names>В. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Abramov</surname><given-names>V. I.</given-names></name></name-alternatives><bio xml:lang="ru"><p>к.э.н., старший научный сотрудник, лаборатория компьютерного моделирования социально-экономических процессов, Нахимовский проспект, 47, Москва, 117418, Россия</p></bio><bio xml:lang="en"><p>Cand. Sci. (Econ.), senior researcher, laboratory of computer modeling of social and economic processes, Nakhimovsky prospect, 47, Moscow, 117418, Russia</p></bio><email xlink:type="simple">wladi-mir.abramow@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-8300-7061</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Кудинов</surname><given-names>А. Н.</given-names></name><name name-style="western" xml:lang="en"><surname>Kudinov</surname><given-names>A. N.</given-names></name></name-alternatives><bio xml:lang="ru"><p>к.ф.-м.н., старший научный сотрудник, лаборатория компьютерного моделирования социально-экономических процессов, Нахимовский проспект, 47, Москва, 117418, Россия</p></bio><bio xml:lang="en"><p>Cand. Sci. (Phys.–Math.), senior researcher, laboratory of computer modeling of social and economic processes, Nakhimovsky prospect, 47, Moscow, 117418, Russia</p></bio><email xlink:type="simple">a.kudinov13@gmail.com</email><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-8304-9448</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Евдокимов</surname><given-names>Д. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Evdokimov</surname><given-names>D. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>аспирант, младший научный сотрудник, лаборатория компьютерного моделирования социально-экономических процессов, Нахимовский проспект, 47, Москва, 117418, Россия</p></bio><bio xml:lang="en"><p>graduate student, junior researcher, laboratory of computer modeling of social and economic processes, Nakhimovsky prospect, 47, Moscow, 117418, Russia</p></bio><email xlink:type="simple">dimaevd15@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Центральный экономико-математический институт Российской академии наук</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Central Economics and Mathematics Institute, RAS</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>Центральный экономико-математический институт Российской академии наук,)</institution><country>Russian Federation</country></aff><aff xml:lang="en"><institution>Central Economics and Mathematics Institute, RAS</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2019</year></pub-date><pub-date pub-type="epub"><day>18</day><month>11</month><year>2019</year></pub-date><volume>81</volume><issue>3</issue><fpage>339</fpage><lpage>359</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Абрамов В.И., Кудинов А.Н., Евдокимов Д.С., 2019</copyright-statement><copyright-year>2019</copyright-year><copyright-holder xml:lang="ru">Абрамов В.И., Кудинов А.Н., Евдокимов Д.С.</copyright-holder><copyright-holder xml:lang="en">Abramov V.I., Kudinov A.N., Evdokimov D.S.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" 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://www.vestnik-vsuet.ru/vguit/article/view/2333">https://www.vestnik-vsuet.ru/vguit/article/view/2333</self-uri><abstract><p>Агент-ориентированные модели (АОМ) и мультиагентные системы (МАС) могут использоваться для решения проблем во многих областях исследований – от естественных наук и информатики до экономики и социальных наук. Многие природные и социальные явления могут быть представлены в виде сложной имитации. Таким образом, с течением времени агентные модели и мультиагентные системы оказались действительно мощным инструментом в таких сферах, как экономика и торговля, здравоохранение, городское планирование и социальные науки. Кроме того, мультиагентная система может быть представлена как искусственное общество, аналогичное человеческому и состоящее из сущностей с характеристиками, сходными с человеческими, например, с точки зрения автономии и интеллекта. В основе АОМ лежит принцип объективной ориентированности, а также эволюции (обучения) агентов в процессе моделирования различных вариантов предлагаемых событий. Несмотря на всю кажущуюся простоту правил взаимодействия между агентами, получаемые результаты, как правило, неочевидны, а также вполне осмысленны и содержательны. АОМ могут быть разработаны как на микроуровне, так и представлять собой модели с множеством агентов на макроуровне. О концепции мультиагентных систем, которые сразу приобрели сторонников и поддержку как в научных кругах, так и индустриальных сообществах, впервые заговорили в середине 1980-х годов. За последние 30 лет методология создания МАС постоянно совершенствовалась: активно развивались технологии и инструменты для ее продвижения и использования при управлении крупномасштабными сетевыми структурами (такими, как оборонные комплексы, энергетика, здравоохранение, транспорт, логистика, управление городским хозяйством, коллективная робототехника и пр.). Область применения МАС обширна. Анализ реализованных МАС доказывает, что в настоящее время инструмент является самой передовой технологией для управления любыми объектами, построенными на принципах самоорганизации. Однако, несмотря на всю очевидность позитивных перспектив внедрения технологии АОМ, число примеров ее успешного применения на сегодняшний день мало. В связи с этим, для дальнейшего распространения инструментария особенно актуально создание новых площадок для обсуждения международного опыта и совершенствования подхода к имитационному моделированию в целом. Создание открытого консорциума по агент-ориентированному моделированию, а также работа по содействию в разработке и коммуникации, распространению результатов исследований, осуществлению образовательной деятельности в совокупности позволят внести вклад в развитие агент-ориентированного моделирования. Проведенные в работе анализ и обзор существующей методологии социального моделирования с использованием агент-ориентированного подхода в приложении к научно-техническому развитию, реализации НИОКР и поддержанию инновационного потенциала, показали, что модели, отличающиеся сложными многоуровневыми процессами и взаимодействиями агентов, обладают более емкими программными конструкциями, которые зависят в большей степени от «тонкой» настройки самих агентов. Такие модели могут содержать и использовать объемный набор данных и в области экономических исследований, как правило, направлены на анализ и прогнозирование различных социально-экономических процессов на макроуровне.</p></abstract><trans-abstract xml:lang="en"><p>Agent based models (ABM) and multiagent systems (MAS) can be used to solve problems in many fields of research - from natural and computer to economics and social sciences. Many natural and social phenomena can be represented in form of complex simulations so over time agent models and multi-agent systems have proven to be a really powerful tool in areas such as economics and trade, health, urban planning and social sciences. In addition multi-agent systems can be represented as an artificial society similar to a human one and consisting of entities with characteristics similar to human ones, for example in terms of autonomy and intelligence. ABM are based on the principle of objective orientation as well as the evolution (training) of agents in the process of modeling various variants of the proposed events. Despite the apparent simplicity of the rules of interaction between agents the results are usually non-obvious and quite meaningful. ABM can be developed both at the micro level and represent models with multiple agents at the macro level. The concept of multi-agent systems which immediately gained followers and support in both scientific circles and industrial communities, first started talking in the mid-1980s. Over the past thirty years, the methodology of IAU creation has been constantly improved: technologies and tools for its promotion and use in the management of large-scale network structures (such as defense systems, energy, health, transport, logistics, urban management, collective robotics, etc.) have been actively developed. The scope of application of MAS is very wide. The analysis of implemented MAS proves that currently the tool is the most advanced technology for managing any objects built on the principles of self-organization. However, despite all the evidence of positive prospects for the introduction of AOM technology the number of examples of its successful application to date is small. In this regard creation of new platforms for discussion of international experience and improvement of the approach to simulation modeling in general is especially important for further dissemination of AMB and MAS. Creation of an open consortium for agent-oriented modeling as well as promotion of development, communication and dissemination of research results as well as implementation of educational activities together will contribute to the development of agent based modeling. The analysis and review of existing methodology of social modeling with use of agent based approach in the application to scientific and technical development, implementation of R&amp;D and maintenance of innovative potential showed that models characterized by complex multi-level processes and interactions of agents have more capacious software structures which depend more on the "fine" tuning of the agents themselves. Such models can contain and use a voluminous set of data, and in the field of economic research tend to focus on the analysis and forecasting of various socio-economic processes at the macro level.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>агент-ориентированное моделирование</kwd><kwd>имитационное моделирование</kwd><kwd>мультиагентные системы</kwd><kwd>научно-технический прогресс</kwd><kwd>НИОКР</kwd><kwd>R&amp;D</kwd><kwd>S&amp;D</kwd><kwd>инновационные разработки</kwd></kwd-group><kwd-group xml:lang="en"><kwd>agent based modeling</kwd><kwd>simulation modeling</kwd><kwd>multi-agent systems</kwd><kwd>scientific and technological progress</kwd><kwd>R&amp;D</kwd><kwd>S&amp;D</kwd><kwd>innovation</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Исследование выполнено по программе фундаментальных исследований РАН «Многофакторные вызовы и риски перехода к новому этапу научно-технологического и экономического развития России: фундаментальные и прикладные проблемы»</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Абрамов В.И., Евдокимов Д.С. Разработка комплексаагент-ориентированных моделей системы государственных закупок стран Евразийского континента // Проблемы теории и практики управления. 2019. С. 15–23.</mixed-citation><mixed-citation xml:lang="en">Abramov V.I., Evdokimov D.S. Development of a complex of agent-based models of the public procurement system of the countries of the Eurasian continent. Problems of management theory and practice. 2019. pp. 15–23. (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Дьячук П.П., Дьячук П.П., Карабалыков С.А., Шадрин И.В. Диагностика неустойчивых когнитивных состояний активных агентов // Нейроинформатика2016: сборник научных трудов: в 3 частях. М.: Национальный исследовательский ядерный университет "МИФИ", 2016. С. 259–270.</mixed-citation><mixed-citation xml:lang="en">Dyachuk P.P., Dyachuk P.P., Karabalykov S.A., Shadrin I.V. Diagnosis of unstable cognitive states of active agents. Neuroinformatics 2016: collection of scientific papers: in 3 parts. Moscow, National Research Nuclear University MEPhI, 2016. pp. 259–270. (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Когаловский М.Р., Калиниченко Л.А. Концептуальное и онтологическое моделирование в информационных системах // Программирование. 2009. Т. 35. № 5. С. 3–25.</mixed-citation><mixed-citation xml:lang="en">Kogalovsky M.R., Kalinichenko L.A. Conceptual and ontological modeling in information systems. Programming. 2009. vol. 35. no. 5. pp. 3–25. (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Макаров В.Л., Бахтизин А.Р. Социальное моделирование – новый компьютерный прорыв. Агенториентированные модели. М.: Экономика, 2013. 295 с.</mixed-citation><mixed-citation xml:lang="en">Makarov V.L., Bakhtizin A.R. Social modeling is a new computer breakthrough. Agent-based models. Moscow, Economics, 2013. 295 p. (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Макаров В.Л., Бахтизин А.Р., Сушко Е.Д., Абрамов В.И. Компьютерноемоделирование в управлении экономикой (методологическая основа длястратегического планирования) // Государственный аудит. Право. Экономика. 2017. № 3.</mixed-citation><mixed-citation xml:lang="en">Makarov V.L., Bakhtizin A.R., Sushko E.D., Abramov V.I. Computer simulation in economic management (methodological basis for strategic planning). State audit. Right. Economy. 2017. no. 3. (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Тарасов В.Б. От многоагентных систем к интеллектуальным организациям: философия, психология, информатика. М.: Эдиториал УРСС, 2002. 352 с.</mixed-citation><mixed-citation xml:lang="en">Tarasov V.B. From multi-agent systems to intelligent organizations: philosophy, psychology, computer science. Moscow, Editorial URSS, 2002. 352 p. (in Russian).</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Ahrweiler P., Schilperoord M., Pyka A., Gilbert N. Modelling Research Policy: Ex-Ante Evaluation of Complex Policy Instruments // Journal of Artificial Societies and Social Simulation. 2015. V. 18 (4). № 5. doi: 10.18564/jasss.2927</mixed-citation><mixed-citation xml:lang="en">Ahrweiler P., Schilperoord M., Pyka A., Gilbert N. Modelling Research Policy: Ex-Ante Evaluation of Complex Policy Instruments. Journal of Artificial Societies and Social Simulation. 2015. vol. 18 (4). no. 5. doi: 10.18564/jasss.2927</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Angelini A., Cerulli G., Cecconi F., Miceli A. et al. R&amp;D Subsidization Effect and Network Centralization: Evidence from an Agent-Based Micro-Policy Simulation // Journal of Artificial Societies and Social Simulation. 2017. V. 20 (4). № 4. doi: 10.18564/jasss.3494</mixed-citation><mixed-citation xml:lang="en">Angelini A., Cerulli G., Cecconi F., Miceli A. et al. R&amp;D Subsidization Effect and Network Centralization: Evidence from an Agent-Based Micro-Policy Simulation. Journal of Artificial Societies and Social Simulation. 2017. vol. 20 (4). no. 4. doi: 10.18564/jasss.3494</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Antonelli С., Ferrarisb G. Innovation as an Emerging System Property: An Agent Based Simulation Model // Journal of Artificial Societies and Social Simulation. 2011. V. 14 (2). № 1.</mixed-citation><mixed-citation xml:lang="en">Antonelli С., Ferrarisb G. Innovation as an Emerging System Property: An Agent Based Simulation Model. Journal of Artificial Societies and Social Simulation. 2011. vol. 14 (2). no. 1.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Bousquet F., Tr?buil G., Hardy B. Companion Modeling and Multi-Agent Systems for Integrated Natural Resource Management in Asia Los Baсos (Philippines). International Rice Research Institute. 2005. 360 p.</mixed-citation><mixed-citation xml:lang="en">Bousquet F., Tr?buil G., Hardy B. Companion Modeling and Multi-Agent Systems for Integrated Natural Resource Management in Asia Los Baсos (Philippines). International Rice Research Institute. 2005. 360 p.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Bianchi F., Grimaldo F., Bravo G., Squazzoni F. The peer review game: an agent-based model of scientists facing resource constraints and institutional pressures. Springer, 2018. doi: 10.1007/s11192–018–2825–4</mixed-citation><mixed-citation xml:lang="en">Bianchi F., Grimaldo F., Bravo G., Squazzoni F. The peer review game: an agent-based model of scientists facing resource constraints and institutional pressures. Springer, 2018. doi: 10.1007/s11192–018–2825–4</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Brinner R. The 1985 DRI Model: An Overview, in Data Resources Review of the US Economy. Lexington, 1985.</mixed-citation><mixed-citation xml:lang="en">Brinner R. The 1985 DRI Model: An Overview, in Data Resources Review of the US Economy. Lexington, 1985.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Epstein J., Axtell R. Growing Artificial Societies: Social Science From the Bottom Up. Washington, D.C.: MIT Press / Brookings Institution, 1996.</mixed-citation><mixed-citation xml:lang="en">Epstein J., Axtell R. Growing Artificial Societies: Social Science From the Bottom Up. Washington, D.C., MIT Press / Brookings Institution, 1996.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Goldspink C. Methodological Implications Of Complex Systems Approaches to Sociality: Simulation as a foundation for knowledge // Journal of Artificial Societies and Social Simulation. 2002. V. 5. № 1.</mixed-citation><mixed-citation xml:lang="en">Goldspink C. Methodological Implications Of Complex Systems Approaches to Sociality: Simulation as a foundation for knowledge. Journal of Artificial Societies and Social Simulation. 2002. vol. 5. no. 1.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Goto Y., Takeuchi I., Kakumoto S. Integrated earthquake disaster simulation systems for the highlynetworked information society // Proc. of the 13thWorld Conference on Earthquake Engineering. Vancouver, 2004. P. 2793. URL: http://www.iitk.ac.in/ nicee/wcee/article/13_2793.pdf</mixed-citation><mixed-citation xml:lang="en">Goto Y., Takeuchi I., Kakumoto S. Integrated earthquake disaster simulation systems for the highlynetworked information society. Proc. of the 13th World Conference on Earthquake Engineering. Vancouver, 2004. pp. 2793. Available at: http://www.iitk.ac.in/ nicee/wcee/article/13_2793.pdf</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Gilbert N., Pyka A., Ahrweiler P. Innovation Networks – A Simulation Approach // Journal of Artificial Societies and Social Simulation. 2001. V. 4. № 3.</mixed-citation><mixed-citation xml:lang="en">Gilbert N., Pyka A., Ahrweiler P. Innovation Networks – A Simulation Approach. Journal of Artificial Societies and Social Simulation. 2001. vol. 4. no. 3.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Haag G., Liedl P. Modelling and Simulating Innovation Behaviour within Micro-based Correlated Decision Processes // Journal of Artificial Societies and Social Simulation. 2001</mixed-citation><mixed-citation xml:lang="en">Haag G., Liedl P. Modelling and Simulating Innovation Behaviour within Micro-based Correlated Decision Processes. Journal of Artificial Societies and Social Simulation. 2001.</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Haydari S., Smead R. Does Longer Copyright Protection Help or Hurt Scientific Knowledge Creation? // Journal of Artificial Societies and Social Simulation. 2015. V. 18 (2). № 23. doi: 10.18564/jasss.2720</mixed-citation><mixed-citation xml:lang="en">Haydari S., Smead R. Does Longer Copyright Protection Help or Hurt Scientific Knowledge Creation? Journal of Artificial Societies and Social Simulation. 2015. vol. 18 (2). no. 23. doi: 10.18564/jasss.2720</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Janssen A., Alessa L., Barton M., Bergin S. et al. Towards a Community Framework for Agent-Based Modelling // Journal of Artificial Societies and Social Simulation. 2008</mixed-citation><mixed-citation xml:lang="en">Janssen A., Alessa L., Barton M., Bergin S. et al. Towards a Community Framework for Agent-Based Modelling. Journal of Artificial Societies and Social Simulation. 2008</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Kravari K., Bassiliades N. A Survey of Agent Platforms // Journal of Artificial Societies and Social Simulation. 2015. doi: 10.18564/jasss.2661</mixed-citation><mixed-citation xml:lang="en">Kravari K., Bassiliades N. A Survey of Agent Platforms. Journal of Artificial Societies and Social Simulation. 2015. doi: 10.18564/jasss.2661</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Lee S. Simulation of the Long-Term Effects of Decentralized and Adaptive Investments in Cross-Agency Interoperable and Standard IT Systems // Journal of Artificial Societies and Social Simulation. 2010. V. 13 (2). № 3. doi: 10.18564/jasss.1488</mixed-citation><mixed-citation xml:lang="en">Lee S. Simulation of the Long-Term Effects of Decentralized and Adaptive Investments in Cross-Agency Interoperable and Standard IT Systems. Journal of Artificial Societies and Social Simulation. 2010. vol. 13 (2). no. 3. doi: 10.18564/jasss.1488</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Law A.M., Kelton W.D. Simulation Modeling and Analysis. New York: McGraw-Hill, 1991.</mixed-citation><mixed-citation xml:lang="en">Law A.M., Kelton W.D. Simulation Modeling and Analysis. New York: McGraw-Hill, 1991.</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Monticino M.G., Brooks E., Cogdill T., Acevedo M. et al. Applying a Multi-Agent Model to Evaluate Effects of Development Proposals and Growth Management Policies on Suburban Sprawl // Proc. of the International Environmental Modelling and Software Society, Summit on Environmental Modelling and Software. Burlington, 2006. URL: http://www.math.unt.edu/~monticino/papers/mult-agent_development.pdf</mixed-citation><mixed-citation xml:lang="en">Monticino M.G., Brooks E., Cogdill T., Acevedo M. et al. Applying a Multi-Agent Model to Evaluate Effects of Development Proposals and Growth Management Policies on Suburban Sprawl. Proc. of the International Environmental Modelling and Software Society, Summit on Environmental Modelling and Software. Burlington, 2006. Available at: http://www.math.unt.edu/~monticino/papers/mult-agent_development.pdf</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Neves F., Campos P., Silva S. Innovation and Employment: An Agent-Based Approach // Journal of Artificial Societies and Social Simulation. 2019. V. 22 (1). № 8. doi: 10.18564/jasss.3933</mixed-citation><mixed-citation xml:lang="en">Neves F., Campos P., Silva S. Innovation and Employment: An Agent-Based Approach. Journal of Artificial Societies and Social Simulation. 2019. vol. 22 (1). no. 8. doi: 10.18564/jasss.3933</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Pajares J., Hern?ndez-Iglesias C., L?pez-Paredes A. Modelling Learning and R&amp;D in Innovative Environments: a Cognitive Multi-Agent Approach // Journal of Artificial Societies and Social Simulation. 2004. V. 7. № 2.</mixed-citation><mixed-citation xml:lang="en">Pajares J., Hern?ndez-Iglesias C., L?pez-Paredes A. Modelling Learning and R&amp;D in Innovative Environments: a Cognitive Multi-Agent Approach. Journal of Artificial Societies and Social Simulation. 2004. vol. 7. no. 2.</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Pajares J., L?pez A., Hern?ndez C. Industry as an Organisation of Agents: Innovation and R&amp;D Management // Journal of Artificial Societies and Social Simulation. 2003. V. 6. № 2.</mixed-citation><mixed-citation xml:lang="en">Pajares J., L?pez A., Hern?ndez C. Industry as an Organisation of Agents: Innovation and R&amp;D Management. Journal of Artificial Societies and Social Simulation. 2003. vol. 6. no. 2.</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Parinov S., Neylon C. Science as a Social System and Virtual Research Environment // Journal of Artificial Societies and Social Simulation. 2011. V. 14 (4). № 10. doi: 10.18564/jasss.1835</mixed-citation><mixed-citation xml:lang="en">Parinov S., Neylon C. Science as a Social System and Virtual Research Environment. Journal of Artificial Societies and Social Simulation. 2011. vol. 14 (4). no. 10. doi: 10.18564/jasss.1835</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Sobkowicz P. Innovation Suppression and Clique Evolution in Peer-Review-Based, Competitive Research Funding Systems: An Agent-Based Model // Journal of Artificial Societies and Social Simulation. 2015. V. 18 (2). № 13. doi: 10.18564/jasss.2750</mixed-citation><mixed-citation xml:lang="en">Sobkowicz P. Innovation Suppression and Clique Evolution in Peer-Review-Based, Competitive Research Funding Systems: An Agent-Based Model. Journal of Artificial Societies and Social Simulation. 2015. vol. 18 (2). no. 13. doi: 10.18564/jasss.2750</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Schulze J., M?ller B., Groeneveld J., Grimm V. Agent-Based Modelling of Social-Ecological Systems: Achievements, Challenges, and a Way Forward // Journal of Artificial Societies and Social Simulation. 2017. V. 20 (2). № 8. doi: 10.18564/jasss.3423</mixed-citation><mixed-citation xml:lang="en">Schulze J., M?ller B., Groeneveld J., Grimm V. Agent-Based Modelling of Social-Ecological Systems: Achievements, Challenges, and a Way Forward. Journal of Artificial Societies and Social Simulation. 2017. vol. 20 (2). no. 8. doi: 10.18564/jasss.3423</mixed-citation></citation-alternatives></ref><ref id="cit30"><label>30</label><citation-alternatives><mixed-citation xml:lang="ru">Tsekeris T., Vogiatzoglou K. Multi-Regional Agent-Based Economic Model of Household and Firm Location and Transport Decisions // Proc. of the 10th STRC Swiss Transport Research Conference. Monte Veritа, 2010. URL: http://www.strc.ch/conferences/2010/Tsekeris.pdf</mixed-citation><mixed-citation xml:lang="en">Tsekeris T., Vogiatzoglou K. Multi-Regional Agent-Based Economic Model of Household and Firm Location and Transport Decisions. Proc. of the 10th STRC Swiss Transport Research Conference. Monte Veritа, 2010. Available at: http://www.strc.ch/conferences/2010/Tsekeris.pdf</mixed-citation></citation-alternatives></ref><ref id="cit31"><label>31</label><citation-alternatives><mixed-citation xml:lang="ru">Yilmaz L. Toward Multi-Level, Multi-Theoretical Model Portfolios for Scientific Enterprise Workforce Dynamics // Journal of Artificial Societies and Social Simulation. 2011. V. 14 (4). № 2. doi: 10.18564/jasss.1853</mixed-citation><mixed-citation xml:lang="en">Yilmaz L. Toward Multi-Level, Multi-Theoretical Model Portfolios for Scientific Enterprise Workforce Dynamics. Journal of Artificial Societies and Social Simulation. 2011. vol. 14 (4). no. 2. doi: 10.18564/jasss.1853</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
