Мультиагентное описание сложного объекта по достоверной информации
Ключевые слова:
мультиагентное описание объекта, формула исчисления предикатов, неполная выводимость формулы, вычислительная сложность алгоритма
Аннотация
Рассматриваются три задачи составления описания объекта по достоверной информации, полученной несколькими агентами, причём информация, которой располагает каждый агент, не полна. В первой задаче объект характеризуется своими глобальными бинарными признаками и описывается набором значений этих признаков. Во второй и третьей задачах объект представлен как множество своих элементов, характеризуется свойствами этих элементов и отношениями между ними и описывается множеством постоянных атомарных формул исчисления предикатов. Во второй задаче предполагается, что все агенты располагают одинаковыми именами частей объекта. В третьей задаче каждый агент не знает подлинных имён частей объекта и даёт им имена произвольно. Приводятся алгоритмы решения рассмотренных задач и доказываются верхние оценки числа шагов их работы. Для второй и третьей задач приведены модельные примеры работы алгоритмов.
Литература
[1] A. V. Berezin, “Mnogoagentnaya sistema monitoringa protsessov korporativnoi seti” [Multi-agent system for monitoring the corporate network processes], Sistemy upravleniya i informatsionnye tekhnologii, vol. 55, no. 1, pp. 47‒51, 2014 (in Russian).
[2] A. Y. Bernstein and N. V. Shilov, “Mul'tiagentnaya zadacha o robotakh v prostranstve: slozhnostnoi, informatsionnyi i kriptograficheskii aspekty” [Multiagent Problem: Complexity, Information and Cryptographic Aspects], Modeling and analysis of information systems, vol. 20, no. 2, pp. 34–53, 2013 (in Russian).
[3] A. N. Bolgov, “Mul'tiagentnyi podkhod v rekonstruktsii tekstury na izobrazheniyakh” [Image texture reconstruction based on multiagent approach], Vestnik SibGAU, no. 5(57), pp. 44–50, 2014 (in Russian).
[4] E. A. Gofman, A. A. Oleynik, and S. A. Subbotin, “Agentnyi metod sinteza derev'ev reshenii” [Agent-based method for the synthesis of decision trees], Herald of the National Technical University "KhPI". Subject issue: Information Science and Modelling, no. 17, pp. 16–25, 2011 (in Russian).
[5] R. Duda and P. Hart, Raspoznavanie obrazov i analiz stsen [Pattern classification and scene analysis, Moscow: Mir, 1976 (in Russian).
[6] T. M. Kosovskaya, “Nekotorye zadachi iskusstvennogo intellekta, dopuskayushchie formalizatsiyu na yazyke ischisleniya predikatov, i otsenki chisla shagov ikh resheniya” [Some artificial intelligence problems permitting formalization by means of predicate calculus language and upper bounds of their solution steps], SPIIRAS Proceedings, no. 14, pp. 58–75, 2010 (in Russian).
[7] T. M. Kossovskaya, “Chastichnaya vyvodimost' predikatnykh formul kak sredstvo raspoznavaniya ob"ektov s nepolnoi informatsiei” [Partial deduction of predicate formula as an instrument for recognition of an object with incomplete description], Vestnik of Saint-Petersburg State University. Series 10. Applied Mathematics. Computer Science. Control Processes, vol. 1, pp. 74–84, 2009 (in Russian).
[8] T. Kosovskaya, “Distance between objects described by predicate formulas”, in Mathematics of Distances and Applications (International Book Series. Information Science and Computing. Book 25), M. Deza, M. Petitjean, and K. Markov eds., Sofia, Bulgaria: ITHEA ‒ Publisher, 2012, pp. 153–159.
[9] T. M. Kosovskaya, “Podkhod k resheniyu zadachi postroeniya mnogourovnevogo opisaniya klassov na yazyke ischisleniya predikatov” [An approach to the construction of a level description of classes by means of a predicate calculus language], SPIIRAS Proceedings, no. 3(34), pp. 204–217, 2014 (in Russian).
[10] A. A. Oleynik and S. A. Subbotin, “Reduktsiya baz nechetkikh pravil na osnove mul'tiagentnogo podkhoda” [The fuzzy rule base reduction based on multiagent approach], Herald of the National Technical University "KhPI". Subject issue: Information Science and Modelling, no 43, pp. 126–137, 2009 (in Russian).
[11] S. Rassel and P. Norvig, “Iskusstvennyi intellekt: sovremennyi podkhod“ [Artificial Intelligence: A Modern Approach], 2nd. ed., Moscow: Izdatel'skii dom “Vil'yams”, 2006 (in Russian).
[12] G. M. Tsibul'skii, “Mul'tiagentnyi podkhod k analizu izobrazhenii” [Multiagent approach to image analysis], Novosibirsk, Russia: Krasnoyarsk State Technical University, 2005 (in Russian).
[13] Ye. V. Cheremisina, Postanovka osnovnykh zadach matematicheskogo modelirovaniya pri mul'tiagentnom podkhode [Staging of main tasks of mathematical modeling at multi-agent approach], Vestnik Tambovskogo universiteta. Seriya: Estestvennye i tekhnicheskie nauki, vol. 17, no. 1, p. 174, 2012 (in Russian).
[14] A. Artikis, M. Sergot, and G. Paliouras, “A logic-based approach to activity recognition,” In Human Behavior Recognition Technologies: Intelligent Applications for Monitoring and Security, H. W. Guesgen and S. Marsland, eds., Information Science Reference, 2013, ch. 1, pp. 1–13.
[15] E. Lorini, D. Longin, and E. Mayor, “A logical analysis of responsibility attribution: emotions, individuals and collectives,” Journal of Logic and Computation, vol. 24, no. 6. pp. 1313–1339, Dec. 2014; doi:10.1093/logcom/ext072
[16] D. Porello and U. Endriss “Ontology Merging as Social Choice: Judgment Aggregation under the Open World Assumption,” Journal of Logic and Computation, vol. 24, no. 6, pp. 1229–1249, Dec. 2014; doi:10.1093/logcom/exs056
[17] Porello D. “Logics for Collective Reasoning” in Proc. of the European Conference on Social Intelligence (ECSI 2014), Nov. 2014, pp. 148–159.
[2] A. Y. Bernstein and N. V. Shilov, “Mul'tiagentnaya zadacha o robotakh v prostranstve: slozhnostnoi, informatsionnyi i kriptograficheskii aspekty” [Multiagent Problem: Complexity, Information and Cryptographic Aspects], Modeling and analysis of information systems, vol. 20, no. 2, pp. 34–53, 2013 (in Russian).
[3] A. N. Bolgov, “Mul'tiagentnyi podkhod v rekonstruktsii tekstury na izobrazheniyakh” [Image texture reconstruction based on multiagent approach], Vestnik SibGAU, no. 5(57), pp. 44–50, 2014 (in Russian).
[4] E. A. Gofman, A. A. Oleynik, and S. A. Subbotin, “Agentnyi metod sinteza derev'ev reshenii” [Agent-based method for the synthesis of decision trees], Herald of the National Technical University "KhPI". Subject issue: Information Science and Modelling, no. 17, pp. 16–25, 2011 (in Russian).
[5] R. Duda and P. Hart, Raspoznavanie obrazov i analiz stsen [Pattern classification and scene analysis, Moscow: Mir, 1976 (in Russian).
[6] T. M. Kosovskaya, “Nekotorye zadachi iskusstvennogo intellekta, dopuskayushchie formalizatsiyu na yazyke ischisleniya predikatov, i otsenki chisla shagov ikh resheniya” [Some artificial intelligence problems permitting formalization by means of predicate calculus language and upper bounds of their solution steps], SPIIRAS Proceedings, no. 14, pp. 58–75, 2010 (in Russian).
[7] T. M. Kossovskaya, “Chastichnaya vyvodimost' predikatnykh formul kak sredstvo raspoznavaniya ob"ektov s nepolnoi informatsiei” [Partial deduction of predicate formula as an instrument for recognition of an object with incomplete description], Vestnik of Saint-Petersburg State University. Series 10. Applied Mathematics. Computer Science. Control Processes, vol. 1, pp. 74–84, 2009 (in Russian).
[8] T. Kosovskaya, “Distance between objects described by predicate formulas”, in Mathematics of Distances and Applications (International Book Series. Information Science and Computing. Book 25), M. Deza, M. Petitjean, and K. Markov eds., Sofia, Bulgaria: ITHEA ‒ Publisher, 2012, pp. 153–159.
[9] T. M. Kosovskaya, “Podkhod k resheniyu zadachi postroeniya mnogourovnevogo opisaniya klassov na yazyke ischisleniya predikatov” [An approach to the construction of a level description of classes by means of a predicate calculus language], SPIIRAS Proceedings, no. 3(34), pp. 204–217, 2014 (in Russian).
[10] A. A. Oleynik and S. A. Subbotin, “Reduktsiya baz nechetkikh pravil na osnove mul'tiagentnogo podkhoda” [The fuzzy rule base reduction based on multiagent approach], Herald of the National Technical University "KhPI". Subject issue: Information Science and Modelling, no 43, pp. 126–137, 2009 (in Russian).
[11] S. Rassel and P. Norvig, “Iskusstvennyi intellekt: sovremennyi podkhod“ [Artificial Intelligence: A Modern Approach], 2nd. ed., Moscow: Izdatel'skii dom “Vil'yams”, 2006 (in Russian).
[12] G. M. Tsibul'skii, “Mul'tiagentnyi podkhod k analizu izobrazhenii” [Multiagent approach to image analysis], Novosibirsk, Russia: Krasnoyarsk State Technical University, 2005 (in Russian).
[13] Ye. V. Cheremisina, Postanovka osnovnykh zadach matematicheskogo modelirovaniya pri mul'tiagentnom podkhode [Staging of main tasks of mathematical modeling at multi-agent approach], Vestnik Tambovskogo universiteta. Seriya: Estestvennye i tekhnicheskie nauki, vol. 17, no. 1, p. 174, 2012 (in Russian).
[14] A. Artikis, M. Sergot, and G. Paliouras, “A logic-based approach to activity recognition,” In Human Behavior Recognition Technologies: Intelligent Applications for Monitoring and Security, H. W. Guesgen and S. Marsland, eds., Information Science Reference, 2013, ch. 1, pp. 1–13.
[15] E. Lorini, D. Longin, and E. Mayor, “A logical analysis of responsibility attribution: emotions, individuals and collectives,” Journal of Logic and Computation, vol. 24, no. 6. pp. 1313–1339, Dec. 2014; doi:10.1093/logcom/ext072
[16] D. Porello and U. Endriss “Ontology Merging as Social Choice: Judgment Aggregation under the Open World Assumption,” Journal of Logic and Computation, vol. 24, no. 6, pp. 1229–1249, Dec. 2014; doi:10.1093/logcom/exs056
[17] Porello D. “Logics for Collective Reasoning” in Proc. of the European Conference on Social Intelligence (ECSI 2014), Nov. 2014, pp. 148–159.
Опубликован
2017-06-04
Как цитировать
Косовская, Т. М. (2017). Мультиагентное описание сложного объекта по достоверной информации. Компьютерные инструменты в образовании, (4), 5-18. извлечено от http://cte.eltech.ru/ojs/index.php/kio/article/view/1402
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