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2019 | OriginalPaper | Chapter

Modeling the Structure of MIMO-Agents and Their Interactions

Author : Liudmila Yu. Zhilyakova

Published in: Artificial Intelligence

Publisher: Springer International Publishing

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Abstract

The paper describes a formal model of social network users who have definite sets of interests in different subjects. The users are represented by heterogeneous agents with multiple inputs of different types and multiple outputs of different types (MIMO-agents). Each type corresponds to one of the interests of users. Agents have a cumulative activation function, depending on current external influence from their neighbors and previous network states. If the value of this function at a certain time step is above a specified threshold, the agent becomes active according to one of the types. The choice of this type depends both on his internal structure (personal preferences specified by a vector) and on the proportion of active neighbors of every type. A network of such agents is capable of generating various kinds of complex activity patterns. We consider several examples of activity propagation and show the dependence of stable activity patterns on the parameters of agents. Networks of MIMO-agents with similar properties can be used not only to describe the interaction of users of social networks, but also in modeling the transfer of heterogeneous information in telecommunications networks.

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Literature
2.
go back to reference Baronchelli, A., Ferrer-i-Cancho, R., Pastor-Satorras, R., Chater, N., Christiansen, M.H.: Networks in cognitive science. Trends Cogn. Sci. 17(7), 2013 (2013)CrossRef Baronchelli, A., Ferrer-i-Cancho, R., Pastor-Satorras, R., Chater, N., Christiansen, M.H.: Networks in cognitive science. Trends Cogn. Sci. 17(7), 2013 (2013)CrossRef
3.
go back to reference Bullmore, E., Sporns, O.: Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10, 186–198 (2009)CrossRef Bullmore, E., Sporns, O.: Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10, 186–198 (2009)CrossRef
4.
go back to reference Kempe, D., Kleinberg, J., Tardos, E.: Maximizing the spread of influence through a social network. In: Proceedings of the 9-th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 137–146 (2003) Kempe, D., Kleinberg, J., Tardos, E.: Maximizing the spread of influence through a social network. In: Proceedings of the 9-th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 137–146 (2003)
6.
go back to reference Gubanov, D.A., Chkhartishvili, A.G.: Models of information opinion and trust control of social network members. In: Proceedings of the 18th IFAC World Congress, 2011 World Congress, pp. 1991–1996. International Federation of Automatic Control (IFAC), Milano (2011) Gubanov, D.A., Chkhartishvili, A.G.: Models of information opinion and trust control of social network members. In: Proceedings of the 18th IFAC World Congress, 2011 World Congress, pp. 1991–1996. International Federation of Automatic Control (IFAC), Milano (2011)
7.
go back to reference Zhilyakova, L.Yu.: Network model of spreading of several activity types among complex agents and ITS applications. Ontol. Design. 5(3(17)), 278–296 (2015). (in Russian)CrossRef Zhilyakova, L.Yu.: Network model of spreading of several activity types among complex agents and ITS applications. Ontol. Design. 5(3(17)), 278–296 (2015). (in Russian)CrossRef
8.
go back to reference Zhilyakova, L., Gubanov, D.: Double-threshold model of the activity spreading in a social network. The case of two types of opposite activities. In: Proceedings of the 11th IEEE International Conference on Application of Information and Communication Technologies, AICT 2017, vol. 2, pp. 267–270 (2017) Zhilyakova, L., Gubanov, D.: Double-threshold model of the activity spreading in a social network. The case of two types of opposite activities. In: Proceedings of the 11th IEEE International Conference on Application of Information and Communication Technologies, AICT 2017, vol. 2, pp. 267–270 (2017)
9.
go back to reference Bazenkov, N., et al.: Discrete modeling of neuronal interactions in multi-transmitter networks. Sci. Tech. Inf. Process. 45(5), 283–296 (2018)CrossRef Bazenkov, N., et al.: Discrete modeling of neuronal interactions in multi-transmitter networks. Sci. Tech. Inf. Process. 45(5), 283–296 (2018)CrossRef
10.
go back to reference Kuznetsov, O.P., Bazenkov, N.I., Boldyshev, B.A., Zhilyakova, L.Yu., Kulivets, S.G., Chistopolsky, I.A.: An asynchronous discrete model of chemical interactions in simple neuronal systems. Sci. Tech. Inf. Process. 45(6), 375–389 (2018)CrossRef Kuznetsov, O.P., Bazenkov, N.I., Boldyshev, B.A., Zhilyakova, L.Yu., Kulivets, S.G., Chistopolsky, I.A.: An asynchronous discrete model of chemical interactions in simple neuronal systems. Sci. Tech. Inf. Process. 45(6), 375–389 (2018)CrossRef
11.
go back to reference Zhu, L., Chen, X., Chen, Z., Hill, D.J.: Output synchronization of linear MIMO heterogeneous multi-agent systems via output communication. IFAC PapersOnLine 50(1), 1748–1753 (2017)CrossRef Zhu, L., Chen, X., Chen, Z., Hill, D.J.: Output synchronization of linear MIMO heterogeneous multi-agent systems via output communication. IFAC PapersOnLine 50(1), 1748–1753 (2017)CrossRef
Metadata
Title
Modeling the Structure of MIMO-Agents and Their Interactions
Author
Liudmila Yu. Zhilyakova
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-030-30763-9_1

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