Models of Information Exchange Between Intelligent Agents
The article discusses the models of information exchange between agents in an abstract intelligent active system. Information exchange is a transfer of messages containing a certain semantic load, from the agent-translator to the agent-recipient. Moreover, in the exchange of information for all agents, the role change is characteristic: the translator becomes the recipient and vice versa. Under the influence of all informational messages, a psychological and business climate is formed in the intellectual active system, which closely correlates with the efficiency of the system. Therefore, it is important to prevent the appearance of information in the system that does not correspond to the truth. To do this, it is necessary to identify the reasons for transmitting false information and to determine managerial influences that would make it possible to minimize the amount of false information transmitted. This article discusses models of the flow of messages transmitted from agent to agent. In these models, parameters are identified, changing which through managerial influences, you can determine which information is true and which information is false. Therefore, to minimize the transmission of false information.
KeywordsIntelligent active system Intelligent agent Information exchange Psycho-behavioral type Concord Communication
The reported study was funded by RFBR according to the research project No. 17-01-00817A.
- 1.Mutovkina, N.Yu.: The formation of the optimal composition of multi-agent system. In: Hu, Z., Petoukhov, S., He, M. (eds.) Advances in Artificial Systems for Medicine and Education, AIMEE 2017. Advances in Intelligent Systems and Computing, vol. 658, pp. 293–302. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-67349-3_28Google Scholar
- 2.Mutovkina, N.Yu., Kuznetsov, V.N.: Algorithms for agreement and harmonization the creative solutions of agents in an intelligent active system. In: Hu, Z., Petoukhov, S., He, M. (eds.) Advances in Artificial Systems for Medicine and Education II, AIMEE 2018. Advances in Intelligent Systems and Computing, vol. 902, pp. 651–660. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-12082-5_59Google Scholar
- 3.Lipman, O.: Falsehood in Truth. O. Lipmann, L. Adam; foreword and trans. of A.E. Brusilovsky, 47  p. Legal Publishing House of Ukraine, Kharkiv (1929)Google Scholar
- 4.Lipman, O., Romanov, V.V., Romanova, E.V.: Psychology of interrogation of the accused in the criminal process. In: Legal Psychology: Chrestomathy, 352 p. Yurist (2000)Google Scholar
- 5.Gubanov, D.A., Novikov, D.A., Chkhartishvili, A.G.: Models of reputation and information management in social networks. In: Management of Large Systems: A Collection of Works, vol. 26, no. 1, pp. 209–234 (2009)Google Scholar
- 6.Dashkova, A.Yu.: Manipulative methods of influencing mass consciousness. Bull. Volga Acad. Public Serv. 1(22), 74–77 (2010)Google Scholar
- 7.Mutovkina, N.Yu.: Methods of Coordinated Control in Active Systems: Monograph, 164 p. Tver State Technical University, Tver (2018)Google Scholar
- 8.Otto von Bismarck: quotes of famous people, aphorisms. https://citaty.info/man/otto-fon-bismark?page=2. Accessed 07 Feb 2019
- 11.Wunsch, G.: Systems Theory: Translate from German of T.N. Krenkel, 288 p. Soviet Radio (1978)Google Scholar