Abstract
The adaptive game method of event synchronization in multiagent systems in the conditions of uncertainty is developed. The essence of a method consists in alignment of delays of event approach based on action supervision of the next players. The formulation of stochastic game is executed and the game algorithm for its solving is developed. The parameter influences on convergence of a game method are investigated by means of a computer experiment that allows to study the dependence of the training time on the stochastic game of agents from the basic parameters of the algorithm and permits to assert that partial compensation of uncertainty is ensured by the agent ability to self-learning and adaptive decision-making strategies. The obtained work results are used in the construction of multi-agent systems of various purposes, ensuring the work coordination of the components, message transmission between agents, construction of communication protocols, promoting self-organization of multi-agent systems.
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References
Byrski, A., Kisiel-Dorohinicki, M.: Evolutionary Multi-Agent Systems: From Inspirations to Applications, 224 p. Springer (2017)
Radley, N.: Multi-Agent Systems – Modeling, Control, Programming, Simulations and Applications, 284 p. Scitus Academics LLC (2017)
Rachid, B., Hafid, H.: Distributed monitoring for wireless sensor networks: a multi-agent approach. Int. J. Comput. Netw. Inf. Secur. (IJCNIS) 6(10), 13–23 (2014). https://doi.org/10.5815/ijcnis.2014.10.02
Barabash, O., Shevchenko, G., Dakhno, N., Neshcheret, O., Musienko, A.: Information technology of targeting: optimization of decision making process in a competitive environment. Int. J. Intell. Syst. Appl. (IJISA) 9(12), 1–9 (2017). https://doi.org/10.5815/ijisa.2017.12.01
Amato, C.: Decision-making under uncertainty in multi-agent and multi-robot systems: planning and learning. In: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI 2018), pp. 5662–5666 (2018)
Sahai, A., Sankat, C.K., Khan, K.: Decision-making using efficient confidence-intervals with meta-analysis of spatial panel data for socioeconomic development project-managers. Int. J. Intell. Syst. Appl. (IJISA) 4(9), 92–103 (2012). https://doi.org/10.5815/ijisa.2012.09.12
Demir, O., Lunze, J.: Event-based synchronization of multi-agent systems. In: IFAC Proceeding Volumes, vol. 45, Issue 9, pp. 1–6. Elsevier (2012)
Veretennikova, N., Kunanets, N.: Recommendation systems as an information and technology tool for virtual research teams. In: Advances in Intelligent Systems and Computing II, vol. 689, pp. 577–587 (2018)
Zhang, W. (ed.): Self-organization: Theories and Methods, 255 p. Nova Science Publishers, USA (2013)
Roy, S., Biswas, S., Chaudhuri, S.S.: Nature-inspired swarm intelligence and its applications. Int. J. Mod. Educ. Comput. Sci. (IJMECS) 6(12), 55–65 (2014). https://doi.org/10.5815/ijmecs.2014.12.08
Yin, G., Wang, L.Y., Zhang, H.: Stochastic approximation methods – powerful tools for simulation and optimization: a survey of some recent work on multi-agent systems and cyber-physical systems. In: AIP Conference Proceedings, vol. 1637, p. 1263 (2014)
Chakroborty, S., Hasan, M.B.: A proposed technique for solving scenario based multi-period stochastic optimization problems with computer application. Int. J. Math. Sci. Comput. (IJMSC) 2(4), 12–23 (2016). https://doi.org/10.5815/ijmsc.2016.04.02
Ummels, M.: Stochastic Multiplayer Games: Theory and Algorithms, 174 p. Amsterdam University Press (2014)
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Kravets, P., Pasichnyk, V., Kunanets, N., Veretennikova, N. (2020). Game Method of Event Synchronization in Multi-agent Systems. In: Hu, Z., Petoukhov, S., Dychka, I., He, M. (eds) Advances in Computer Science for Engineering and Education II. ICCSEEA 2019. Advances in Intelligent Systems and Computing, vol 938. Springer, Cham. https://doi.org/10.1007/978-3-030-16621-2_35
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DOI: https://doi.org/10.1007/978-3-030-16621-2_35
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