Abstract
Dynamic coordination of multi-agent systems (MAS) strategies under uncertainty based on a stochastic game model is solved. Dynamic coordination is teaching of the system of generating spatially distributed periodic signals. A stochastic game model is built, criteria for dynamic coordination of player strategies are determined, a recurrent method, algorithmic and software for stochastic game solving are developed. The developed model, method and algorithm for stochastic game resolution provide dynamic MAS coordination, which is manifested in locally deter-mined spatial and temporal alignment of players’ strategies. Dynamic coordination is ensured by an adaptive search method for resolving stochastic play, taking into account current penalties for relevant spatial coordination and rhythm disturbances. It is established that the effectiveness of training players to perform coordinated rhythmic actions is determined by the balance between these penalties, which is achieved by the influence of white noise. Dynamic coordination of agent strategies is achieved as the real-time stochastic game is unleashed based on gathering current information and its adaptive processing. The considered method belongs to the class of reactive methods and simulates the reflexive behavior of living organisms. The method allows finding stochastic game solutions in pure strategies.
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Kravets, P., Lytvyn, V., Vysotska, V., Ryshkovets, Y., Vyshemyrska, S., Smailova, S. (2021). Dynamic Coordination of Strategies for Multi-agent Systems. In: Babichev, S., Lytvynenko, V., Wójcik, W., Vyshemyrskaya, S. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2020. Advances in Intelligent Systems and Computing, vol 1246. Springer, Cham. https://doi.org/10.1007/978-3-030-54215-3_42
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