Досліджено проблему кооперативного прийняття рішень у мультиагентних системах на основі моделі стохастичної гри з корельованими стратегіями. Сформульовано ігрову задачу, розроблено метод та алгоритм для її розв’язування. Наведено та проаналізовано результати комп’ютерного моделювання стохастичної гри з корельованими стратегіями.
The stochastic game method of coalitions formation in multiagent systems is offered. Adaptive algorithm for stochastic game solving are developed. Computer modelling of stochastic game is executed. The parameter influences on convergence of stochastic game method for coalitions formation are studied. The analysis of received results is realized.
The problem of dynamic coordination of strategies of multiagent systems in the conditions of uncertainty on the basis of stochastic game model is solved. Dynamic coordination consists in system learning to generate the spatially-distributed periodic signals. The model of stochastic game is constructed, criteria of dynamic coordination of strategies are defined, a recurrent method, algorithmic and software support for the stochastic game solving are developed.
The problem of reinforcement learning of multiagent systems in the game formulation is considered. The Markovian model of stochastic game is constructed, criteria of game learning are formulated, the Q-method and corresponding algorithm of the stochastic game solving are described, results of computer realization of a Q-method are analyzed.