Досліджується проблема координації та самоорганізації стратегій мультиагентних систем на основі моделі стохастичної гри виду «хижак – жертва» з локальними зв’язками між агентами. Розроблено ігровий рекурентний метод та алгоритм координації стратегій агентів під час мінімізації функцій середніх програшів. Виконано комп’ютерне моделювання стохастичної гри «хижак – жертва». Досліджено вплив параметрів моделі на збіжність ігрового методу.
Досліджується проблема координації стратегій мультиагентних систем на основі моделі стохастичної гри з локальними зв’язками. Розроблено ігровий рекурентний метод та алгоритм формування узгоджених стратегій агентів в процесі мінімізації функцій середніх програшів. Виконано комп’ютерне моделювання стохастичної гри для побудови карти скоординованих стратегій. Досліджено вплив параметрів моделі на збіжність ігрового методу.
Deformation processes in media with fractal structure have been studied. At present, research on the construction of mathematical methods and models of interconnected deformation-relaxation and heatmass transfer processes in environments with a fractal structure is at an early stage. There are a number of unsolved problems, in particular, the problem of correct and physically meaningful setting of initial and boundary conditions for nonlocal mathematical models of nonequilibrium processes in environments with fractal structure remains unsolved.
This paper proposes a new application of the stochastic game model to solve the problem of self- organization of the Hamiltonian cycle of a graph. To do this, at the vertices of the undirected graph are placed game agents, whose pure strategies are options for choosing one of the incident edges. A random selection of strategies by all agents forms a set of local paths that begin at each vertex of the graph. Current player payments are defined as loss functions that depend on the strategies of neighboring players that control adjacent vertices of the graph.
In this paper, a stochastic game model of self-organization of strategies of stochastic game of mobile agents in the form of cyclic behavioral patterns, which consist of coordinated strategies for moving agents in a limited discrete space, is developed. The behavioral pattern of a multi-agent system is a visualized form of orderly movement of agents that arises from their initial chaotic movement during the learning of a stochastic game.
In the work, on the basis of the apparatus of fractional integro-differentiation, the mathematical models of heat-and-moisture transfer and of deformation-relaxation processes in the medium with "memory" effects and self-organization are constructed. Numerical implementation of the mathematical models of heat-transfer and moisture-transfer is based on the adaptation of the predictor-corrector method. That is why the mathematical models obtained in this work are in a finite-difference form. For the explicit difference scheme, the stability conditions are determined on the basis of the met
The mechanisms of self-organization of information heterogeneous networks have been analyzed in this article and new indicators and criteria for defining functionally stable networks have been suggested in accordance with the concept of SON, as well as a mathematical model of relevant network processes based on hypergraphs providing the required parameters and performance indicators of the mentioned hypernet has been rigorously substantiated. Due to the suggested indicators and criteria, we can evaluate and compare different structures of the high-connectivity networks, and apply them to t
In this research the actual problem of self-organizing of strategies of stochastic game of multiagent systems is considered. Self-organizing display are formations of the co-ordinated behavioural patterns of group of the mobile agents endowed with the ability to move within a limited discrete space.
Presented the basic theories and algorithms with the help of which common coordinated actions of a group of objects are achieved. To research the joint work of a group of drones (UAVs) capable of self-organization, using the theory of swarm intelligence. The method of organizing the interaction of a group of UAVs in the environment, by dividing the group into local subgroups, is considered. The proposed algorithm to prevent possible collisions of neighboring UAVs by recalculating the flight trajectory.
Processes of self-assembly were studied in the magnetic polymer carbon nanocomposites doped with cobalt nanoclusters. These processes proceed due to the diffusion of magnetic nanoparticles stimulated by a combined effect of an outer steady magnetic fields and heating. The obtained polymer composites are promising for practical applications.