Forecasting macro parameters representing the behavior of an applied multi-agent system

Under consideration is the method of probabilistic forecasting of macro parameters representing general patterns of an applied multi-agent system behavior.This system introduces the game interaction between a set of agents and a target.The behavior dynamics of such a system is described by a discrete-state discrete-time Markov random process and represented in the terms,which are considered convenient for interpretation and practical control of macro parameters.The corresponding calculations are based on common characteristics of the initial conditions.The probabilistic model of behavior of the system is generalized for the case of the mobile target and supplemented with formulas for the dynamical calculation of probabilistic distributions of the target’s defeat by the agents as well as the agent’s defeat by the target.