Game strategies for decision making in hierarchical systems. I. Mathematical model of stochastic game

Authors

DOI:

https://doi.org/10.20535/SRIT.2308-8893.2019.3.06

Keywords:

decision making, hierarchical system, conditions of uncertainty, stochastic game, mathematical model

Abstract

A mathematical model of a stochastic game for decision making in hierarchical systems under uncertainty conditions is developed. The essence of the game consists in aligning the players' pure strategies to achieve a consensus or a majoritarian collective solution. The parameterization of the game model for the separation of the autocratic, anarchic, and democratic hierarchical structures of decision-making systems is carried out. A Markov recurrent method for solving a stochastic game based on a stochastic approximation of the complementary slackness condition has been developed.

Author Biography

Petro A. Kravets, Lviv Polytechnic National University, Lviv

Petro Alekseevich Kravets,

Cand. Tech. Sci. (Ph.D.), an associate professor at the Information Systems and Networks Department of Lviv Polytechnic National University, Lviv, Ukraine.

Research areas: game models and decision-making methods in the uncertainty conditions, multi-agent systems.

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Published

2019-10-07

Issue

Section

Methods of optimization, optimum control and theory of games