Ігрові стратегії прийняття рішень в ієрархічних системах. І. Математична модель стохастичної гри

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

Evolutionary multi-agent systems: from inspirations to applications

This book addresses agent-based computing, concentrating in particular on evolutionary multi-agent systems (EMAS), which have been developed since 1996 at the AGH University of Science and Technology in Cracow, Poland. It provides the relevant background information on and a detailed description of this computing paradigm, along with key experimental results. Readers will benefit from the insightful discussion, which primarily concerns the efficient implementation of computing frameworks for developing EMAS and similar computing systems, as well as a detailed formal model. Theoretical deliberations demonstrating that computing with EMAS always helps to find the optimal solution are also included, rounding out the coverage