An applied multi-agent system within the framework of a player-centered probabilistic computer game

The probabilistic model to represent the behavior of an applied multi-agent system that introduces the interaction between a set of agents and Player has been developed within the framework of player-centered probabilistic computer games.The approach features are given with the aid of a game developed for testing cognitive abilities.The agent’s behavior is nondeterministic and therefore unpredictable from Player viewpoint.The system allows both coordinated and autonomous agent’s behavior that depends on availability of information about the presence and position of workable agents for each other.Agent’s behavior is determined with the aid of the algorithm that includes identification of the probabilistic model parameters using maximized objective functions representing individual and group probabilities for Player defeating.Both the model and algorithm ensure the behavior control for relevant applied multi-agent systems.

Analysis of statistical dependencies between intellectual characteristics and gaming ability,measured with the aid of a computer game

The aim of this paper is testing a computer game as an alternative tool for the assessment of intelligence and creativity of school children.The relevance of the research task is determined by the growing interest in practical psychology in the use of computer games as a special diagnostic tool in educational process.There are two original factor models that have been developed and the structural equation modeling of measured parameters has been carried out.The relationships between game dynamic and final individual results in the computer game,on the one hand,and psychometric intelligence and divergent creativity,on the other,are presented.Weak correlation between the above-mentioned and individually measured intellectual and creativity characteristics of the participants with the computer game results was discovered.Consideration of these characteristics in the form of a common latent factor makes it possible to identify the corresponding dependencies only in some cases when there is a dividing the sample into groups according to their ability level.Particularly,the dynamics of game scoring allows to refer participants to the target group with a certain level of abilities(high intelligence and creativity versus low intelligence and creativity),and it is the high level of psychological traits that determines effectiveness in the game behavior,but not vice versa.The qualitative ratios of the two groups of subsets of participants were revealed:weak,medium and strong players and players with three different levels of psychological abilities.The prospects for the further use of computer games for assessment of cognitive abilities in the measurement of combination of psychological abilities are discussed.

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.