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 probabil...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.展开更多
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 a...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.展开更多
文摘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.
基金Grant 17-06-00277 from the Russian Foundation for Basic Research.
文摘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.
