AGENT BEHAVIOR ADAPTATION METHOD IN INTELLIGENT TRAINING MANAGER PREPARATION SYSTEM AIR TRAFFIC CONTROL
DOI:
https://doi.org/10.26906/SUNZ.2020.2.017Keywords:
agent, adaptation, air traffic control manager, intelligent learning system environment, multiagent systems, planning, self-tuning, fuzzy set theory, learning efficiencyAbstract
In the framework of the agent-based approach, in order to increase the variability of the training environment for air traffic control dispatchers, the article improves the method for adapting the behavior of the agents of the learning environment of an intelligent learning system based on knowledge of the results of agent interactions. At the stage of making changes to the parameters of the planning subsystem, when insisting on agent behavior modeling systems, it is proposed to use the selftuning mechanism. To manage the process of self-tuning the behavior of intelligent agents, the article developed a toolkit for adapting the agent behavior planning system. The use of agent behavior models with planning methods will increase the success rate for the implementation of the expected agent behavior in the construction of intelligent learning systems. The approach proposed in the article for adapting the behavior of the agents of the learning environment of the intellectual learning system will increase its variability. As a result, such an intelligent training system will bring to a new level the training of air traffic controllers.Downloads
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