ARTIFICIAL INTELLIGENCE IN SYSTEMS SIMULATION

Abstract

Simulation modeling is an important tool in various scientific and engineering fields, allowing to represent complex systems and processes without the limitations of physical experiment. Traditional modeling methods often prove to be insufficiently effective for the analysis and prediction of such systems. These tools have evolved significantly with the integration of artificial intelligence (AI), which offers enhanced capabilities in the main aspects of simulation modeling, such as optimization, data analysis, verification and validation. The application of AI, in particular machine learning and agent modeling with elements of intelligence, allows to automate individual stages of modeling, increase the accuracy of predictions and gain a deeper understanding of the dynamics of the studied systems. The article considers the advantages of using AI for scenario generation, model calibration, parameter optimization and analysis of simulation results. The prospects for further development of AI integration into simulation models are discussed.