A Methodology for Limit Cycle Detection in Simulation Models

The exploration of model behavior is often a necessary step to validate and generate information from them, and it permits modelers and users to identify critical parameters. This is even more crucial when simulation techniques, such as agent-based models, are employed. The paper contributes to the discipline by proposing a novel exploration methodology to detect parameter configurations that generate limit cycles. It differs from pre-existing methodologies since it automatically explores the parameter space with a strategy that, once detected, investigates all the neighboring space until the limit cycle region ends.