Predicting the location where a lost person could be found is crucial for
    search and rescue operations with limited resources.
    To improve the
    precision and efficiency of these predictions,
    simulated agents can be
    created to emulate the behavior of the lost person.
    Within this study,
    we introduce an innovative agent-based model designed
    to replicate diverse psychological profiles of lost persons,
    allowing these agents to navigate real-world landscapes while making
    decisions autonomously