Initial Conditions Sensitivity Analysis of a Two-Species Butterfly-Effect Agent-Based Model

Abstract

AbstractAgent-based models are powerful tools for understanding complex systems. Their accuracy and capacity for prediction, however, are dependent on the initial conditions of the model during simulation. Current agent-based modeling endeavors show a lack of systematic analysis of sensitivity to initial conditions, and renewed interest is given to this issue. In this paper, we hypothesize that we can analyze the effect of initial conditions in agent-based models through the positive and negative feedback behaviors of individual agents. For this, we present a systems theory interpretation of local agent behaviors based on closed loops. Our approach illustrates how the initial conditions (of the whole model or of individual agents) determine the presence of positive or negative feedback agents in the agent-based model, and that their numbers influence the steady state of the model. We perform a proof-of-concept analysis on a two-species butterfly-effect agent-based model.KeywordsAgent-based modelInitial conditionsSensitivity analysis