Structural Distinguishability of Static and Adaptive Policy Regimes in Agent-Based Regulatory Simulation

This paper presents a controlled simulation benchmark for agent-based models (ABMs) used in evaluating regulatory interventions, specifically focusing on the structural distinguishability between static and adaptive policy regimes. It compares four scenarios involving constant and adaptive agents and policies, utilizing various controllers to assess their impact on regulatory outcomes. The findings underscore the importance of regime distinguishability in adaptive policy-oriented ABMs, suggesting that average performance metrics alone may obscure significant differences in regulatory effectiveness, which is crucial for practitioners developing policy simulations in complex systems.