Agent-Based Models as Policy Decision Tools: The Case of Smallpox Vaccination

Agent-based simulation (ABS) studies have recently been employed to support policy decisions. This article addresses the particular potentials and problems that ABS faces in this usage. First, the author warns against taking "familiarity" with specific ABS as a criterion for having confidence in the model's policy recommendations. Second, he shows that specific epistemic issues-in particular the high number of detailed simulated systems-require additional reflection on which decision rules to choose for policy decisions based on ABS. Third, the author points out directions in which the construction and uses of ABS in policy decision could be improved. Each of these issues is illustrated by simulation studies undertaken to investigate smallpox vaccination policies.