It is general practice for scientists to publish the details of experiments and scientific research, with explicit documentation of the methods used, to enable future researchers to replicate and expand upon prior experiments. If a finding cannot be replicated, then current understanding of the study system in question and its variables or our methods of testing may be insufficient. Within archaeology, however, the process of studying the archaeological record is itself destructive, making reproducibility within research designs near impossible. Agent-based models (ABMs) are one tool which allow archaeologists to create representations of past reality and manipulate variables within a simplified system that can be replicated and falsified.ABMs are a class of computational models that simulate the behavior and actions of autonomous agents (whether individuals, groups, natural phenomena, or other units of interest) to investigate emergent phenomena within complex systems (e.g., Macal 2017; Railsback and Grimm 2012). ABMs are object-oriented computational models where individuals or agents are unique entities that interact locally with each other and/or their environment. Rather than describing overall, global phenomena, ABMs simulate system dynamics that arise from how the system's individual components interact with and respond to each other and their environment over time. This bottomup, generative, and historically contingent exploration of emergent patterns is the most important feature of ABMs (Epstein 2008). Thus, ABMs are particularly suitable for the analysis of complex adaptive systems and emergent phenomena in social sciences, biology, paleoecology, taphonomy, and many other disciplines. While more frequently employed in evolutionary anthropology, human ecology, and complexity science, ABMs offer archaeologists and social scientists the opportunity to study systems which may be impossible to replicate or may no longer exist (Premo 2006a; Premo 2006b) or as a space in which to test archaeological data (Thiele, Kurth and Grimm 2014).Agent-based modeling also offers new ways of ensuring research is reproducible and falsifiable. Model replication or re-implementation as a form of model validation is critical component in the modelling process and is encouraged in almost every ABM guide (Axtell et al. 1996;