This paper explains how the Islamic State grew rapidly, answering a question of "what is" the Islamic State? A review of existing literature on simulation modeling of insurgencies identifies several gaps, as existing theories of non-state actors and insurgencies are inadequate to explain ISIS's performance. Additionally, there are few mathematical simulation models of insurgent behavior that can reproduce ISIS results. Finally, what models exist are not detailed enough either to conduct detailed experiments testing proposed explanations of ISIS, or evaluate policy responses aimed at containing or mitigating ISIS. The paper offers several contributions. First it proposes a dynamic hypothesis that the Islamic State (ISIS) is an emerging-state actor, a new form of actor that differs from traditional non- state actors and insurgencies. Propositions are constructed and presented as an overall theory of emerging-state actor behavior. These propositions are then simulated as experiments within a detailed model parameterized with conditions very similar to what ISIS faced in Iraq and Syria 2013. The model is then run from 2013-2020, and experiment results confirm evidence of emerging- state actor behavior and allow refinement of model boundary assumptions. Second, an initial set of intervention policies are tested in a variety of conditions: best case, operationally constrained, isolated, combined, and at different timing intervals. Analysis of the results yields key dynamic insights. These insights aid policy makers in understanding the challenges posed by emerging state actors. Finally, the detailed simulation model used to test the propositions and policy analysis, including a novel approach to combat simulation with endogenous geospatial feedback, is provided in full detail in two Appendices. Appendix A provides a sector-by-sector view of model structure and equations. Appendix B provides more discussion, analysis and sources used to develop model structure, establish parameter values and determine equations for the simulation. Due to length and other considerations, Appendix B is available only upon request. The detailed simulation model can be used to refine non-state actor theories (configured for insurgencies, emerging-state actors, or other scenarios). The model can be loaded with other scenarios to simulate other actors in other geospatial terrain: ISIS in Libya, Boko Haram in Nigeria, the returning Taliban in Afghanistan, etc. Keywords: ISIS, ISIL, DAESH, insurgency, conflict, security, stability, non-state actor, emerging- state actor, combat simulator, geospatial, national security.

This paper explains how the Islamic State grew rapidly, answering a question of "what is" the Islamic State? A review of existing literature on simulation modeling of insurgencies identifies several gaps, as existing theories of non-state actors and insurgencies are inadequate to explain ISIS's performance. Additionally, there are few mathematical simulation models of insurgent behavior that can reproduce ISIS results. Finally, what models exist are not detailed enough either to conduct detailed experiments testing proposed explanations of ISIS, or evaluate policy responses aimed at containing or mitigating ISIS. The paper offers several contributions. First it proposes a dynamic hypothesis that the Islamic State (ISIS) is an emerging-state actor, a new form of actor that differs from traditional non- state actors and insurgencies. Propositions are constructed and presented as an overall theory of emerging-state actor behavior. These propositions are then simulated as experiments within a detailed model parameterized with conditions very similar to what ISIS faced in Iraq and Syria 2013. The model is then run from 2013-2020, and experiment results confirm evidence of emerging- state actor behavior and allow refinement of model boundary assumptions. Second, an initial set of intervention policies are tested in a variety of conditions: best case, operationally constrained, isolated, combined, and at different timing intervals. Analysis of the results yields key dynamic insights. These insights aid policy makers in understanding the challenges posed by emerging state actors. Finally, the detailed simulation model used to test the propositions and policy analysis, including a novel approach to combat simulation with endogenous geospatial feedback, is provided in full detail in two Appendices. Appendix A provides a sector-by-sector view of model structure and equations. Appendix B provides more discussion, analysis and sources used to develop model structure, establish parameter values and determine equations for the simulation. Due to length and other considerations, Appendix B is available only upon request. The detailed simulation model can be used to refine non-state actor theories (configured for insurgencies, emerging-state actors, or other scenarios). The model can be loaded with other scenarios to simulate other actors in other geospatial terrain: ISIS in Libya, Boko Haram in Nigeria, the returning Taliban in Afghanistan, etc. Keywords: ISIS, ISIL, DAESH, insurgency, conflict, security, stability, non-state actor, emerging- state actor, combat simulator, geospatial, national security.