‘Hard’ and ‘Soft’ Methods in Complex Adaptive Systems (CAS) : Agent Based Modeling (ABM) and the Agent Based Approach (ABA)

In this chapter, we provide the basis for why a Complex Adaptive Systems (CAS) approach is critically important to solving problems. As a naturalistic reality, a theoretical framework, or a heuristic device, CAS is a powerful tool. Agent Based Modeling (ABM), too, can be a powerful way to discreetly model a CAS understanding of phenomena. When ABM can be used, it is a powerful tool. However, ABM has drawbacks that make it an infeasible method some of the time. These drawbacks should not preclude us from using CAS as an alternative, ‘mixed,’ ‘qualitative,’ or ‘heuristic’ method. For this reason, we have outlined a new approach—the Agent Based Approach or ABA—which can be used the majority of the time when CAS analysis is indicated. ABA was developed by Drs. Derek and Laura Cabrera at Cornell University with an expressed focus on the analyses of CASs leading to specific policy recommendations, although it is quite possible that many aspects of ABA can be applied outside of a policy context. This is especially true in light of more nuanced and expanded definitions of ‘policy’ and/or ‘policy analyst.’ Where one might think of ‘a policy’ as a statement or document presented in a legislative, legal, or bureaucratic context, we promote that an understanding of CAS means that a ‘policy’ is simply a set of guidelines for understanding how agent action (the following of simple rules) will affect emergent properties. In other words, policy can be defined as “a statement of the simple interaction rules that one predicts will lead to desired systemic change.” In this regard, ‘a policy’ is something any person might utilize anywhere, not merely something a policy analyst in the halls of Congress might use. To understand and effect change on any CAS—even if the CAS is your family, your classroom, your team, your organization, the state or federal system, or a global crisis—requires you understand the system, to identify the types of actions that can be taken to alter it, and then codify those generalizable actions into specific recommendations. The steps to doing this are the same regardless of the venue or scale. The degree, scale, resources available, timeline, stakeholders, and relative complexity may change, but the basic process does not. In other words, policy analysis is a fractal pattern and ‘the analysis of policy’ is for everyone (i.e., not limited to legislative personnel). Therefore, ABA is a tool that anyone can use, and is well-suited for the formally trained policy analyst. ABA provides another tool in the systems scientist’s tool belt and is an invaluable means by which policy students or scientists can better understand and effect complex adaptive systems.