Bonabeau’s article goes to great lengths to illustrate the advantages of Agent Based Modeling (ABM). He provides a quick overview of the approach which consists of agents that independently make decisions towards their goals and a shared environment. The novelty of this approach is that it captures emergent behaviour and often counter-intuitive results by analyzing at the individual agent level (which is often highly heterogeneous). Bonabeau explains this modeling has been applied to many fields such as transportation, supermarket design, and stock markets.
Despite this broad applicability of ABM, it must be approached cautiously. I believe that there is a large gap between seeing a simulation of an emergent phenomenon and whether it can be validated as representative of reality. The accuracy of these simulations depends on the inputted parameters, which often must reflect difficult-to-quantify behaviours. An uncritical acceptance of ABM’s results can risk large sums of money, public trust, and lives.
Furthermore, it is important to use ABM to its full potential. Users of this tool should not focus solely on running this model until they get a desired result. There is room for geographic analysis of unexpected emergent interactions to better explain conclusions. There is also a need for a deep understanding of the limited spatial analysis each agent is capable of, and how the agents’ perception of their spatial surroundings affects their behaviour.
Bonabeau, Eric. “Agent-based Modeling: Methods and Techniques for Simulating Human Systems.” Proceedings of the National Academy of Sciences of the United States of America. 99.10 (2002): 7280-7287. Print.
– Madskiier_JWong
Tags: ABM