I would like to respond and build on to sidewalk ballet’s post about the contextual limitations of abstract Agent Based Models (ABMs). While your critique may be levelled at abstract ABMs specifically, I believe that ABMs are capable of capturing the complex specificities of any local area. Coming at a computational cost, I would imagine users of ABM would typically tailor their models to accurately reflect their situation. Another thing to consider is that an ABM’s environment does not need to represent a physical location. ABM can be used with environments that are very common to many agents, such as time or virtual environments like the stock market. I think of it as a way to model simultaneous decision-making, game theorying. In these types of non-place specific environments, more generalized ABMs may still be appropriate.
An important reminder is that agents need not be individuals as well. Frankly, I find this a more challenging concept for ABM. O’Sullivan touches on this point as well; how do we represent agents that are not individuals and who are also mobile? Is it ever appropriate to assume an entire family is one agent when a census tracks movement of the population? Can we assume a pride of lions in the savannah is one agent since it is clearly led by the dominant male? Tackling these issues of generalization and how to represent their movements allows for reduced computation cost and a scaling up of these models.
O’Sullivan, David. (2008). “Geographical information science: agent-based models.” Progress in Human Geography, 32(4) 541-550.
– Madskiier_JWong
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