As illustrated by O’Sullivan, individuals in an ABM are governed by a set of rules in order to provide a natural representation of a phenomena. I am intrigued by the notion of having such a flexible system, which allows agents to exhibit behaviours and reactions that differ from their counterparts. This reflects real-life situations, as the outcome of an event, for example, can completely depend on the actions of a single individual, who is influenced by their setting and social context and vice-versa.
Our in-class exercise of modeling the users of McGill’s outdoor walkways, however, revealed the incredibly complex nature of agent-based modeling. In attempting to represent how students, tourists, cyclists and vehicles use space, we quickly discovered that there are a wide range of users who use the space very differently, and also respond to certain events in very different ways.
This complexity brings up issues surrounding data collection/storage/usage limitations, which have arguably rendered the popularity of ABMs to be low in the geographic community to date. As noted by sah, I think that this issue has not been given enough attention regarding access to modeling capabilities. More importantly, however, because AMB is still in its infancy, I think that the way in which ABMs simulate human systems reinforces the notion of GIS as tool-making, a process whereby representations are constantly being improved upon. While GIS may currently struggle to represent processes, technological advancements—as O’Sullivan briefly illustrates—will perhaps enable ABMs (and GIS) to better incorporate the human element through increased public participation, for instance.