Bonabeau’s article certainly gives us a good introduction to the potential of agent-based modeling and the wide-reaching social phenomenon that it is able to explore. The key contribution that ABM offers social science is the ability to study an issue from bottom-up by looking at interactions between agents rather than overall processes produced by agent. The concept of “growing” an explanation to social phenomenon is both catchy and intriguing.
I especially liked the last example in Bonabeau’s paper. It showed how an ABM is capable of incorporating the fact that each individual is situated in the social world and that we can most influenced by the people we know both in terms of our behaviors and our location (http://gizmodo.com/5879504/how-your-friends-locations-give-yours-away-online). In an age where social network sites allow us to communicate with more people than ever before, ABM can be powerful in studying the adoption of new ideas, dissemination of information, and power/influence.
However, there were two points which I thought deserved further explanation. First, when arguing for the flexibility exhibited in an ABM, the author points to its “… ability to change levels of description and aggregation: one can easily play with aggregate agents, sub-groups of agents, and single agents, with different levels of description coexisting in a given model” (7281). I think this is an attractive feature that warrants more description regarding how groups are created, whether a single agent keeps its description when aggregated with other agents, and can an agent move dynamically in/out of a group? Secondly, Bonabeau mentions the ability for ABM to capture “individual behaviors [that] exhibit memory… learning and adaptation” (7281), but fails to mention the type or the complexity of knowledge that can be learnt by agents (are logical inferences possible?). It would have been interesting to see an example of how this artificial intelligence plays out in an ABM and a brief discussion about the power and recent developments in the capability of this type of algorithms.
-Ally_Nash