In O’Sullivan’s description of simple abstract models, he mentions Epstein and Axtell’s use of the term ‘generative’. It is discussed initially as a “new approach to social science” whereby if a model “replicates observed regularities in the real world”(542) the researcher can claim to have “explained the phenomenon”(542). Although this is mentioned in the context of social science, it strikes me as being completely against the use of the word ‘explanation’ when it is applied to science. To me, a scientific explanation involves being able to not only list factors that create the phenomenon and quantifying them but also understanding the interactions between them. In this case, ABMs are being used as a tool rather than a science and involve more trial and error button pushing than anything else. If one sets the parameters of the model in many different ways for each simulation and one happens upon the right combination of parameters, one has managed to explain a phenomenon. Thus, in my opinion, it is necessary to ensure one fully understands all the factors influencing a system and how these factors interact with one another before one can say they have explained the system even when an ABM produces results matching the system as seen in reality.
-Outdoor Addict
Is not the button pushing enabled by theory? Building an ABM requires one to define a system and behaviours – this should be based on theory and empirical work.
Also, is there any facet of the social sciences where we can say that we have a full understanding of all factors that would influence a system? Only if you draw artificial boundaries around a system. The catch is that we need this simplification to start developing an understanding of how components of a system interact.