The Sidewalk Ballet speaks very critically of ABM’s: “Abstract ABMs disregard any detail of real world situations […]Things occurring in one space cannot be blindly applied to a different one without acknowledging the different factors which comprise and inhabit the space[…] then what is their use in GIScience?”
I will argue that very few ABM’s will claim to explain the whole issue being examined. I do not believe that the people responsible for the ant and the sugar model are attempting to explain income inequality. The metaphor there or the main purpose behind ABM’s in general is to simplify a certain problem to gain a better understanding.
If I were to, for example attempt at writing a piece of music, I would not write everything down at once—or if I were to decide deconstruct and learn how to play and conduct, let’s say Tchaikovsky’s Swan Lake ballet Op.20 written in 1875, I would not tackle the whole song at once. I would break down the components. First I might figure out what key the song was written in. I would then have a better understanding of what my options may be when choosing the notes throughout the song. From there I might teach myself different chords or scales that are required to play this song. Sure, if I blindly apply scales outside of the proper key into the song, my rendition might not sound good, but slowly, by gathering more knowledge of the problem I become closer to learning the piece as a whole. By understanding the key, time signature and tempo, I could then change the way I conduct the song. By changing one of these components, the mood of the song (outcome) can drastically be altered.
I’m not totally in favour of ABM’s, and I do understand some of the drawbacks, but I do think that they offer a way for us to break down complex phenomenon. As mentioned in class, the IPCC attempt, time after time, to model the impacts of GHG’s on climate change. People have been extremely critical of these models, but I believe that the point here is that models aid in the understanding of trends and patterns. Many miss the point and are very focused on proving these predictions (I will use this word gingerly) wrong. By being able to control variables, much like key or time signature, researchers have the opportunity to forecast and understand possible outcomes with very little risk. By being able to change desired variables, we now have the ability to see how each one impacts the system. As basic as the variable sliding bars seen in class appear, they still represent an extremely powerful tool.
http://youtu.be/_Uyg24hOiog
Great movie, great ballet.
Andrew “GIS” Funa