So, we've had a taste of cellular automata, and now of agent based models, and are about to go on to other things. Maybe its a good time to look back at our initial thoughts about emergence and what it is/might be good for, and reflect a bit on where we've gotten to so far?

My own thoughts (hoping others will add theirs):

• CA's make interesting patterns, and are fine if one thinks the universe is deterministic and has a lot of time to do the computing needed to predict its future course
• agent based models can make interesting patterns too but also do things that seem more interesting/immediately interpretable to humans
  

A while back Laura suggested a field trip to The Fabric Workshop and Museum. Next Friday would be an excellent time to go. Shir Ly Camin, Education Coordinator, invites us to: Swarm Conversation with the Guest Curators, Abbott Miller and Ellen Lupton Friday, 3 March 2006 6:00 p.m. Camin says "Miller and Lupton will convene a discussion of "swarming" as it reflects contemporary views of nature, politics, and social life that favor unplanned and decentralized modes of organization. They will be joined by Deborah Gordon, Professor of Biological Sciences, Stanford University and Eugene Thacker, Assistant Professor at the School of Literature, Culture & Communication, Georgia Institute of Technology."

Here is my updated version that allows up to four ants and has the option to halt the process when any two ants cross paths. The display will restart by pressing go again. A couple of (I thought) interesting points: The initial coordinates are set up to match the ones that Kathy drew our attention to. This model is difffernt from Kathy's though in that it is not set up to be paralell like hers is. The result is much the same effect, except for two differences. 1) The internal pattern that is left in the centre when the ants start to move out in a circle are mirror images. 2) Because my world is larger, the ants don't wrap and bump into each other, and so they don't cycle.

Here's my latest Netlogo model, a simulation of ants searching a field for food. Hopefully the model (with documentation) explains itself; if not, feel free to ask. Here it is

Here's a standard Langton's ant with a few plots that might be of use. Documentation on the page might be a little sparse--ask me or check out the source if anything's unclear. link

Here's a link to a paper written by a few researchers at the 'Logic Systems Laboratory'. The authors describe the behavior of several 'interesting' rulesets of >2-state ants, and then discuss systems with >1 ants. link [pdf]

I was just looking through the book list on the course site. And I noticed that all of the books appear to have been written by white men. I was just wondering if anyone knew of any books written by women/minority scholars, too. I know the book list is a work in progress, and I'd be happy to see if we can flesh it out a little more. But, if Emergence/Complexity is a male-dominated field, that'd be interesting to know, too. I did a quick amazon search of emergence and didn't find much. Anyone else?

Here is the model with two of Langton's ants

It hit me Monday while sitting in class about how much of it is based simply on perspective. Emergent phenomena could be all around us, but are we too jaded to see most of it? Do we accept it as commonplace and something to be expected simply because we've seen it so much? Sometimes, when I'm feeling particularly philosophical, I look around me and see something that I've seen a thousand times and think, isn't that amazing? This happens the most with trees, I suppose. I still can't get over how complex, but simple, they are. When I think of emergence, I feel like I have to "change my glasses" (not that I wear them) and put on something that makes the world fresh again. Something that gives me back that sense of wonder that we all had when we were children.

Yes, yes, I agree with #1, and I understand that simple models may help define certain aspects, as opposed to the whole of a complex issue. I can see that and the utility of using them. But there are still a couple of observations about this model that I’d like to share: 1) My first interpretation of 50% preference was that it would imply no particular preference (which is why segregated results were so surprising when using 50% or less preference for difference), but this assumption isn’t true. After all, the test is still biased to a particular preference, no matter how low the %. It appears that the continuum of preferences would start at one end with 100% preference for similarity, progress on down to 0% preference for similarity, then to 0% preference for difference, on up through to 100% preference for difference at the other end of the scale. So, it seems to me that 0% of either would be truly no preference, and that there really is no surprise at seeing segregation resulting from a low similarity preference setting.