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. 2) I thought that even if we only consider two colors of people, we should still probably consider the fact that in real life there isn’t often an equal number of each. It seems as though it would be useful to be able to adjust the proportion of color quantities (and so there’s an enhancement suggestion). 3) What came to mind from my sociology reading was that many blacks also rate black neighborhoods unfavorably and prefer white neighborhoods (which tend to be economically better off with more resources). In other words, in the real-life example of white & black, one color preferred similar and one preferred different. And so there’s another enhancement possibility, but I think this one might be less useful because in the simple model world, I suspect this would cause constant movement (as long as preference strengths were high enough) since one color’s goals would be counter to the other’s. While in the real world, economic and socio-political barriers help prevent minorities from moving to resource-rich (predominantly white) neighborhoods. Interesting observation: I initialized the model with segregated distribution and set the preference to difference and the strength of that preference to 77%; I wanted to see how easy it was to undo segregation when agents were motivated to do so. But it ran on and on without ever being able to get lower than 45% similar neighbors. I tried again and found that with 60% preference strength it was attainable, and the % similar went down to 18. What resolved was a screen of colored lines – short parallel lines of green and red in clusters. I repeated both with the same results. I’m guessing that the higher preference scuttles the success by prompting agents to move on before diversity can be achieved in any area, so the breaking point must lie between 60 and 77%.