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In working with the models in the NetLogo library, I frequently catch myself tinkering with code and then generalizing about patterns in the agents' behaviors--only to find that these conclusions are often shot to pieces as each model is left alone to morph and emerge over thousands of iterations. Such straightforward instructions and seemingly unpredictable results!
With all this "inherent randomness" (where does it come from?), I am really starting to believe that tackling the intricacies of emergence may be more intense than any one person's brain can handle. Talk about a mental workout.

This whole concept has made my mind spin. If emergent systems exist, how can we begin to obtain answers to these mysteries without falling into the reductionist constraints of traditional science? Does isolating components in a system really help us to better learn their functions? Is it necessary to understand each piece in order to understand a whole? Are there "correct" and "incorrect" observations that can be made about the models we alter? Or does it all just boil down to individual perception? What if, at this stage in our consciousness, we are simply not ready for (or capable of realizing) the truth? Ironic thought but if we stop searching so hard for answers, perhaps we will emergently stumble across them in the future. (I don't know how realistic that last thought is, but well...it certainly works for my car keys.)

natsu - The book you mentioned sounds really interesting and super relevant. If you remember the name, let me know! I'd like to track down a copy.