Emergence, Reflections

My first questions in this class were:
“How complex is an emerging system?

Can computer science really cover all facets when modeling a system?

How can we apply success/failure rates to modeling a system as a program with Boolean values?”


FIrst, I want to start by answering my questions that I originally asked in my first Serendip post after the semester of talking and having more experience.  I began with, “How complex is an emerging system?”.  What I think I meant by this question is how complex exactly can an emerging system be?  We’ve found using NetLogo that making simple models yields the best results for prediction.  The simpler a model, the easier to understand.  Of course, the breadth of NetLogo is great and models can represent and factor in many things to make such a model intricate to begin with (in lieu of being simple).

In regards to my second question, “Can computer science really cover all facets when modeling a system?”  NetLogo can cover whatever you’re modeling as long as you specify it.  Depending upon how many views you’d like to get of what you’re modeling, you can specify how many different scenarios or viewpoints of the interactions.

“How can we apply success/failure rates to modeling a system as a program with Boolean values?”  What I see now that I meant by this question is how can we say that this model is a good model or bad model based on the content?  It wasn’t worded quite the way I that I meant it to be. This is similar to a question some of us had earlier in the year, “What can be considered more ‘interesting’ (in a model)?”

As for the questions/future explorations I now endeavor to search out, is thinking (the concept of a thought) and focusing on breaking down things that I may find to be complicated.  I think that none of our questions (including my own, although I tried to answer them the best I could) can be _fully_ answered, but can always be explored as much as one would want to delve into it.  I am also very glad I took this course and am starting to question things when I see/experience them and sometimes think, “What would it be like to model this?”  I enjoyed really taking time to think in this class, as opposed to other classes where you don’t have this luxury.  I hope to never stop exploring emergence!

 

I came into the course with these questions:

1) What are some examples of systems that have no element of emergence at all? Or is there emergence in everything at a certain level?

2) How exactly will we be examining emerging systems and what will we learn from them?

3) How can I link what I have learned in Biology and Psychology to emergence?

I feel like my questions have been answered. I now find myself interested in the material that we ended with related to agent based modeling, in relation to thinking an evolution. My questions now are related to the exploration and definition of limits as well as to how to go from one level of organization (thinking) to another (evolution), or from inanimate to animate and animate to the conscious…

I really enjoyed the course of Emergence and feel that it has truly changed the way I view many things. I began the course knowing very little about the field of emergence and thought that emergence was actually a something very complicated to learn about. However, I quickly realized that the field of emergence is actually quite the opposite. Emergence is a field that tries to understand and make sense of many of the most complicated questions by breaking complex matters down into smaller parts. I have learned that emergence is a field of questions more than of answers. This was especially evident in our discussion of randomness and disorganization.

            I found it to be very useful to explore emergence in the way that we did, especially by looking at complex ideas and models and breaking them down into smaller parts so that we could examine the different elements interacting in simple ways and giving rise to complex outcomes. My favorite part of the course was coming to the realization that maybe complicated things are not as complex as we think they are. In all of my college years I had never taken a course that had conveyed that message. I found Netlogo to be very useful in modeling emergence because it really enabled me to see things that may otherwise have been very difficult to see. By creating and working on models throughout the semester I was able to gain insight into the operation of the system that I was trying to model through the observation of patterns. I realized that computer models just as natural phenomena are organized systems and that modeling has the great ability to show something that was not as obvious before. It was especially interesting when I would design a model and create certain codes and then get an unexpected outcome. By working with computer models I was able to repeatedly see this happen and realized that new properties can arise from simple interactions without any intention.  

The organization of this course was very interesting as we began by exploring a very general idea of what emergence was followed by an examination of deterministic and non-deterministic systems. Next we learned about randomness and I found our discussion and readings on this topic to be very interesting. I have always valued technology, but have gained a deeper appreciation of what it can do from this course. It became increasingly clear throughout the semester that computers have enabled us to see things that are otherwise very difficult to observe. Computer modeling was especially helpful in that it provided a way for sometimes vague ideas to be explored and to figure out if the way in which I was thinking even made sense. In conclusion, emergence has given me a new lens with which I can inspect and approach different phenomena. I’m glad I took this course and will definitely make use of the skills and insight I gained from working with computer models.  

            At the beginning of the semester, I was self-conscious about how hazy my initial ideas about the concept of “emergence” were.  I was worried that everyone else would have a “right answer” and that it would differ from my own ideas, so one of my initial questions was “What does "emergence" actually mean to different people?”  We quickly began to answer that question.  Though the concept of emergence has become only slightly less hazy in my mind, it is now clear to me that “emergence” can describe phenomena that occur pretty much anywhere you look.  People find their own meaning and significance based on their own notions about emergence, and while I do not believe that emergence exists only because beings capable of conscious thought are around to observe it, I do believe that we thinkers dramatically influence what it means to be emergent.  “Emergence” is a tool we can use to make sense of how the universe works.  I used to think that all tools needed to be standardized, or at least commonly understood, to be useful.  Now, I think that emergence is an example of a tool that works because there are so many different versions of it.  It can be stretched and bent and twisted until our thoughts make sense to ourselves and eventually to others. 

            My other questions centered more on the practical applications of the course, especially computer models.  Having very little background in computer science, I was skeptical about the idea that I, with such limited resources, could create models that were useful or applicable to the real world.  As a biologist and a geologist, I like to be able to put theories into practice, but I couldn’t see how that would be possible in this case.  To a large extent, I have yet to be convinced that models can accurately describe actual living systems.  More specifically, I am not sure I personally will ever have the skill or the equipment to build my own models or even answer my own questions with any degree of satisfaction.  Especially after having worked on a program that attempts to model large biological populations, I feel like so many of the parameters we set in the NetLogo world are arbitrary features we employ only to “get it to work.” 

            This brings up our extensive conversations about the limitations of deterministic systems and whether there are processes that cannot be done deterministically.  From our work in NetLogo, it would be easy to conclude that yes, in fact there are many things that cannot be done deterministically.  But then I remember how extremely limited I am in my programming skills and it seems more plausible that if we tried hard enough we could actually do anything we wanted.  

            The most important question that I had that remains unanswered is whether it is possible that the universe as we know it is a deterministic system.  As a class, the general consensus seemed to be that no, the universe cannot be the way it is without randomness.  As before, I remain unconvinced.  I think this is another example of us not being capable of knowing the answer.  Instead of thinking about the nature of random vs deterministic systems, we should think about the influence of time on these systems.  Time is the only factor we cannot manipulate (as far as we know - my inner sci-fi fan remains hopeful) but I have a feeling it would make all the difference.  As I mentioned in the forum for week 3 of this course, it is very plausible that if we were to re-run the Big Bang exactly the way it happened, INCLUDING setting it at the exact same time, it could be a deterministic process.  However, until we are able to manipulate time, we won’t know for sure.

            After that long-winded post, I suppose that I can now sum up what I learned about emergence in three words: Anything is possible.  And now I’m off to work on my time machine…