Emergence, Week 3

From the beginning of the course, we began with the idea that complexity can arise from simple interactions. Last week it became even more convincing that simple deterministic rules can result in complex seeming behavior as seen in Langton's Ant and the Game of Life. In addition, the importance of the environment was highlighted in Langton's Ant as it became clear that the instructions of the agent do not change and therefore, the agent is not changing. Instead, the environment changes as a result of the established rules, which affect the agent. Additionally, it is also the case that changes in the environment can be produced by an agent as well as by an observer. As far as our conversation from last week of deterministic models, we were left with the following thought: maybe everything that can be done non-deterministically can also be done deterministically?

I think that it is possible and even helpful to deterministically model something that is thought to occur in a non-deterministic way. On the other hand, while many things can be modeled in a deterministic way, there are certainly things outside of the deterministic range. A problem with deterministic models is that we think that they are limited in what they can show. However, this idea does not take into account the fact that deterministic models can teach us a lot and help us to understand things that are seemingly complex. If we accept that the point of a model is not to determine what is real, but rather to show what might be, rather than what is, then deterministic models may be considered to be good models.

On another note, I think that both deterministic and non-deterministic models can contain the emergent element of "surprise" because you can get unexpected results in both. However, in the deterministic model, what initially is "surprising" soon becomes predictable because of the basic deterministic qualities in which the model will do exactly the same thing again if started again from the same starting point. On the other hand, non-deterministic models are able to uphold the element of “surprise” and unpredictability, which brings an important question to mind; does rule-based unpredictability still leave us in a deterministic mode? 

I’ve been thinking more about the question as to whether, were the Big Bang to be run again, every individual event would happen exactly the same as has happened this time around.  On the surface, it would appear that there is too much random chance for that to happen, as we pointed out in class.  However, the more I think about it, the more it seems vaguely possible that what we perceive as chance is actually predetermined and in fact deterministic.  In the cast of Langton’s Ant, it looked at first like the ant was moving randomly until it began building the road.  Upon replaying the model, we saw that the “random motion” could be re-created no matter how many times you run the simulation.  The key here is that it took a second running for us to recognize it.  Since we cannot and have not (to the best of my knowledge) replayed any sequence of time, we can’t yet recognize that what we think of as chance isn’t random at all.  Assuming this is true, the Time Paradox makes sense.  If one were to go back in time and change something in the past, the program would be altered and would fail to progress as planned.  Alternately, if one were to get a glimpse of their future self and as a result try to change the course of their life, the program would also be altered. 

       The opening scene in Tom Stoppard’s play “Rosencrantz and Guildenstern are Dead” illustrates what I’m trying to express.  The two title characters have been flipping a coin for awhile, and every time it has come up heads.  They talk about how it shouldn’t be surprising each individual time the coin comes up heads, because chance tells them that it is just as likely to come up heads as tails.  They also talk about how they could potentially be trapped in a time loop where they are not spinning a single coin multiple times but are replaying a single coin spin multiple times; hence the result is always the same.  If that were the case, it is a prime example of a deterministic system.  If you replay an even in exactly the same way, it gives you the same result every time.  This may be a simple example, but it does help support my idea that randomness is just a narrow perspective of a deterministic system.  After all, without knowing the rules of Langton’s Ant, we couldn’t predict its outcome.  Maybe we just aren’t familiar enough with the overlaying rules of the universe to have the perspective that would allow us to eradicate the concept of randomness.