Serendip is an independent site partnering with faculty at multiple colleges and universities around the world. Happy exploring!

Reply to comment

jguillen's picture

Deterministic Models

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? 

Reply

To prevent automated spam submissions leave this field empty.
2 + 4 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.