Last Tuesday, we had our first discussion concerning “Introduction to Complex Systems: An Adventure to the Frontier of Knowledge,” and “Simulation for the Social Scientist,” and explored how understanding by creating, or “The Constructive Way of Understanding” works.
Society, life, intelligence is too complicated when broken down from the specific objects. They are much simpler and understandable when viewed from the occurrences which appear and disappear yet generated continuously. Therefore, society, life, intelligence, can be understood as dynamic systems. This is where the idea of complex systems is significant.
Lets say you wanted to understand how a person is created, and studied every detail of his/her DNA. This would be the correct approach from a biologist. Yet even if you understand all of a person’s DNA does not mean you understand him/her completely; it is necessary to approach from other fields.
Most scientific fields understand by reduction: understanding specific objects (such as DNA) in order understand the whole (the human being). Yet the whole is much more complicated, and it is necessary to see relationships between fields, and not reductively. These gaps within seemingly unrelated fields are where the idea of complex systems can explain.
Why do we use simulations?
So how do we understand complex society, life, or intelligence without reduction? We must take a more tentative approach, because we must see the complicated dynamics in a system. That is why we use simulation, because unlike data analysis, where existing data is analyzed, simulation creates completely new data in a simplified environment. This is what we call the Constructive Way of Understanding. And through such process, simulation allows the observer to understand the structure of a system.
This is the core idea of simulation: Rather than understanding what something is, we must understand how it works through a constructive method. Although simulations are dictated by how the models are designed, we believe simulation is significant because they can give new insights concerning complex systems, revealing data that may have never been possible with data analysis alone.
For the second part of the class, we explored the different kinds of simulation. First, we experienced computer simulation by discovering the dynamics of the logistic map according to the dynamics of each parameter, using “chaotic walk.”
Simulation is not limited to scientific fields. Although some may refer only to computer simulation when discussed the above, simulation (at least in this course) is in other words, creation of dynamics, whether it be in a computer or a story.
That is why we also looked into how Naoki Urasawa, a famous Japanese manga artist created, or simulated his characters in his many very successful series of manga. It was as if he only created the characters, and then simulated them into their own story.
Next week we will continue on exploring the Constructive Way of Understanding. See you again then!
Takashi Iba and Yoshihisa Fukuhara, Introduction to Complex Systems: An Adventure to the Frontier of Knowledge, NTT Publishers, 1998 (in Japanese)
Nigel Gilbert, Klaus G Troitzsch, Simulation for the Social Scientist, Open University Press, 1999
Takashi Iba & Kazeto Shimonishi, "The Origin of Diversity: Thinking with Chaotic Walk", Unifying Themes in Complex Systems Volume VIII: Proceedings of the Eighth International Conference on Complex Systems, Sayama, H., Minai, A. A., Braha, D. and Bar-Yam, Y. eds., NECSI Knowledge Press, Jun., 2011, pp.447-461.
[ http://necsi.edu/events/iccs2011/papers/72.pdf ]
ChaoticWalker: A New Vehicle for Exploring Patterns Hidden in Chaos
[ http://www.chaoticwalk.org/ ]