Monday, September 20, 2010

The Importance of Modeling – SENDSim, Part 1

By Carl Hunt

In the previous blog of 10 September, I offered to provide a graphic to better explain exchange and emergence as these concepts apply to our study of cyberspace and the development of a Science of Cyberspace. Below is that graphic and narrative explanation. This addition also serves as a bridge between discussing the concepts of exchange, self-organization and emergence and the importance of modeling to better understand cyberspace.

We will have a lot to say about modeling and simulation in coming blog entries, and we will hear from the real experts such as Dr. Eric Bonabeau (Icosystem), Dr. David Davis (VGO Associates) and Dr. Greg Amis (Icosystem, and the modeling project lead on SENDS for Eric and Icosystem). All of these experts are significant contributors to SENDS and we will be delighted to hear from them.

Without further adieu, I present our first graphic depiction of exchange, self-organization and emergence as empowered by cyberspace (click image to enlarge).

As shown in the figure, interactions (or exchanges), self-organizing criticality and emergence thus offer us insightful clues as to what we should seek to explain and predict in this new science. If thought of in the sense of some sort of vehicle that moves us from processes to a “final” product, we can visualize the relationship of these components of behavior in cyberspace. Exchange takes place in any environment, of course, but cyberspace as a supporting infrastructure brings the process of exchange to many more people and information transactions around the world.

From this infrastructure, the participants of the exchanges (people, systems and information) self-select and self-organize, again greatly facilitated though the network-based interactions cyberspace empowers. This self-organization process is the transmission that moves exchange into emergence. Absent the unifying body of discipline we propose in the Science of Cyberspace, we are only beginning to visualize the outcome, or product of emergence.

As Morowitz and others have noted, we can only see the emergence after it has happened, but advanced models such as agent-based modeling and simulation, accompanied by evolutionary algorithms, allow us to observe and deduce these potential behaviors through visual interfaces the models provide. These models will likely be the key to better “predicting” emergence in the future. We will be discussing the application of these modeling capabilities to SENDS in much greater detail in future blogs.

While the above figure appears to be a linear movement of information from exchange to emergence, only the beginning and the “end” (the emergence) have relatively fixed points, considering the highly dynamic nature of emergence. As the bottom arrow indicates, the continuous dynamic feedback that is inherent in cyberspace almost ensures nonlinearity will permeate the flow of information. Emergence will lead to more exchange and the process will coevolve and continue.

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