Papers
Follow
Find tag "complexity"
258.9K views | +308 today
Papers
Recent publications related to complex systems
Your new post is loading...
Your new post is loading...
Scooped by Complexity Digest
Scoop.it!

How Can the Study of Complexity Transform Our Understanding of the World?

How Can the Study of Complexity Transform Our Understanding of the World? | Papers | Scoop.it

The “study of complexity” refers to the attempt to find common principles underlying the behavior of complex systems—systems in which large collections of components interact in nonlinear ways. Here, the term nonlinear implies that the system can’t be understood simply by understanding its individual components; nonlinear interactions cause the whole to be “more than the sum of its parts.”


How Can the Study of Complexity Transform Our Understanding of the World?

Melanie Mitchell

https://www.bigquestionsonline.com/content/how-can-study-complexity-transform-our-understanding-world

more...
António F Fonseca's curator insight, January 22, 2014 4:45 AM

Wonderful and clarifying text.

Lorien Pratt's curator insight, January 22, 2014 11:20 PM

One of my favorite complexity authors.  An excerpt: "In the past it was widely assumed that such phenomena are hard to predict because the underlying processes are highly complex, and that random factors must play a key role.  However, Complex Systems science—especially the study of dynamics and chaos—have shown that complex behavior and unpredictability can arise in a system even if the underlying rules are extremely simple and completely deterministic.  Often, the key to complexity is the iteration over time of simple, though nonlinear, interaction rules among the system’s components."


This insight is at the core of Decision Intelligence, which adds an understanding of these emergent behaviors to the usual big data/predictive analytics/optimization stack.

Scooped by Complexity Digest
Scoop.it!

Measuring the Complexity of Ultra-Large-Scale Evolutionary Systems

Ultra-large scale (ULS) systems are becoming pervasive. They are inherently complex, which makes their design and control a challenge for traditional methods. Here we propose the design and analysis of ULS systems using measures of complexity, emergence, self-organization, and homeostasis based on information theory. We evaluate the proposal with a ULS computing system provided with genetic adaptation mechanisms. We show the evolution of the system with stable and also changing workload, using different fitness functions. When the adaptive plan forces the system to converge to a predefined performance level, the nodes may result in highly unstable configurations, that correspond to a high variance in time of the measured complexity. Conversely, if the adaptive plan is less "aggressive", the system may be more stable, but the optimal performance may not be achieved.

 

Measuring the Complexity of Ultra-Large-Scale Evolutionary Systems

Michele Amoretti, Carlos Gershenson

http://arxiv.org/abs/1207.6656

more...
No comment yet.