- My eBooks
Ed Radio
Current song: Loading ...
Stream title:
Bit rate:
Current listeners:
Maximum listeners:
Server status:
AutoDJ status:
Source connected:
About
About Stephen Downes
About Stephen's Web
About OLDaily
Subscribe to Newsletters
gRSShopper
Threads Discussions
Privacy and Security Policy
Subscribe
Web - Today's OLDaily
Web - This Week's OLWeekly
Email - Subscribe
RSS - Individual Posts
RSS - Combined version
JSON - OLDaily
Viewer
Social Network
Stephen's Web and OLDaily
Half an Hour Blog
Google Plus Page
Twitter Feed
Flickr Photos
Huffington Post Blog
Slideshare
Blip TV
Professional
National Research Council Canada
Research Topics, Research Wiki, Code
Publications
Presentations
All My Articles
Contact
Email: stephen@downes.ca
Email: Stephen.Downes@nrc-cnrc.gc.ca
Skype: Downes
Interactive Value Creation
Posts
March 19, 2012
Some good reflections. One is that network science tells us we cannot understand the workings of a system by looking at the parts. I would add that this is one of the major differences between network theory and systems theory. "The suggested unit of analysis is now communication and emergence, not entities." Additionally, the same phenomena look different when viewed in this way. "Self-interest in the network economy looks different from self-interest in the market economy; Individual success is likely to take place through enriching relationships, being part of networked interaction aiming to enable both the individual and the collective effort."
[Comment] [Direct Link] [Tags: Interaction, Networks]
April 12, 2010
"Nonlinear dynamics are concerned with complex, messy systems," writes Esko Kilpi in this excellent post describing the interplay between patterns and connections. "Chaos theory explains how the parameters in the equations cause patterns in time. These patterns are called attractors... At very high rates of, for example information flow, the system displays a totally random behavior. The pattern is highly unstable. However, there is a level between repetition/stability and randomness/instability. This level is called the edge of chaos. The pattern in time is called a strange attractor. The strange thing with a strange attractor is that the ongoing movement is never the same but always recognizable."
So what? Well, it gives you a way of organizing things. You can't manage or control a chaotic system - you can't even predict the outcome. But as this article suggests, you can identify, and even position, attractors. "In sum, our strategy was to control only that which could be ordered. For those activities in the realm of that which is, and must be, unordered, we watched and we shaped – gently, but with insistence. Because I have learned to know the difference between the states of order and unorder, I am now seen by all Athens as the wisest of men." This is at the heart of Snowden's framework (see below).
[Comment] [Direct Link] [Tags: none]





