I saw the link for Complexity 1001 and thought I might use it to jump start my learning.
Where would be a good place to start? What article (book chapter etc.) could you suggest -- something to get my feet wet. Perhaps from here I could raise a question or two for subsequent discussion, pick up another yet another suggesting resource or two, and go from there?
DR. C'S RESPONSE
Dear Complexity Challenged, thanks for becoming part of this blog. I think the best way to "jump in and get your feet wet" is to take a historical macro-level approach and begin with two of the best known reviews of the field.
1. The first is Capra's The Web of Life. While written in 1997, this book still provides the best introductory review of complexity science and its historical roots--in particular, systems science, cybernetics and artificial intelligence and their links to the major themes in complexity science.
2. The second book is Waldrop's Complexity. This is another excellent book because it covers what Capra misses--the historical development of the Santa Fe Institute, the first and most important institute involved in the creation of complexity science and its most cutting-edge research. Almost every major figure in complexity science during the 1980s and 1990s had something to do with Santa Fe. Complexity is a bit journalistic and sensationalist (even gossipy) in style, but it really does give a good historical account of the early years of complexity science.
Most important about The Web of life and Complexity, they introduce you to all the major concepts of complexity science: emergence, self-organization, tipping-points, autopoiesis, self-organizing criticality, computational economics, cellular automata, agent-based modeling, fractals, chaos theory, networks, and so on.
These two books also introduce you to the major players during the 1980s and 1990s: from Holland and Kauffman to Prigogine and Bak to Matarana and Varela.
Once you have a basic sense of the field, you can move to a review of the methods of complexity science. Here is where things become more technical and less macro. You start to move down to the meso and even micro level, exploring specific topics like neural networks, agent-based modeling, the new science of networks, fractals, modeling complex systems, power laws, etc.
But, let's not get into the deep section of the pool too quick. I would get those two books and read them first.