Once you start seeing complex adaptive systems – and it’s like a new pair of eyes – you start seeing them everywhere. You have those eyes because you’re seeing them in many different fields under many different names.
That’s why I find amazing about complex adaptive systems: whatever the input is, whether it’s been identified and tracked or randomness (can’t be identified and tracked to its source or it can’t be predicted ahead of time), the systems nevertheless incorporate this new data and make changes based upon this new information but not tied to the new information, as the very systems themselves have their own rules they follow which generate patterns.
Sadly, people who do not understand complex adaptive systems often impose an extra “order” on the generated patterns, using the effects to attempt to deduce a direct cause.
While this can work up to a point (think of classical mechanics: it works very well *most* of the time), it can’t account for everything, but it *is* possible to re-write classical systems as complex adaptive systems adding the necessary flexibility to incorporate not only classical systems but also novel patterns that do not follow the previously deduced order.
yes! But even more successfully than GR + QM because these complex adaptive systems operate on scales that we humans are capable of measuring using our tools.
What makes GR and QM especially difficult is so much of it lives in the world of pure mathematics which has its own set of limitations and assumptions.
But when it comes to studying, say, the behavior of ant colonies, or the behavior of bacteria colonies, or the activities of neurons acting “in concert” upon the emergence of thought, these things _are_ trackable and can be measured.
I find this very powerful indeed.
I don’t know what kind of computer you have, but if you ever want to do some experiments on your computer with some basic complex adaptive systems, https://ccl.northwestern.edu/netlogo/ is a surprisingly easy to use and powerful tool for basic modeling.
I was obsessed with it back in April 2017 and made a few videos. This one is on segregation. Complex adaptive systems works not only in the theoretical but the practical.
Another one I made. I’m not good at describing things but when I get excited about a topic (and complex adaptive systems grabs my interest about once or twice a year) I dive deep into it and always learn something new each time)
Some synonyms: You can substitute “rules” for “feedback loops” – because a rule is a feedback loop. You can also substitute “programming” or perhaps “responsive programming”.
An extremely simple feedback loop is an “if/then” loop or a “Do loop” in programming. A Do loop is a rule. A do loop is a feedback loop.
Complex systems can also be called “massively parallel”, equivalent to parallel processing in computing. Instead of a single decision, you’re now measuring the decisions of hundreds or thousands or millions of overlapping decisions being made, some simultaneously, some at different times or different speeds, both somewhat independently of each other but also passing messages or otherwise influenced by the others in the set.