URL : https://www.complexityexplorer.org/courses/119-introduction-to-complexity
I enrolled on this in August 2021. I see it as a bit of a refresher on what I did in [[Evolutionary and adaptive systems]]. And to give me a fun intro to [[agent-based modelling]] with [[NetLogo]].
And then, the aim would be, to be followed up by some study of [[Systems thinking]]. They’re related, but slightly different. See [[Complex Adaptive Systems, Systems Thinking, and Agent-Based Modeling]].
That I can then apply to questions around [[political organisation]], [[climate change]], and [[social network]]s.
In this course you’ll learn about the tools used by scientists to understand [[complex systems]]. The topics you’ll learn about include dynamics, chaos, fractals, information theory, self-organization, agent-based modeling, and networks. You’ll also get a sense of how these topics fit together to help explain how complexity arises and evolves in nature, society, and technology.
Some examples of complex systems given are [[ant colonies]], [[the brain]], [[social network]]s, the web, the human genome, the economy, [[food webs]], the [[immune system]], cities.
I’m probably most interested in the [[networks]] complex systems. But they’re all interesting.
Biological, social, technological.
dynamics : the study of continually changing structure and behaviour of systems
information : the study of representation, symbols, and communication
computation : the study of how systems process information and act on the results
evolution : the study of how systems adapt to constantly changing environments
experimental work
theoretical work
computer simulation
This course has a focus on computer simulation of complex systems.
Hard to define… lots of definitions. We’ll look at [[Shannon information]] and [[Fractal dimension]].
NetLogo is super simple to set up and get running the demos. The Ants model is very cool - foraging for food sources and finding the closest thanks to pheromone trails. This is the kind of thing I faffed around with graphics programming on in my Masters, surely would have been easier to use a pre-built system for it. I wonder why we didn’t…
I really like the way it’s presented, in that it gets you thinking about how the agent-based models might run and their dynamics. And it also makes you make predictions as to how changes in parameters and behaviours might change the dynamics. Thinking a bit more scientifically about it. Making a prediction and testing it with an experiment.
I also love the NetLogo agent-based modelling stuff because it is very much thinking visually. When some result isn’t what you expected, you actually view the behaviour on screen.
[[Dynamics]] is the science of how systems change over time. How does behaviour unfold and how does it change over time.
e.g. planetary dynamics; fluid dynamics; electrical dynamics; climate dynamics; crowd dynamics; population dynamics; financial dynamics; group dynamics; dynamics of conflicts and dynamics of cooperation.
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