25 min listen
The 10 features of complex systems: Part 1
The 10 features of complex systems: Part 1
ratings:
Length:
27 minutes
Released:
May 15, 2023
Format:
Podcast episode
Description
In most of our episodes so far, we've taken a single concept and looked at it through the context of a single example. But in this episode and the next, we're going to pull back the camera to get a bird's-eye view of complexity science, by exploring the features common to all complex systems.
We're joined again by Karoline Wiesner, Professor of Complexity Science in the Department of Physics and Astronomy at the University of Potsdam in Germany. In this episode, Karoline is going to explain four conditions that we see in complexity science: numerosity, disorder and diversity, feedback, and non-equilibrium. At the end of the episode, she's going to bring them all together to explain a central concept of complex systems: emergence.
Resources and links:
Karoline’s book ‘What Is a Complex System?’
Connect:
Simplifying Complexity on Twitter
Sean Brady on Twitter
Sean Brady on LinkedIn
Brady Heywood website
This show is produced in collaboration with Wavelength Creative. Visit wavelengthcreative.com for more information.
We're joined again by Karoline Wiesner, Professor of Complexity Science in the Department of Physics and Astronomy at the University of Potsdam in Germany. In this episode, Karoline is going to explain four conditions that we see in complexity science: numerosity, disorder and diversity, feedback, and non-equilibrium. At the end of the episode, she's going to bring them all together to explain a central concept of complex systems: emergence.
Resources and links:
Karoline’s book ‘What Is a Complex System?’
Connect:
Simplifying Complexity on Twitter
Sean Brady on Twitter
Sean Brady on LinkedIn
Brady Heywood website
This show is produced in collaboration with Wavelength Creative. Visit wavelengthcreative.com for more information.
Released:
May 15, 2023
Format:
Podcast episode
Titles in the series (40)
What makes ant colonies robust? by Simplifying Complexity