7:00 – 5:00 ASRC MKT
- Complexity Explorables
- This page is part of the Research on Complex Systems Group at the Institute for Theoretical Biology at Humboldt University of Berlin.The site is designed for people interested in complex dynamical processes. The Explorables are carefully chosen in such a way that the key elements of their behavior can be explored and explained without too much math (There are a few exceptions) and with as few words as possible.
- Orli’s Flock’n Roll (Adjustable variables, but just having the alignment radius doesn’t have the same effect. Maybe a function of the slew rate?
- This explorable illustrates of an intuitive dynamic model for collective motion (swarming) in animal groups. The model can be used to describe collective behavior observed in schooling fish or flocking birds, for example. The details of the model are described in a 2002 paper by Iain Couzin and colleagues.
- Saving Human Lives: What Complexity Science and Information Systems can Contribute
- We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.
- Fooled around with the model definition section in the paper to bring forward the rate limited heading a bit.
- Had to fix several bug in the DC paper
- Worked with Aaron a lot on tweaking the introduction. T is reading it now. Assuming it’s done, the only thing remaining is the conclusion