Direct link to video

Direct link to video

Wikipage of the lecture: LectureOnChaosAndInstability

This lecture will discuss Chaos and instability. Students should be able to:

• Define chaos and differentiate it from randomness
• Understand pseudo random numbers and their role of in Agent Based Models
• Understand model bifurcations
• Understand the notion of attractors and attractor maps.

ToDo: Parameter sweeps in models are used to test for chaos and instability.

• Use the learning model that you are developing to test, if you have it done already. Alternatively, choose any model from NetLogo that you like, that has at least 2 parameters that can be varied.
• Think of a interesting experiment where you need to analyze a 2D parameter space.
• Decide which output metrics you will measure. Use one or two, to limit the amount of graphing.
• Think about the stop criterion, or limit the maximum number of ticks.
• Perform the experiments and report them as usual.

• Be aware that a parameter sweep can quickly get out of had in therms of computational time

• First, calculate the number of parameter points that you want to test.
• Then, time a single run to get a sense of the overall duration of the experiment
• Adapt your parameter space as necessary. You can either reduce the bounds, or increase the coarseness.
• Be aware that laptops can get very warm after hours of crunching numbers.

Below is a link to the lecture slides.