Dynamics of Complex Systems 

The framework of the four series of meetings is roughly the same, each covering 6 to 7 weeks. Each week starts with a lecture addressing the statistical background and practical application of a particular aspect of the statistical technique in question. Afterward students complete assignments in order to obtain hands-on experience regarding this particular aspect. Each series of meetings is examined separately.

This course will discuss techniques which allow for the study of human behaviour from a complex systems perspective. Complexity research transcends the boundaries between the classical scientific disciplines and is a hot topic in physics, mathematics, biology, economy and psychology. Its focus is a description and explanation of behaviour based on interaction dominant dynamics: Many processes interact on different (time)scales and behaviour emerges out of those interactions through a process of self-organization or soft-assembly. Contrary to what the term might suggest, complexity research is often about finding simple models which are able to simulate a wide range of behaviour. This approach differs fundamentally from the more classical approaches where behaviour is caused by a system of many hidden (cognitive) components which interact in sequence as in a machine (component dominant dynamics). The most important difference is how 'change' and hence the time-evolution of a system is studied. The aim is to give students a broad introduction to the dynamical and non-linear models and analyses techniques from complex systems theory, as used in contemporary papers in many top journals in the fields of behavioural and cognitive science. Topics include: State Space Grid analysis; Analysis of fractal geometry (i.e. pink noise) in time series (Standardized Dispersion Analysis, Power Spectral Density Analysis); Nonlinear and chaotic time series analysis (Phase Space Reconstruction, (Cross) Recurrence Quantification Analysis); Growth Curve models; Potential Theory; Catastrophe Theory (Cusp model) and Dynamical Field Theory. No advanced level of mathematical knowledge is required for this course; a regular Bachelor or Master background in Psychology is sufficient.

Examination on July 2, 2012: 13.45-17.30 (with reservation)

The final assignment will be split up into two parts. One will be given after session 5 and will be about sessions 1-5 (Models & Simulation). The second part will be given after session 9 and will be about sessions 6-9 (Complex Signal Analysis).

This course is for students of the Research Master Behavioural Science. Other Research Master students and PhD students interested in this course have to contact the lecturer for permission. This course is not available for Bachelor and Master students.
If permission is granted please email this to .
The lecturer then will give research master students access to the course on BB. PhD students (RU and external) have to subscribe through http://www.ru.nl/socialewetenschappen/onderwijs/overig/aanschuifonderwijs
Registration for the course in OSIRIS can be done by the OSP (1st floor Spinoza building) by showing the mail in which the lecturer gives you permission to follow his course.