Complex Adaptive Systems

120 credits (MSc, 2 years )

The brain, the immune system and the formation of clouds, are all examples of complex adaptive systems comprising of many interacting components, often non-linear and dynamic, leading to multiple levels of collective structures and organization.

Inspired by complex adaptive systems in nature, several new methods for information processing have emerged: artificial neural networks resemble neurobiology; genetic algorithms and genetic programming are based on evolutionary processes in nature; the construction of artificial life, the design of autonomous robots and software agents are based on the behaviour of living systems.

Programme description

To understand the dynamics of increasingly complex phenomena where standard simulation methods are inadequate, stochastic algorithms, game theory, adaptive programming, self-similarity, chaos theory and statistical methods are used to describe and increase our understanding of complex systems in nature and society, in the end trying to predict the unpredictable.
Examples are gene-regulation networks, the motion of dust particles in turbulent air or the dynamics of financial markets.
One example is fluctuations of share and option prices determining the stability of our economy. Other examples are the dynamics of dust particles in the exhaust of diesel engines, the dynamics of biological or artificial populations, earthquake prediction, and last but not least adaptive learning: the problem of teaching a robot how to respond to unexpected changes in its environment.
Truly interdisciplinary and encompassing several theoretical frameworks, this programme provides you with a broad and thorough introduction to the theory of complex systems and its applications to the world around us. The programme is based on a physics perspective with a focus on general principles, but it also provides courses in information theory, computer science and optimisation algorithms, ecology and genetics as well as adaptive systems and robotics.
Location: Campus Johanneberg

Educational methods

Besides traditional lectures on simulation and theory of complex systems, the programme is largely based on numerical calculation and simulation projects and depending on course selection possibly practical work in the robotics lab.

 

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Programme content in detail, incl. syllabus and description of the courses

Learn more about the programme content, courses, opportunities, research and much more...
Meet students, teachers, alumni from Complex Adaptive Systems

Career opportunities

Training in "computational engineering" teaches students to model and analyse complex systems and the computer modelling and analytical skills acquired in the programme open up a wide range of possibilities on the employment market, in software development and consulting, in research and development, management, and in the financial sector.

Research connections

The content of the programme is closely connected to the research on genetics and turbulence, information theory and adaptive systems and robotics performed at Chalmers and the University of Gothenburg. There is also a lively exchange with international research groups and regular guest lectures on current research that is often directly related to the course material.
The programme also has a student project activity with the Fraunhofer-Chalmers Research Centre for Industrial Mathematics

​STUDENT INTERVIEW​
“I have made a Siri-app for football”
Dante Landa Vega, Mexico, Complex Adaptive System
Chat with Dante​

Why did you choose this programme?
–  I have a background in mechatronics and was very interested in Artifical neural networks. All the research in the field is now going into machine learning and deep learning is everywhere, in our cellphones, our computers and tablets and soon in our vehicles too. There seems to be a great demand in the industry for people that can develop Artifical intelligence and I wanted to be a part of that.

What have you been working on?
– I have created an intelligent agent like Siri, but it works only for football teams. I named it Fabio after a Mexican tradition that I have with my friends when we play FIFA. You can ask Fabio questions about your favourite football team and it returns information about when they are playing the next match, their results and images. It works with three different leagues: The Premier League in England, Bundesliga in Germany and La Liga in Spain. The application itself is in the shape of a football and when it finds some information it stars to bump and rotate. 

What do you like the most about your programme?
– The combination of theory and practice. Everything is built from scratch from a mathematical model, then passed on to code and then a system. And everything works from my first idea. When I finish a project, it keeps growing and improving without me which is very cool.

What do you want to do in the future?
– I would like to work with machine learning or deep learning for a company here in Sweden rather than having my own business or going for a PhD.

Published: Thu 18 Nov 2010. Modified: Wed 16 Oct 2019