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.

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

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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

Published: Thu 18 Nov 2010. Modified: Mon 08 Apr 2019