Description: 'The whole is more than the sum of its parts', Aristotle
Complex systems are systems where the collective behavior of their parts entails emergence of properties that can hardly, if not at all, be inferred from properties of the parts. Examples of complex systems include ant-hills, ant themselves, human economies, climate, nervous systems, cells and living things, including human beings, as well as modern energy or telecommunication infrastructures.
This course will cover theory and some important aspects related to the modeling and analysis of complex systems. This knowledge will be useful also in your real life and at work. It will complete your top-down engineering skills with unconventional bottom-up techniques.
Keywords: Complex Systems, Unconventional Computation, Cellular Computation, Sparsely Connected Networks, Cellular Automata, State Space, Basin of Attraction, Boolean Networks, Emergent Properties, Biologically-Inspired Methods, Neural Networks, Agent-Based Models, Swarm, Evolution, Development, Life Universe and Everything.
Structure: Lectures are orginized as discussions on selected scientific publications. The students are ekpected to read the set of selected publications given before each meeting and come up with at least one topic for discussion for each paper.
Editor: Gunnar Tufte Contact address: Gunnar tufte Page updated: 17 09 2018