Course code TPT09
Course title Emergence in complex systems
Institution TELECOM ParisTech
Course address TELECOM ParisTech - 46 rue Barrault - 75013 Paris
City Paris
Minimum year of study 4th year
Minimum level of English Good
Minimum level of French None
Key words

Complex systems, Collective Intelligence, Emergence, Evolution, Genetic Algorithms, Small World, Swarm Intelligence.


Language English
Professor responsible Jean-Louis DESSALLES
Participating professors
Number of places Minimum: 10, Maximum: 30, Reserved for local students: 5

Insect colonies, evolving species, economic communities, social networks are complex systems. Complex systems are collective entities, composed of many similar agents, that show emerging behaviour. Though the interactions between agents are too complex to be described, their collective behaviour often obeys much simpler rules. The objective of this course is to describe some of the laws that control emergent behaviour and allow to predict it. The course will address conceptual issues, at the frontier between biology and engineering. Each afternoon consists in a lab work session in which students will get an intuitive and concrete approach to phenomena such as genetic algorithms, ant-based problem solving, collective decision, cultural emergence or sex ratio in social insects.

Students who have a scientific curiosity for emerging phenomena in nature (evolution of species, self-organizing collective behaviour) and are interested in importing ideas from nature to engineering are welcome to this course.


Programme to be followed

The main topics studied in this module are:

- Biological evolution; Genetic algorithms, in which a virtual population evolves and collectively adapts to a particular problem or to a new environment.

- Swarm intelligence, as a model of natural phenomena and as a class of collective algorithms. They are used to address problems in which adaptability and robustness are essential.

- Emerging phenomena like morphogenesis, cooperation, segregation through symmetry breaking, and emergence in social networks. We show how these different models can be applied to concrete problems, such as message routing in communication networks, optimal resource allocation or the emergence of communication.

The notion of emergence is formally defined, as well as concepts like punctuated equilibria, scale invariance, implicit parallelism and autocatalytic phenomena.


All lectures and all materials are in English, so we expect students to be fluent in English. Lab work sessions are based on software written in Python. Mastery of the Python language is not required, but students who attend this course will be fluent in procedural object-oriented programming (Java, C++, Python or equivalent). They will get some knowledge of Python by themselves before the Athens week.



Course exam

 The pedagogy consists in alternating lectures and practical work on machines. Students are asked to use the software platform that is provided to them and to perform slight modifications. They will study emergent phenomena by themselves and develop their own personal (micro-)project.



Students will be evaluated based on the following tasks:

- Answers during Lab work sessions

- Small open question quiz

- A 5 min. presentation of their personal project

- A short written description of their personal project (+ source files)