Descriptif

PREREQUISITES:

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). If needed, they will get some knowledge of Python by themselves before the Athens week. Some fluency in basic mathematics (e.g optimization) is required.

OBJECTIVES:

Insect colonies, evolving species, economic communities, social networks are complex systems. Complex systems are collective entities whose interactions lead to emerging behaviour. Though the detailed interactions between all agents are too complex to be described, their collective behaviour often obeys much simpler rules. The objective of this course is to present some of the laws that control emergent behaviour and may be used to predict it. The course will address conceptual issues, at the frontiers between biology, sociology and engineering.

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:

Swarm intelligence; feedback loops; Emerging phenomena; definition of emergence; biological evolution; genetic algorithms; punctuated equilibria; scale invariance; implicit parallelism; autocatalytic phenomena; multi-scale systems;

cooperation; altruism; social signalling.

Potential applications are robotic swarms, smart grids, smart cities, autonomous car networks, ecology and biodiversity, crowd behaviour, financial markets, social norms, mob phenomena on social media, ...

COURSE EXAM:

The pedagogy consists in alternating lectures and practical work on machines. 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 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 sessions

- Small open question quiz

- A 5 min. presentation of their personal project

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