Dep. Informatique & Réseaux
J-L. Dessalles ← Home page
Module Athens TPT-09
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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. Emergence occurs when a collectivity of elements or agents shows coherent organization instead of the kind of disorganization expected from the juxtaposition of their individual characteristics.
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.
An ant colony can find the shortest path in a complex environment;
A species can solve complex adaptation problems;
Economic agents may spontaneously reach a locally optimal allocation of resources.
Simple individual acts, in each case, produce non-trivial results at the collective level. These observations constitute a rich source of inspiration for innovative engineering solutions, such as optimization using genetic algorithms, or message routing in telecom networks.
The emergent behaviour of complex collective systems often goes against intuition. Its dynamics can be described through non-linear models that predict sudden transitions. Emergence is best apparent during those transitions. Its study consists in accounting for the appearance of collective patterns when individual, generally simple, behaviours are given as input.
The main techniques studied in this module are:
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