Multiagent system for flow management in complex systems: Development of a decision-support system in epidemiology

Complex systems regroup a considerable number of entities. The number and diversity of these is determinant for the evolution of the system. This Evolution is, in particular, by stochastic relations which link the actors of the system. This evolution is not very predictable. Our work is centred on the flow circulation modelling and comprehension that takes place between the elements of the system. Taking account of the various specifications of complex systems, MultiAgent Systems (MAS) represent one of the most adapted methods for their simulation. It is possible to represent the emergence of environmental phenomena as the consequence of the interactions of agents acting in parallel. A particular flow management application on which we work is to simulate the circulation of a parasite (Cryptosporidium parvum) in an ecosystem. The objective is to better understand the various infection episodes of host populations (animal or human) under specific constraints. Given. that this parasite is particularly resistant to the traditional disinfection methods, we want, in the long term, to produce an autonomous decision-support system in epidemiology which we have called Meta-MAS. The objective is to evaluate the factors acting in the parasite contamination and propagation.