Different goals in multiscale simulations and how to reach them

Pierrick Tranouez (1, 2) , Antoine Dutot (1)

1 LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes
2 IDEES - Identité et Différenciation de l’Espace, de l’Environnement et des Sociétés

In this paper we sum up our works on multiscale programs, mainly simulations. We first start with describing what multiscaling is about, how it helps perceiving signal from a background noise in a flow of data for example, for a direct perception by a user or for a further use by another program. We then give three examples of multiscale techniques we used in the past, maintaining a summary, using an environmental marker introducing an history in the data and finally using a knowledge on the behavior of the different scales to really handle them at the same time.

Mots clés: Multiscale; clustering; dynamic graphs; adaptation; incremental learning

Domaines: Intelligence artificielle [cs.AI]; Adaptation et Systèmes auto-organisés [nlin.AO]

Pierrick Tranouez, Antoine Dutot. Different goals in multiscale simulations and how to reach them. Bertelle, Cyrille; Duchamp, Gérard H.E.; Kadri-Dahmani, Hakima. Complex Systems and Self-organization Modelling, Springer, pp.29-39, 2009, Understanding Complex Systems, ⟨10.1007/978-3-540-88073-8⟩. ⟨hal-00430674⟩