Building upon Fast Multipole Methods to Detect and Model Organizations

Pierrick Tranouez (1) , Antoine Dutot (1)

1 LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes

Many models in natural and social sciences are comprised of sets of inter-acting entities whose intensity of interaction decreases with distance. This often leads to structures of interest in these models composed of dense packs of entities. Fast Multipole Methods are a family of methods developed to help with the calculation of a number of computable models such as described above. We propose a method that builds upon FMM to detect and model the dense structures of these systems.

Mots clés: Organization detection; structure management; multiscale; N body systems; hierarchical tree; code approximations

Domaines: Intelligence artificielle [cs.AI]

Pierrick Tranouez, Antoine Dutot. Building upon Fast Multipole Methods to Detect and Model Organizations. DCDIS Series B: Applications & Algorithms, 2009, 16 (4), pp.489 - 500. ⟨hal-00422358v1⟩