Génération Aléatoire: Modèles, Méthodes, Algorithmes ANR-07-BLAN-0330-03
Contact : Michele.Soria (at) nulllip6.frDu 01/12/2007 au 30/11/2010
The goal of this project, "random generation: models, methods and algorithms", is to develop a set of fundamental methods and algorithms for the random generation of complex combinatorial structures. such objects appear in a variety of applications, especially in computer science. Random generation plays an important role in domains dealing with enormous volumes of data, for example in interaction networks (computer, sociological, biological networks); in this case, random generation allows the comparison of models and the evaluation of their adequacy for real data. random testing and model checking are two additional fields of application for random generation. one of the main issues there arises when choosing appropriate data for testing, and designing efficient methods for fast generation of this data. in many cases the problem can be described in terms of graphs or automata, so that the data are specified as paths, or words. in these cases where intensive generation is required, the samplers have to be very efficient.
LIAFA - Paris Diderot, IGM - Paris-Est, LRI - Paris-SudANRPlus d'informations ici …
Michele SORIA