[en] Genetic type particle methods are increasingly used to sample from complex high-dimensional distributions. They have found a wide range of applications in applied probability, Bayesian statistics, information theory, and engineering sciences. Understanding rigorously these new Monte Carlo simulation tools leads to fascinating mathematics related to Feynman-Kac path integral theory and their interacting particle interpretations. In this chapter, we provide an introduction to the stochastic modeling and the theoretical analysis of these particle algorithms. We also illustrate these methods through several applications.
Disciplines :
Mathematics Computer science
Author, co-author :
Del Moral, Pierre; Univ Bordeaux 1, Inst Math Bordeaux, Ctr INRIA Bordeaux Sud Ouest, F-33405 Talence, France.
TANTAR, Alexandru-Adrian ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
TANTAR, Emilia ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Language :
English
Title :
On the Foundations and the Applications of Evolutionary Computing
scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.