This extended abstract proposes a surprisingly simple framework for the random generation of combinatorial configurations based on Boltzmann models. Random generation of possibly complex structured objects is performed by placingan appropriate measure spread over the whole of a combinatorial class. The resultingalg orithms can be implemented easily within a computer algebra system, be analysed mathematically with great precision, and, when suitably tuned, tend to be efficient in practice, as they often operate in linear time. © 2002 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Duchon, P., Flajolet, P., Louchard, G., & Schaeffer, G. (2002). Random sampling from Boltzmann principles. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2380 LNCS, pp. 501–513). Springer Verlag. https://doi.org/10.1007/3-540-45465-9_43
Mendeley helps you to discover research relevant for your work.