Carte Algorithms for Random Generation and Counting: A Markov Chain Approach A. Sinclair

Algorithms for Random Generation and Counting: A Markov Chain Approach

A Markov Chain Approach

Autor: A. Sinclair
Limbă: engleză
Legare: Copertă tare
Editura: Springer, Basel
Disponibilitate: În depozitul extern
Expediem în 10-13 zile
550.51 lei
This monograph is a slightly revised version of my PhD thesis [86], com pleted in the Department of...

Informații despre carte

Autor
Limbă
engleză
Legare
Carte - Copertă tare
Publicat
1993
Pagini
147
EAN
9780817636586
ISBN
0817636587
Enbook ID
01399015
Editura
Greutate
408
Dimensiuni
156 x 234 x 11

Descriere completă

This monograph is a slightly revised version of my PhD thesis [86], com pleted in the Department of Computer Science at the University of Edin burgh in June 1988, with an additional chapter summarising more recent developments. Some of the material has appeared in the form of papers [50,88]. The underlying theme of the monograph is the study of two classical problems: counting the elements of a finite set of combinatorial structures, and generating them uniformly at random. In their exact form, these prob lems appear to be intractable for many important structures, so interest has focused on finding efficient randomised algorithms that solve them ap proxim~ly, with a small probability of error. For most natural structures the two problems are intimately connected at this level of approximation, so it is natural to study them together. At the heart of the monograph is a single algorithmic paradigm: sim ulate a Markov chain whose states are combinatorial structures and which converges to a known probability distribution over them. This technique has applications not only in combinatorial counting and generation, but also in several other areas such as statistical physics and combinatorial optimi sation. The efficiency of the technique in any application depends crucially on the rate of convergence of the Markov chain.

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