Posted by **Nice_smile)** at Jan. 16, 2017

English | 1987 | ISBN: 0262200600 | 200 Pages | PDF | 14.45 MB

Posted by **tien1309** at Sept. 6, 2009

By Tommaso Toffoli, Norman Margolus

Publisher: The MIT Press | 200 pages | 1987-04-22 | ISBN: 0262200600 | PDF | 10.87 MB

Posted by **AvaxGenius** at Feb. 22, 2018

English | PDF,EPUB | 2018 | 350 Pages | ISBN : 3319655566 | 18.59 MB

This book explores Probabilistic Cellular Automata (PCA) from the perspectives of statistical mechanics, probability theory, computational biology and computer science. PCA are extensions of the well-known Cellular Automata models of complex systems, characterized by random updating rules.

Posted by **step778** at Dec. 19, 2017

2003 | pages: 353 | ISBN: 0195137183 | PDF | 22,6 mb

Posted by **ChrisRedfield** at Dec. 12, 2017

Published: 2017-05-28 | ISBN: 3319530429 | PDF | 467 pages | 7.34 MB

Posted by **ChrisRedfield** at Aug. 1, 2017

Published: 2013-03-06 | ISBN: 3642366627, 3642442048 | PDF | 320 pages | 45.52 MB

Posted by **thingska** at July 19, 2017

English | 2017 | ISBN: 3319586300, 9783319586304 | 201 Pages | PDF | 5.93 MB

Posted by **Jeembo** at June 9, 2017

English | 2016 | ISBN: 331944364X | 468 Pages | PDF | 90.2 MB

This book constitutes the proceedings of the 12th International Conference on Cellular Automata for Research and Industry, ACRI 2016, held in Fez, Morocco, in September 2014.

Posted by **AvaxGenius** at May 27, 2017

English | PDF | 2017 | 467 Pages | ISBN : 3319530429 | 7.3 MB

This book focuses on a coherent representation of the main approaches to analyze the dynamics of cellular automata. Cellular automata are an inevitable tool in mathematical modeling. In contrast to classical modeling approaches as partial differential equations, cellular automata are straightforward to simulate but hard to analyze.

Posted by **lengen** at April 18, 2017

English | Feb. 21, 1994 | ISBN: 0201626640 | 587 Pages | PDF | 188 MB

Are mathematical equations the best way to model nature? For many years it had been assumed that they were. But in the early 1980s, Stephen Wolfram made the radical proposal that one should instead build models that are based directly on simple computer programs. Wolfram made a detailed study of a class of such models known as cellular automata, and discovered a remarkable fact: that even when the underlying rules are very simple, the behavior they produce can be highly complex, and can mimic many features of what we see in nature.