• Title Cellular Automata And Complexity
• Authors Stephen Wolfram
• Publisher: Westview Press; First Printing edition (February 21, 1994)
• Paperback: 608 pages
• eBook: PDF files
• Language: English
• ISBN-10: 0201626640
• ISBN-13: 978-0201626643
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Book Description

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.

And based on this result, Wolfram began a program of research to develop what he called "A Science of Complexity". The results of Wolfram's work found many applications, from the so-called Wolfram Classification central to fields such as artificial life, to new ideas about cryptography and fluid dynamics.

This volume seems to be interesting for computer scientists, especially for those engaged in parallelization, and for physicists and chemists having to discover the basic rules of complex systems (by cellular computer simulation)

This book is a collection of Wolfram's original papers on cellular automata and complexity. Some of these papers are widely known in the scientific community; others have never been published before. Together, the papers provide a highly readable account of what has become a major new field of science, with important implications for physics, biology, economics, computer science and many other areas.

About the Authors

• Stephen Wolfram is a British-American computer scientist, physicist, and businessman. He is known for his work in computer science, mathematics, and in theoretical physics. In 2012, he was named a fellow of the American Mathematical Society.

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Related Book Categories:

• Control Theory, Robust/Robotics, and Automation
• Computational Complexity
• Artificial Intelligence
• Machine Learning
• Neural Networks
• Statistics, and SAS Programming
• Applied Mathematics

Read and Download Links:

• Cellular Automata And Complexity (Stephen Wolfram)
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