Product Description

Recently, cellular automata machines with the size, speed, and flexibility for general experimentation at a moderate cost have become available to the scientific community. These machines provide a laboratory in which the ideas presented in this book can be tested and applied to the synthesis of a great variety of systems. Computer scientists and researchers interested in modeling and simulation as well as other scientists who do mathematical modeling will find this introduction to cellular automata and cellular automata machines (CAM) both useful and timely. Cellular automata are the computer scientist's counterpart to the physicist's concept of 'field' They provide natural models for many investigations in physics, combinatorial mathematics, and computer science that deal with systems extended in space and evolving in time according to local laws. A cellular automata machine is a computer optimized for the simulation of cellular automata. Its dedicated architecture allows it to run thousands of times faster than a general-purpose computer of comparable cost programmed to do the same task. In practical terms this permits intensive interactive experimentation and opens up new fields of research in distributed dynamics, including practical applications involving parallel computation and image processing. Contents: Introduction. Cellular Automata. The CAM Environment. A Live Demo. The Rules of the Game. Our First rules. Second-order Dynamics. The Laboratory. Neighbors and Neighborhood. Running. Particle Motion. The Margolus Neighborhood. Noisy Neighbors. Display and Analysis. Physical Modeling. Reversibility. Computing Machinery. Hydrodynamics. Statistical Mechanics. Other Applications. Imaging Processing. Rotations. Pattern Recognition. Multiple CAMS. Perspectives and Conclusions. Tommaso Toffoli and Norman Margolus are researchers at the Laboratory for Computer Science at MIT. Cellular Automata Machines is included in the Scientific Computation Series, edited by Dennis Cannon.

Product Details

• Amazon Sales Rank: #1016581 in Books
• Published on: 1987-04-22
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 200 pages

Customer Reviews

buy for the ideas, not the implementation
This is a terrific book that takes a step-by-step approach to cellular automata, especially for modelling. Within the first two chapters I had already found several interesting ideas for improving my own general-purpose automata program.

The part of the book that is most dated is the discussion of a specific hardware card and software designed for IBM PCs and ATs, and a specific dialect of Forth that can be used to program automata that will run on this card. Obviously this is no longer the mainstream approach to programming automata - even massively parallel systems programming has moved away from Forth. For me, I think of it as pseudo-code instead of a program example, and the book is still very very useful.

So on the whole, I would say this is a valuable addition to the bookshelf of any automata enthusiast.

How to reuse some older ideas
Acquired this book many years ago (early 199x). It was inspiring to read about efforts to produce dedicated hardware for cellular automata. Recently Stephen Wolfram's a new kind of science made me read this older book again. Then it was interesting to write a cellular automata program in C++ and afterwards in a mixed Python/C version. The rules to use were taken from this particular book. The general hardware nowadays has enough power to even program in a higher level language and still show adequate performance. In short: the book is inspiring and the presented rules can be used to investigate cellular automata.

Avoid
I came to this book after having seen it referenced in a number of more general books with chapters on cellular automata. The book describes numerous experiments in varying levels of detail that are suitable for running on cellular automata. The example experiments are both abstract (`Life' or `Parity' rules) and concrete (simulation of physical systems). Little attention is paid to simulating either social or biological processes. There is a lot here but the level of detail is poor. Many explanations of the simulations assume considerable knowledge of the physical systems being simulated or the weaknesses of other approaches that may used. The greatest weakness of this book is that it relies on a specific hardware implementation of a CA machine. All examples require this machine (a PC card) to be installed in your PC in order to run. This card appears to no longer be available (no supplier details are given in the book). The use of Forth (a language using reverse polish notation) to describe rules and the reliance on specific hardware makes the rules discussed difficult to implement on a software CA. The rules presented in the second half of the book are so tied to the hardware implementation of the unavailable PC card as to be impossible to translate directly into English-like rules. This is a definite dud.