- Paperback: 176 pages
- Publisher: MIT Press; New Ed edition (21 Oct 2005)
- Language English
- ISBN-10: 0262562154
- ISBN-13: 978-0262562157
- Product Dimensions: 22.7 x 15.4 x 1.4 cm
- Average Customer Review: 3.3 out of 5 stars See all reviews (3 customer reviews)
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Amazon Bestsellers Rank:
573,963 in Books (See Top 100 in Books)
- #12 in Books > Computers & Internet > Computer Science > Algorithms > Genetic
- #24 in Books > Scientific, Technical & Medical > Biology > Computer Modelling & Analysis
- #29 in Books > Computers & Internet > Computer Science > Artificial Intelligence > Neural Networks
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Review
"On the surface it seems that computing should be an attractive career for women, but for many it hasn't been. Margolis and Fisher give us a deep and nuanced insight into this troubling problem. No simplistic answers are offered, but rather the far richer perspectives of real human experience."--Wm. A. Wulf, President, National Academy of Engineering "...A whirlwind history, richer even than its subtitle suggests." John Doyle and Marie Csete Nature "...Forbes [is] an expert guide to the hottest research in a potentially revolutionary area of technology." Gilbert Taylor Booklist "Though the text is clearly written, it offers a lot of technical information. Recommended..." Susan B. Hagloch Library Journal "The analogies between computers and biological organisms have often been overstated, so I approached this book with modest expectations. I was pleased to find that it was often cautious and moderate, even as it described claims enthusiastically promoted by others. Forbes should be congratulated for presenting the case for 'bio-inspired computing' in a way that will make the controversies it evokes accessible to a very broad audience."--Joshua Lederberg, Professor Emeritus, Rockefeller University, 1958 Nobel Laureate in Medicine "Computer engineering and biology have so much to say to each other; Nancy Forbes catalyzes this conversation and let's us listen in via her engaging style. This book will appeal to technophiles, interdisciplinarians, and broad thinkers of all stripes."--George M. Church, Professor of Genetics, Harvard Medical School "How does our brain do such exquisitely complex things with such slow and unreliable components? Are there lessons here for building more capable and robust computers? Nancy Forbes gathers evidence from a wide variety of fields, providing a lively and accessible survey of what we know and don't know about these questions."--Wm. A. Wulf, President, National Academy of Engineering "*Imitation of Life* successfully presents the case that for the first time in history, we are able to engineer machines that can both borrow designs from the complexity of life, through computer science, and implement the algorithms of life, through nanotechnology."--Stan Williams, Senior Fellow, Hewlett-Packard Laboratories
Product Description
As computers and the tasks they perform become increasingly complex, researchers are looking to nature -- as model and as metaphor -- for inspiration. The organization and behavior of biological organisms present scientists with an invitation to reinvent computing for the complex tasks of the future. In Imitation of Life, Nancy Forbes surveys the emerging field of biologically inspired computing, looking at some of the most impressive and influential examples of this fertile synergy.Forbes points out that the influence of biology on computing goes back to the early days of computer science -- John von Neumann, the architect of the first digital computer, used the human brain as the model for his design. Inspired by von Neumann and other early visionaries, as well as by her work on the "Ultrascale Computing" project at the Defense Advanced Research Projects Agency (DARPA), Forbes describes the exciting potential of these revolutionary new technologies. She identifies three strains of biologically inspired computing: the use of biology as a metaphor or inspiration for the development of algorithms; the construction of information processing systems that use biological materials or are modeled on biological processes, or both; and the effort to understand how biological organisms "compute," or process information.Forbes then shows us how current researchers are using these approaches. In successive chapters, she looks at artificial neural networks; evolutionary and genetic algorithms, which search for the "fittest" among a generation of solutions; cellular automata; artificial life -- not just a simulation, but "alive" in the internal ecosystem of the computer; DNA computation, which uses the encoding capability of DNA to devise algorithms; self-assembly and its potential use in nanotechnology; amorphous computing, modeled on the kind of cooperation seen in a colony of cells or a swarm of bees; computer immune systems; bio-hardware and how bioelectronics compares to silicon; and the "computational" properties of cells.
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First Sentence
Since man's earliest efforts to build an electronic calculating machine, scientists and engineers have dreamed of constructing the ultimate artificial brain. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
Since man's earliest efforts to build an electronic calculating machine, scientists and engineers have dreamed of constructing the ultimate artificial brain. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Most Helpful Customer Reviews
4 of 4 people found the following review helpful
Format:Paperback
I read this book because it was on the reading list of an OU course on Natural and artificial intelligence (M366). As such I expected the book to cover the subject in some detail. In contrast to Geoffrey Cockayne (who has also reviewed this book) I found this book disappointing. I felt the treatment of the material was too shallow, even allowing for the fact this book is an overview of current research.
There is also a sense that the American author was somewhat inward looking towards the US when looking at researchers. The first 80% of the book mentioned American researches in abundance and, to my recollection, almost entirely ignored the rest of the world. This is not a true reflection of research projects relevant to the book. However the last 20% of the book did give brief mention to research in Japan, Switzerland and the U.K.
The author has also made some basic technical errors, reminiscent of the errors made by `technical authors' when writing `popular science' books. I would therefore put this book into that category. It is not a book that has much to offer for anyone who is studying the subject in any depth and is looking for meaningful detail.
On the positive side it does give a flavour of what is being researched.
Also note that this book was published in 2005 and the most recent source material quoted by the author was February 2003. At the time of writing this review in October 2009, this makes the material in the book six and a half years old which probably makes it out of date. The copy I received was a first edition.
There is also a sense that the American author was somewhat inward looking towards the US when looking at researchers. The first 80% of the book mentioned American researches in abundance and, to my recollection, almost entirely ignored the rest of the world. This is not a true reflection of research projects relevant to the book. However the last 20% of the book did give brief mention to research in Japan, Switzerland and the U.K.
The author has also made some basic technical errors, reminiscent of the errors made by `technical authors' when writing `popular science' books. I would therefore put this book into that category. It is not a book that has much to offer for anyone who is studying the subject in any depth and is looking for meaningful detail.
On the positive side it does give a flavour of what is being researched.
Also note that this book was published in 2005 and the most recent source material quoted by the author was February 2003. At the time of writing this review in October 2009, this makes the material in the book six and a half years old which probably makes it out of date. The copy I received was a first edition.
Format:Paperback|Amazon Verified Purchase
This book provides a very short introduction to bio-inspired computing and applications. It is useful to computer professionals who like to keep abreast of this exciting emerging field.
Highlights of how biology is inspiring computing include: 1) Artificial neural nets learn on their own and are useful for pattern recognition and industrial control systems. 2) Genetic algorithm is one form of evolutionary algorithm and is especially suited for large-scale optimization problem. 3) Cellular Automata is valuable as a simple model for globalized behaviour of physical systems in terms of localized relations. 4) Artificial life employs a bottom-up approach to construct adaptive and autonomous robots by evoluting simple elemental units into more complex system. 5) Recombinant DNA techniques enable a broad range of algorithmic operations to be used in DNA computing; so far, DNA computing is best adapted to small scale search problems. 5) Amorphous computing is concerned with the use of masses of bulk computational elements to solve problems; the system can reconfigure itself and its communications path to avoid broken parts. 6) Bioelectronics can provide significant advantages over traditional devices made with silicon; evolvable chips can change their own circuitry via evolutionary computation according to changes in task requirements or operating environment.
Highlights of how biology is inspiring computing include: 1) Artificial neural nets learn on their own and are useful for pattern recognition and industrial control systems. 2) Genetic algorithm is one form of evolutionary algorithm and is especially suited for large-scale optimization problem. 3) Cellular Automata is valuable as a simple model for globalized behaviour of physical systems in terms of localized relations. 4) Artificial life employs a bottom-up approach to construct adaptive and autonomous robots by evoluting simple elemental units into more complex system. 5) Recombinant DNA techniques enable a broad range of algorithmic operations to be used in DNA computing; so far, DNA computing is best adapted to small scale search problems. 5) Amorphous computing is concerned with the use of masses of bulk computational elements to solve problems; the system can reconfigure itself and its communications path to avoid broken parts. 6) Bioelectronics can provide significant advantages over traditional devices made with silicon; evolvable chips can change their own circuitry via evolutionary computation according to changes in task requirements or operating environment.
0 of 3 people found the following review helpful
Format:Paperback|Amazon Verified Purchase
Ms Forbes offers a well written survey of the various ways in which biology is inspiring new approaches to the design of both software and hardware. It is suitable both for the general reader and as an introduction to undergraduate studies in bio-computing.
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