Imitation of Life

Imitation of Life

How Biology Is Inspiring Computing

By Nancy Forbes

How scientists are using nature as model and metaphor to reinvent computing: a survey of an emerging field.





How scientists are using nature as model and metaphor to reinvent computing: a survey of an emerging field.

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.


Out of Print ISBN: 9780262062411 190 pp. | 6 in x 9 in 48 illus.


$20.00 X ISBN: 9780262562157 190 pp. | 6 in x 9 in 48 illus.


  • ...A whirlwind history, richer even than its subtitle suggests.


  • ...Forbes [is] an expert guide to the hottest research in a potentially revolutionary area of technology.


  • [T]hough the text is clearly written, it offers a lot of technical information. Recommended...

    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