This work offers an enthralling look at how computer scientists have crossed the line between machines and living organisms. Despite being marvels of complexity and human ingenuity, computers are notoriously bad at learning new things and dealing with new situations. Researchers at the frontiers of computer science have turned to nature for solutions to the problem of machine adaptation and learning. By applying models of complex biological systems to the realm of computing machines, they have given rise to a new breed of adaptive software and hardware. In "Machine Nature", computer scientist Moshe Sipper takes readers on a thrilling journey to the terra nova of computing, to provide a compelling look at cutting-edge computers, robots, and machines now and in the decades ahead, including: "Embryonic" chips that self-heal and artificial immune systems that function like their biological counterparts to fight off computer viruses; DNA computing - a technique for building computers out of DNA instead of silicon; and the deeper questions arising from the arrival of machines that are adaptive, autonomous, lifelike, and perhaps - one day - living.
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? Fascinating, forward-looking, cutting edge computer science theory ? The author is on the front lines of computer science ? Elegantly written take on the near and far future of computing technologyFrom the Back Cover:
Machine and nature are not often used in the same sentence. The title of this book may seem, at first glance, to be an oxymoron. For what is natural about a machine? Our collective consciousness is filled with "unnatural machines," frightening Frankenstein monsters that lead their human creators into frozen wastelands of hubris. It is time to move beyond these dusty concepts of natural creation as ancient as the Greeks' Prometheus and take a fresh look at the nature of the machines around us.
In Machine Nature, computer scientist Moshe Sipper takes us on a thrilling journey to the terra nova of computing for a compelling look at cutting-edge computers, robots, and machines. Marvels of human ingenuity, computers have extended our reach far beyond the wildest dreams of our grandparents. Yet, for all of their amazing complexity, computers are notoriously bad at learning new things and dealing with new situations. Researchers at the frontiers of computer science have turned to Nature for solutions to this fundamental problem. By applying models of complex biological systems to the realm of computing machines, they have given rise to a new breed of adaptive software and hardware.
Undaunted, Sipper guides us through this brave new world in which machines and computers adapt, evolve, learn, heal, reason, and more as he explores the very latest technologies. He takes us into engineering labs to investigate "embryonic" chips that self-heal; bridges, artwork, and computer programs that evolve; fuzzy systems that tolerate human imprecision; robots that learn to walk; artificial immune systems that function like their biological counterparts to fight off computer viruses; DNA computing that hopes to replace silicon; and cellular computing, in which millions of tiny computers work in concert, like living cells. Finally, Sipper asks the question that quivers in all our minds when faced with such Promethean marvels: "Can our creations one day take on a life of their own?"
Standing at the front lines of computer theory and practice, Moshe Sipper speaks not just to the issues of today, but to the ideas that will bear fruit in generations to come, all the while unafraid to tackle the deeper questions arising from the arrival of machines that are adaptive, autonomous, lifelike, and perhaps one day living.
Moshe Sipper, Ph.D., is an Associate Professor in the Department of Computer Science at Ben-Gurion University in Israel and a Visiting Professor in the Logic Systems Laboratory at the Swiss Federal Institute of Technology in Lausanne. Dr. Sipper has published close to 100 scientific papers in the field of bio-inspired computing, and is the author of Evolution of Parallel Cellular Machines: The Cellular Programming Approach.
Journey to the front lines of computer science, where researchers have crossed the paths of machines and living organisms
"Many people feel they were born too late. Then there are those who deem themselves to have been born too early. I, for one, belong to this latter group. I like to envision a future in which our bodies are on a par with our imagination, where humans will have unchained their earthly shackles, and, perhaps most importantly, a future in which humanity's spirit finally matches its technological wizardry. Maybe that is why my research revolves around what might, prima facie, seem like science fiction: machines and computers that adapt, evolve, learn, heal, reason, and more accomplishing feats we usually associate only with Nature. . . ." From Machine Nature
What if Darwinian evolution could occur in machines? It can. Today, computing scientists are using evolution to create not only new objects, but indeed an entirely new way of creating objects. Evolving computer programs, malleable computer chips, self-healing machines braced with artificial immune systems, DNA-based computer "bodies," and entire symphonies of tiny computers that sing to each other like the cells of your own human body surely these are the dreams of scientists and creative writers alike. Not so. In Machine Nature, computer scientist and theorist Moshe Sipper takes us on a thrilling journey to the front lines of the latest computer technology, along the way tackling the difficult questions that arise from such Promethean marvels: What are the fundamental differences between the Nature-made and the human-made? And can our creations one day take on a life of their own? With elegance and intrepidity, Sipper guides us straight to the clockwork heart of this brave new world, opening our eyes along the way.
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Book Description McGraw-Hill, 2002. Hardcover. Book Condition: New. 1. Bookseller Inventory # DADAX0071387048
Book Description McGraw-Hill, 2002. Hardcover. Book Condition: New. book. Bookseller Inventory # 0071387048