Excerpt from: Machine Nature (New York: McGraw-Hill, 2002)
PROLOGUE
Adaptation, Bio-Inspiration, Complexity: A New Computing ABC
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 fiction science: machines and computers that adapt, evolve, learn, heal, reason--and more, accomplishing feats that we usually associate only with Nature. But this seemingly fictional science is in fact quite real. Much of the work is carried out by daring, creative researchers who incessantly push at the frontiers of knowledge, with some of their ideas having already found their way into products such as automobiles and washing machines.
During the past few years a new wind has been sweeping through the computing terrain, slowly changing our fundamental view of computers. We want them to be faster, better, more efficient--and proficient--at their tasks. But that's just part of the story. The other part, and in my mind the more exciting, is that we've come to expect computers to stop being so stiff.
Computers are rigid, unbending, unyielding, inflexible, and quite unwieldy. Let's face it, they've improved our lives in many a way, but they do tend to be a pain. When interacting with them you have to be very methodical and precise, in a manner quite contrary to human nature. Step outside the computer's programmed repertoire of behavior, it will simply refuse to cooperate, or--even worse--it will "crash" (a vivid term coined by computing professionals to describe a computer's breaking down). Computers are notoriously bad at learning new things and at dealing with new situations. It all adds up to one thing: At their most fundamental, computers lack the ability to adapt.
Adaptation concerns a system's ability to undergo modifications according to changing circumstances, thus ensuring its continued functionality. We often speak of an environment and of the system's adjustment to changing environmental conditions. The archetypal examples of adaptive systems are not among human creations, but among Nature's. From bacteria to bumblebees, natural organisms show a striking capacity to adapt to changing circumstances, a quality that has not escaped the eyes of computing scientists and engineers. The influence of the biological sciences in computing is on the rise, slowly but surely inching its way toward the mainstream. There are many examples today of systems inspired by biology, known as bio-inspired systems.
These adaptive, bio-inspired systems are complex, which refers to more than their simply being complicated objects or to the difficulty of building and comprehending them. As Peter Coveney and Roger Highfield wrote in Frontiers of Complexity: "Within science, complexity is a watchword for a new way of thinking about the collective behavior of many basic but interacting units, be they atoms, molecules, neurons, or bits within a computer. To be more precise, our definition is that complexity is the study of the behavior of macroscopic collections of such units that are endowed with the potential to evolve in time.Their interactions lead to coherent collective phenomena, so-called emergent properties that can be described only at higher levels than those of the individual units. In this sense, the whole is more than the sum of its components...."
Natural organisms are complex adaptive systems, and our artifacts are now beginning to follow in their footsteps. Adaptation, Bio-inspiration, and Complexity thus underlie the new computing ABC.
PROLOGUE
Adaptation, Bio-Inspiration, Complexity: A New Computing ABC
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 fiction science: machines and computers that adapt, evolve, learn, heal, reason--and more, accomplishing feats that we usually associate only with Nature. But this seemingly fictional science is in fact quite real. Much of the work is carried out by daring, creative researchers who incessantly push at the frontiers of knowledge, with some of their ideas having already found their way into products such as automobiles and washing machines.
During the past few years a new wind has been sweeping through the computing terrain, slowly changing our fundamental view of computers. We want them to be faster, better, more efficient--and proficient--at their tasks. But that's just part of the story. The other part, and in my mind the more exciting, is that we've come to expect computers to stop being so stiff.
Computers are rigid, unbending, unyielding, inflexible, and quite unwieldy. Let's face it, they've improved our lives in many a way, but they do tend to be a pain. When interacting with them you have to be very methodical and precise, in a manner quite contrary to human nature. Step outside the computer's programmed repertoire of behavior, it will simply refuse to cooperate, or--even worse--it will "crash" (a vivid term coined by computing professionals to describe a computer's breaking down). Computers are notoriously bad at learning new things and at dealing with new situations. It all adds up to one thing: At their most fundamental, computers lack the ability to adapt.
Adaptation concerns a system's ability to undergo modifications according to changing circumstances, thus ensuring its continued functionality. We often speak of an environment and of the system's adjustment to changing environmental conditions. The archetypal examples of adaptive systems are not among human creations, but among Nature's. From bacteria to bumblebees, natural organisms show a striking capacity to adapt to changing circumstances, a quality that has not escaped the eyes of computing scientists and engineers. The influence of the biological sciences in computing is on the rise, slowly but surely inching its way toward the mainstream. There are many examples today of systems inspired by biology, known as bio-inspired systems.
These adaptive, bio-inspired systems are complex, which refers to more than their simply being complicated objects or to the difficulty of building and comprehending them. As Peter Coveney and Roger Highfield wrote in Frontiers of Complexity: "Within science, complexity is a watchword for a new way of thinking about the collective behavior of many basic but interacting units, be they atoms, molecules, neurons, or bits within a computer. To be more precise, our definition is that complexity is the study of the behavior of macroscopic collections of such units that are endowed with the potential to evolve in time.Their interactions lead to coherent collective phenomena, so-called emergent properties that can be described only at higher levels than those of the individual units. In this sense, the whole is more than the sum of its components...."
Natural organisms are complex adaptive systems, and our artifacts are now beginning to follow in their footsteps. Adaptation, Bio-inspiration, and Complexity thus underlie the new computing ABC.
"Much have I travell'd in the realms of gold, And many goodly states and kingdoms seen," wrote John Keats. In the next chapter we begin our voyage to the frontiers of computing, a veritable journey into realms of gold. Each chapter adds a bead to our ABC chain, a chain that defines what I call the Terra Nova of computing, where computers do all those things we'd like them to do.
With our newly won knowledge of all these novel lands in the Terra Nova of computing, it is time to dig a little deeper:
I hold the strong conviction that research should not be judged by its immediate applicability. True, some projects will find their way into commercial products almost immediately. Yet the seeds we sow today may give rise to marvelous trees of knowledge 20 or 30 years hence. And I believe firmly that society at large will benefit from such an outlook. I cannot help but be reminded of the story of William Gladstone who, as Chancellor of the Exchequer, was invited to a demonstration of Michael Faraday's equipment for generating the latest scientific wonder at the time--electricity. Faraday set up the experiment and ran it, while Gladstone looked coolly on. After the demonstration, Gladstone stood silent for a moment, and then said: "It is very interesting, Mr. Faraday, but what practical worth is it?" Undaunted, Faraday replied: "One day, sir, you may tax it." My research-for-tomorrow position notwithstanding, most of the topics covered in this book are studied today both by cutting-edge researchers and by stern industrialists.
While the devil may be in the details, I've tried to be angelic by writing about the important, basic principles without any unexplained technical jargon. Also, this book tries to appeal to your imagination as much as to your reason. As Albert Einstein said, "Imagination is more important than knowledge."
Before we begin our journey, a small remark about sex. One of the problems in modern English writing concerns the use of the gender pronouns. I've applied Occam's razor, opting for the simplest solution: I use one or the other entirely at whim.
In Through the Looking-Glass Lewis Carroll wrote:
"The time has come," the Walrus said,
"To talk of many things:
Of shoes--and ships--and sealing wax--
Of cabbages--and kings--
And why the sea is boiling hot--
And whether pigs have wings."
Indeed.
- Darwinian evolution occurs only in nature? No longer. In Chapter 1 we will see how engineers use evolution to create not only new objects, but indeed an entirely new way of creating objects.
- Are computer programmers industrious? Not all of them. As we'll see in Chapter 2, some of them are quite lazy, reclining comfortably in their swivel chairs while evolution does all the work: evolving computer programs.
- "Why doesn't a computer ever learn?" you've probably asked yourself 53 times over the past week alone. As we'll see in Chapter 3, they actually canlearn, given the right incentive.
- Why do R2D2 and C3PO exist only on the silver screen? In Chapter 4 we'll see what researchers in adaptive robotics are doing to correct this unfortunate situation.
- Why doesn't your computer understand such a simple phrase as "It's a bit warm in here"? In Chapter 5 we'll consider computers that can talk and reason in a fuzzy manner, able to come to grips with phrases such as "a bit" and "warm"--just like us.
- Computer hardware is too hard and unyielding? In Chapter 6 we'll meet the latest in computer-chip technology: soft hardware, namely, computer chips that are malleable.
- Can we do something about computers breaking down much more easily than we do? I shudder to think what would happen if I were to crash three times a day. And even when we do crash, we humans have wonderful bodies that are often able to heal. As we'll learn in Chapter 7, computers are beginning to experience the joys of healing.
- Wouldn't it be nice to equip your computer with an immune system, to ward off all those nasty viruses lurking in the dark corners of cyberspace? In Chapter 8 we'll talk about immune systems for computers.
- Will silicon circuits ever behave like carbon beings? This fundamental gap between the two (somewhat less obvious in California) is starting to close with the advent of DNA computing, a topic we shall encounter in Chapter 9.
- Your body is made up of gazillions of tiny cells that work in concert to produce the symphony you call "I." In Chapter 10 we'll listen to the music of cellular computers.
With our newly won knowledge of all these novel lands in the Terra Nova of computing, it is time to dig a little deeper:
- In Chapter 11 we'll ask: What are the fundamental differences between Nature-made and the human-made?
- If we let evolution run loose in a computer, then who controls the process? Who's the boss? We'll tackle that one in Chapter 12.
- What do you get when you cross a scientist and an engineer? A scigineer, of course. We'll meet this hybrid fellow in Chapter 13.
- Can our creations one day take a life of their own? Now there's a truly big question. You'll have to wait till Chapter 14 to learn more about this one.
- Finally, in Chapter 15, we'll pick up where we've started here, going from "ABC" all the way up to "Z."
I hold the strong conviction that research should not be judged by its immediate applicability. True, some projects will find their way into commercial products almost immediately. Yet the seeds we sow today may give rise to marvelous trees of knowledge 20 or 30 years hence. And I believe firmly that society at large will benefit from such an outlook. I cannot help but be reminded of the story of William Gladstone who, as Chancellor of the Exchequer, was invited to a demonstration of Michael Faraday's equipment for generating the latest scientific wonder at the time--electricity. Faraday set up the experiment and ran it, while Gladstone looked coolly on. After the demonstration, Gladstone stood silent for a moment, and then said: "It is very interesting, Mr. Faraday, but what practical worth is it?" Undaunted, Faraday replied: "One day, sir, you may tax it." My research-for-tomorrow position notwithstanding, most of the topics covered in this book are studied today both by cutting-edge researchers and by stern industrialists.
While the devil may be in the details, I've tried to be angelic by writing about the important, basic principles without any unexplained technical jargon. Also, this book tries to appeal to your imagination as much as to your reason. As Albert Einstein said, "Imagination is more important than knowledge."
Before we begin our journey, a small remark about sex. One of the problems in modern English writing concerns the use of the gender pronouns. I've applied Occam's razor, opting for the simplest solution: I use one or the other entirely at whim.
In Through the Looking-Glass Lewis Carroll wrote:
"The time has come," the Walrus said,
"To talk of many things:
Of shoes--and ships--and sealing wax--
Of cabbages--and kings--
And why the sea is boiling hot--
And whether pigs have wings."
Indeed.