Roger > Roger's Quotes

“Everything affects everything else, and you have to understand that whole web of connections.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“An adaptive agent is constantly playing a game with its environment. What exactly does that mean? Distilled to the essence, what actually has to happen for game-playing agents to survive and prosper?

Two things, Holland decided: prediction and feedback.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“If you have a truly complex system," he says, "then the exact patterns are not repeatable. And yet there are themes that are recognizable. In history, for example, you can talk about 'revolutions,' even though one revolution might be quite different from another. So we assign metaphors. It turns out that an awful lot of policy-making has to do with finding the appropriate metaphor. Conversely, bad policy-making almost always involves finding inappropriate metaphors. For example, it may not be appropriate to think about a drug 'war,' with guns and assaults.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“Kauffman was in awe when he realized all this. Here it was again: order. Order for free. Order arising naturally from the laws of physics and chemistry. Order emerging spontaneously from molecular chaos and manifesting itself as a system that grows. The idea was indescribably beautiful.

But was it life? Well no, Kauffman had to admit, not if you meant life as we know it today. An autocatalytic set would have had no DNA, no genetic code, no cell membrane. In fact, it would have had no real independent existence except as a haze of molecules floating around in some ancient pond. If an extraterrestrial Darwin had happened by at the time, he (or it) would have been hard put to notice anything unusual. Any given molecule participating in the autocatalytic set would have looked pretty much like any other molecule. The essence was not to be found in any individual piece of the set, but in the overall dynamics of the set: its collective behavior.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“Here was this elusive "Santa Fe approach": Instead of emphasizing decreasing returns, static equilibrium, and perfect rationality, as in the neoclassical view, the Santa Fe team would emphasize increasing returns, bounded rationality, and the dynamics of evolution and learning. Instead of basing their theory on assumptions that were mathematically convenient, they would try to make models that were psychologically realistic. Instead of viewing the economy as some kind of Newtonian machine, they would see it as something organic, adaptive, surprising, and alive. Instead of talking about the world as if it were a static thing buried deep in the frozen regime, as Chris Langton might have put it, they would learn how to think about the world as a dynamic, ever-changing system poised at the edge of chaos.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“Through feedback, said Wiener, Bigelow, and Rosenblueth, a mechanism could embody purpose.

Even today, more than half a century later, that assertion still has the power to fascinate and disturb. It arguably marks the beginning of what are now known as artificial intelligence and cognitive science: the study of mind and brain as information processors. But more than that, it does indeed claim to bridge that ancient gulf between body and mind—between ordinary, passive matter and active, purposeful spirit. Consider that humble thermostat again. It definitely embodies a purpose: to keep the room at a constant temperature. And yet there is nothing you can point to and say, "Here it is—this is the psychological state called purpose." Rather, purpose in the thermostat is a property of the system as a whole and how its components are organized. It is a mental state that is invisible and ineffable, yet a natural phenomenon that is perfectly comprehensible.

And so it is in the mind, Wiener and his colleagues contended. Obviously, the myriad feedback mechanisms that govern the brain are far more complex than any thermostat. But at base, their operation is the same. If we can understand how ordinary matter in the form of a machine can embody purpose, then we can also begin to understand how those three pounds of ordinary matter inside our skulls can embody purpose—and spirit, and will, and volition. Conversely, if we can see living organisms as (enormously complex) feedback systems actively interacting with their environments, then we can begin to comprehend how the ineffable qualities of mind are not separate from the body but rather inextricably bound up in it.”
― M. Mitchell Waldrop, The Dream Machine: J.C.R. Licklider and the Revolution That Made Computing Personal

“Nonetheless, his vision of high technology’s enhancing and empowering the individual, as opposed to serving some large institution, was quite radical for 1939—so radical, in fact, that it wouldn’t really take hold of the public’s imagination for another forty years, at which point it would reemerge as the central message of the personal-computer revolution.”
― M. Mitchell Waldrop, The Dream Machine

“Instead of storing those countless microfilmed pages alphabetically, or according to subject, or by any of the other indexing methods in common use—all of which he found hopelessly rigid and arbitrary—Bush proposed a system based on the structure of thought itself. "The human mind . . . operates by association," he noted. "With one item in its grasp, it snaps instantly to the next that is suggested by the association of thoughts, in accordance with some intricate web of trails carried by the cells of the brain. . . . The speed of action, the intricacy of trails, the detail of mental pictures [are] awe-inspiring beyond all else in nature." By analogy, he continued, the desk library would allow its user to forge a link between any two items that seemed to have an association (the example he used was an article on the English long bow, which would be linked to a separate article on the Turkish short bow; the actual mechanism of the link would be a symbolic code imprinted on the microfilm next to the two items). "Thereafter," wrote Bush, "when one of these items is in view, the other can be instantly recalled merely by tapping a button. . . . It is exactly as though the physical items had been gathered together from widely separated sources and bound together to form a new book. It is more than this, for any item can be joined into numerous trails."

Such a device needed a name, added Bush, and the analogy to human memory suggested one: "Memex." This name also appeared for the first time in the 1939 draft.

In any case, Bush continued, once a Memex user had created an associative trail, he or she could copy it and exchange it with others. This meant that the construction of trails would quickly become a community endeavor, which would over time produce a vast, ever-expanding, and ever more richly cross-linked web of all human knowledge.

Bush never explained where this notion of associative trails had come from (if he even knew; sometimes things just pop into our heads). But there is no doubt that it ranks as the Yankee Inventor's most profoundly original idea. Today we know it as hypertext. And that vast, hyperlinked web of knowledge is called the World Wide Web.”
― M. Mitchell Waldrop, The Dream Machine: J.C.R. Licklider and the Revolution That Made Computing Personal

“Indeed, except for the very simplest physical systems, virtually everything and everybody in the world is caught up in a vast, nonlinear web of incentives and constraints and connections. The slightest change in one place causes tremors everywhere else. We can't help but disturb the universe, as T.S. Eliot almost said. The whole is almost always equal to a good deal more than the sum of its parts. And the mathematical expression of that property-to the extent that such systems can be described by mathematics at all-is a nonlinear equation: one whose graph is curvy.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“Why is it that simple particles obeying simple rules will sometimes engage in the most astonishing, unpredictable behavior?”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“Like it or not, the marketplace isn’t stable. The world isn’t stable. It’s full of evolution, upheaval, and surprise.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“As a thought experiment, von Neumann's analysis was simplicity itself. He was saying that the genetic material of any self-reproducing system, whether natural or artificial, must function very much like a stored program in a computer: on the one hand, it had to serve as live, executable machine code, a kind of algorithm that could be carried out to guide the construction of the system's offspring; on the other hand, it had to serve as passive data, a description that could be duplicated and passed along to the offspring.

As a scientific prediction, that same analysis was breathtaking: in 1953, when James Watson and Francis Crick finally determined the molecular structure of DNA, it would fulfill von Neumann's two requirements exactly. As a genetic program, DNA encodes the instructions for making all the enzymes and structural proteins that the cell needs in order to function. And as a repository of genetic data, the DNA double helix unwinds and makes a copy of itself every time the cell divides in two. Nature thus built the dual role of the genetic material into the structure of the DNA molecule itself.”
― M. Mitchell Waldrop, The Dream Machine: J.C.R. Licklider and the Revolution That Made Computing Personal

“Complex systems are more spontaneous, more disorderly, more alive than that. At the same time, however, their peculiar dynamism is also a far cry from the weirdly unpredictable gyrations known as chaos. In the past two decades, chaos theory has shaken science to its foundations with the realization that very simple dynamical rules can give rise to extraordinarily intricate behavior; witness the endlessly detailed beauty of fractals, or the foaming turbulence of a river. And yet chaos by itself doesn't explain the structure, the coherence, the self-organizing cohesiveness of complex systems. Instead, all these complex systems have somehow acquired the ability to bring order and chaos into a special kind of balance. This balance point—often called the edge of chaos—is were the components of a system never quite lock into place, and yet never quite dissolve into turbulence, either. The edge of chaos is where life has enough stability to sustain itself and enough creativity to deserve the name of life. The edge of chaos is where new ideas and innovative genotypes are forever nibbling away at the edges of the status quo, and where even the most entrenched old guard will eventually be overthrown. The edge of chaos is where centuries of slavery and segregation suddenly give way to the civil rights movement of the 1950s and 1960s; where seventy years of Soviet communism suddenly give way to political turmoil and ferment; where eons of evolutionary stability suddenly give way to wholesale species transformation. The edge of chaos is the constantly shifting battle zone between stagnation and anarchy, the one place where a complex system can be spontaneous, adaptive, and alive. Complexity, adaptation, upheavals at the edge of chaos—these common themes are so striking that a growing number of scientists are convinced that there is more here than just a series of nice analogies. The movement's nerve center is a think tank known as the Santa Fe Institute, which was founded in the mid-1980s and which was originally housed in a rented convent in the midst of”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“Most obviously, they agreed, an autocatalytic set was a web of transformations among molecules in precisely the same way that an economy is a web of transformations among goods and services. In a very real sense, in fact, an autocatalytic set was an economy-a submicroscopic economy that extracted raw materials (the primordial "food" molecules) and converted them into useful products (more molecules in the set).

Moreover an autocatalytic set can bootstrap its own evolution in precisely the same way that an economy can, by growing more and more complex over time. This was a point that fascinated Kauffman. If innovations result from new combinations of old technologies, then the number of possible innovations would go up very rapidly as more and more technologies became available. In fact, he argued, once you get beyond a certain threshold of complexity you can expect a kind of phase transition analogous to the ones he had found in his autocatalytic sets. Below that level of complexity you would find countries dependent upon just a few major industries, and their economies would tend to be fragile and stagnant. In that case, it wouldn't matter how much investment got poured into the country. "If all you do is produce bananas, nothing will happen except that you produce more bananas." But if a country ever managed to diversify and increase its complexity above the critical point, then you would expect it to undergo an explosive increase in growth and innovation-what some economists have called an "economic takeoff."

The existence of that phase transition would also help explain why trade is so important to prosperity, Kauffman told Arthur. Suppose you have two different countries, each one of which is subcritical by itself. Their economies are going nowhere. But now suppose they start trading, so that their economies become interlinked into one large economy with a higher complexity. "I expect that trade between such systems will allow the joint system to become supercritical and explode outward."

Finally, an autocatalytic set can undergo exactly the same kinds of evolutionary booms and crashes that an economy does. Injecting one new kind of molecule into the soup could often transform the set utterly, in much the same way that the economy transformed when the horse was replaced by the automobile. This was part of autocatalysis that really captivated Arthur. It had the same qualities that had so fascinated him when he first read about molecular biology: upheaval and change and enormous consequences flowing from trivial-seeming events-and yet with deep law hidden beneath.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“Theoretical economists use their mathematical prowess the way the great stags of the forest use their antlers: to do battle with one another and to establish dominance.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“Most obviously, they agreed, an autocatalytic set was a web of transformations among molecules in precisely the same way that an economy is a web of transformations among goods and services. In a very real sense, in fact, an autocatalytic set was an economy—a submicroscopic economy that extracted raw materials (the primordial “food” molecules) and converted them into useful products (more molecules in the set). Moreover, an autocatalytic set can bootstrap its own evolution in precisely the same way that an economy can, by growing more and more complex over time. This was a point that fascinated Kauffman. If innovations result from new combinations of old technologies, then the number of possible innovations would go up very rapidly as more and more technologies became available. In fact, he argued, once you get beyond a certain threshold of complexity you can expect a kind of phase transition analogous to the ones he had found in his autocatalytic sets. Below that level of complexity you would find countries dependent upon just a few major industries, and their economies would tend to be fragile and stagnant. In that case, it wouldn’t matter how much investment got poured into the country. “If all you do is produce bananas, nothing will happen except that you produce more bananas.” But if a country ever managed to diversify and increase its complexity above the critical point, then you would expect it to undergo an explosive increase in growth and innovation—what some economists have called an “economic takeoff.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“> In effect, though Wiener didn't quite express it this way, cybernetics was offering an alternative to the Skinnerian worldview, in which human beings were just stimulus-response machines to be manipulated and conditioned for their own good. It was likewise offering an alternative to von Neumann's worldview, wherein human beings were unrealistically rational technocrats capable of anticipating, controlling, and managing their society with perfect confidence. Instead, cybernetics held out a vision of humans as neither gods nor clay but rather "machines" of the new kind, embodying purpose—and thus, autonomy. No, we were not the absolute masters of our universe; we lived in a world that was complex, confusing, and largely uncontrollable. But neither were we helpless. We were embedded in our world, in constant communication with our environment and one another. We had the power to act, to observe, to learn from our mistakes, and to grow. "From the point of view of cybernetics, the world is an organism," Wiener declared in his autobiography. "In such a world, knowledge is in its essence the process of knowing. . . . Knowledge is an aspect of life which must be interpreted while we are living, if it is to be interpreted at all. Life is the continual interplay between the individual and his environment rather than a way of existing under the form of eternity.”
― M. Mitchell Waldrop, The Dream Machine: J.C.R. Licklider and the Revolution That Made Computing Personal

“The word "emergence" seemed to crop up frequently. And most of all, there was this incredible energy and camaraderie in the air-a sense of barriers crumbling, a sense of new ideas let loose, a sense of spontaneous, unpredictable, open-ended freedom. In an odd, intellectual sort of way, the artificial life workshop felt like a throwback, like something right out of the Vietnam-era counterculture.

And, of course, in an odd, intellectual sort of way, it was.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“So for James, too, will derives not from the freedom to initiate thoughts, but to focus on and select some while stifling, blocking-or vetoing-others. For Buddhist mindfulness practice, it is the moment of restraint that allows mindful awareness to take hold and deepen. The essence of directed mental force is first to stop the grinding machine-like automaticity of the urge to act. Only then can the wisdom of the prefrontal cortex be actively engaged.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“In fact, the fourteen programs submitted in the first round of the tournament embodied a variety of complex strategies. But much to the astonishment of Axelrod and everyone else, the crown went to the simplest strategy of all: TIT FOR TAT. Submitted by psychologist Anatol Rapoport of the University of Toronto, TIT FOR TAT would start out by cooperating on the first move, and from there on out would do exactly what the other program had done on the move before. That is, the TIT FOR TAT strategy incorporated the essence of the carrot and the stick. It was "nice" in the sense that it would never defect first. It was "forgiving" in the sense that it would reward good behavior by cooperating the next time. And yet it was "tough" in the sense that it would punish uncooperative behavior by defecting the next time. Moreover, it was "clear" in the sense that its strategy was so simple that the opposing programs could easily figure out what they were dealing with.

Of course, with only a handful of programs entered in the tournament, there was always the possibility that TIT FOR TAT's success was a fluke. But maybe not. Of the fourteen programs submitted, eight were "nice" and would never defect first. And every one of them easily outperformed the six not-nice rules. So to settle the question Axelrod held a second round of the tournament, specifically inviting people to try to knock TIT FOR TAT off its throne. Sixty-two entrants tried-and TIT FOR TAT won again. The conclusion was inescapable. Nice guys-or more precisely, nice, forgiving, tough, and clear guys-can indeed finish first.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“all these complex systems have somehow acquired the ability to bring order and chaos into a special kind of balance. This balance point—often called the edge of chaos—is were the components of a system never quite lock into place, and yet never quite dissolve into turbulence, either.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“In non linear systems-and the economy is most certainly nonlinear-chaos theory tells you that the slightest uncertainty in your knowledge of the initial conditions will often grow inexorably. After a while, your predictions are nonsense.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“At the same time, Kaufmann discovered that in developing his genetic networks, he had reinvented some of the most avant-garde work in physics and applied mathematics-albeit in a totally new context. The dynamics of his genetic regulatory networks turned out to be a special case of what the physicists were calling "nonlinear dynamics." From the nonlinear point of view, in fact, it was easy to see why his sparsely connected networks could organize themselves into stable cycles so easily: mathematically, their behavior was equivalent to the way all the rain falling on the hillsides around a valley will flow into a lake at the bottom of the valley. In the space of all possible network behaviors, the stable cycles were like basins-or as the physicists put it, "attractors.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“Furthermore, Kauffman felt that it might ultimately be possible to apply these ideas far beyond the economy. "I think these kinds of models are the place for contingency and law at the same time," he says. "The point is that the phase transitions may be lawful, but the specific details are not. So maybe we have the starts of models of historical, unfolding processes for such things as the Industrial Revolution, for example, or the Renaissance as a cultural transformation,a nd why it is that an isolated society, or ethos, can't stay isolated when you start plugging some new ideas into it." You can ask the same thing about the Cambrian explosion: the period some 570 million years ago when a world full of algae and pond scum suddenly burst forth with complex, multicellular creatures in immense profusion. "Why all of a sudden do you get all this diversity?" Kauffman asks. "Maybe you had to get to a critical diversity to then explode. Maybe it's because you've gone from algal mats to something that's a little more trophic and complex, so that there's an explosion of processes acting on processes to make new processes. It's the same thing as in an economy.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“Instead of relying on the Newtonian metaphor of clockwork predictability, complexity seems to be based on metaphors more closely akin to the growth of a plant from a tiny seed, or the unfolding of a computer program from a few lines of code, or perhaps even the organic, self-organized flocking of simpleminded birds. That's certainly the kind of metaphor that Chris Langton has in mind with artificial life: his whole point is that complex, lifelike behavior is the result of simple rules unfolding from the bottom up. And it's likewise the kind of metaphor that influenced Arthur in the Santa Fe economics program: "If I had a purpose, or a vision, it was to show that the messiness and the liveliness in the economy can grow out of an incredibly simple, even elegant theory. That's why we created these simple models of the stock market where the market appears moody, shows crashes, takes off in unexpected directions, and acquires something that you could describe as a personality.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“But now Holland was beginning to realize just how prescient Samuel's focus on games had really been. This game analogy seemed to be true of any adaptive system. In economics the payoff is in money, in politics the payoff is in votes, and on and on. At some level, all these adaptive systems are fundamentally the same. And that meant, in turn, that all of them are fundamentally like checkers or chess: the space of possibilities is vast beyond imagining. An agent can learn to play the game better-that's what adaptation is, after all. But it has just about as much chance of finding the optimum, stable equilibrium point of the game as you or I have of solving chess.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“However, he added, there is one big difference: "Our particles in economics are smart, whereas yours in physics are dumb." In physics, an elementary particle has no past, no experience, no goals, no hopes or fears about the future. It just is. That's why physicists can talk so freely about "universal laws": their particles respond to forces blindly, with absolute obedience. But in economics, said Arthur, "Our particles have to think ahead, and try to figure out how other particles might react if they were to undertake certain actions. Our particles have to act on the basis of expectations and strategies. And regardless of how you model that, that's what makes economics truly difficult.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“Competition and cooperation may seem antithetical,” he says, “but at some very deep level, they are two sides of the same coin.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos

“Lick was unique in bringing to the field a deep appreciation for human beings: our capacity to perceive, to adapt, to make choices, and to devise completely new ways of tackling apparently intractable problems. As an experimental psychologist, he found these abilities every bit as subtle and as worthy of respect as a computer’s ability to execute an algorithm. And that was why to him, the real challenge would always lie in adapting computers to the humans who used them, thereby exploiting the strengths of each.”
― M. Mitchell Waldrop, The Dream Machine

“In contrast to mainstream artificial intelligence, I see competition as much more essential than consistency," he says. Consistency is a chimera, because in a complicated world there is no guarantee that experience will be consistent. But for agents playing a game against their environment, competition is forever. "Besides," says Holland, "despite all the work in economics and biology, we still haven't extracted what's central in competition." There's a richness there that we've only just begun to fathom. Consider the magical fact that competition can produce a very strong incentive for cooperation, as certain players spontaneously forge alliances and symbiotic relationships with each other for mutual support. It happens at every level and in every kind of complex, adaptive system, from biology to economics to politics. "Competition and cooperation may seem antithetical," he says, "but at some very deep level, they are two sides of the same coin.”
― M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos