STEVEN JOHNSON EMERGENCE PDF
Steven Johnson begins with the amoeba-like slime mold cell. These cells . Emergence, by Steven Johnson deals with the topic of emergence. For me with no. EMERGENCE. THE CONNECTED LIVES. BRAINS, CITIES, AND SOFTWARE. ATCEVEN JOHNSON. In August of , a Japanese scientist named Toshiyuki . STEVEN JOHNSON 'ords, of a particular kind of emergent, self-organizing system. . about-and moddiog-die emergent intelligence of self-organizing.
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"Emergence will make understanding 'emerge' in your own head, as Steven Johnson explains a lot of phenomena you may not even have noticed." —Esther . Editorial Reviews. ecogenenergy.info Review. An individual ant, like an individual neuron, is just In the tradition of Being Digital and The Tipping Point, Steven Johnson, acclaimed as a "cultural critic with a poet's heart" (The Village Voice), takes. In the tradition of Being Digital and The Tipping Point, Steven Johnson, acclaimed as a "cultural critic with a poet's heart" (The Village Voice), takes readers on.
Emergence: The Connected Lives of Ants, Brains, Cities, and Software
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Getting this book is simple and easy. An individual ant alters its behaviour based on the behaviour of other ants that it happens to encounter; out of all those semi-random encounters, the higher-level order of the colony emerges. A neuron in your brain decides to fire or not to fire based on the input from other neurons to which it is connected. A given "block" in the game SimCity decides to raise or lower its crime rate or pollution levels based on the crime or pollution in neighbouring blocks.
All of these systems follow relatively simple rules, but they project those rules out over thousands or, in the case of the brain, billions of interacting agents. Given enough interactions, and given the right rules, something magical happens: the colony starts organising its workforce; the brain starts thinking; the simulated city comes to life on the screen. Guardian readers may already know something about emergent behavior if they've read books like Chaos, or Kevin Kelly's wonderful Out of Control.
But what's happening now is that our growing understanding of "bottom-up" intelligence is being channelled towards consumer-level software applications.
review: “Emergence” by Steven Johnson
Emergence, in other words, is becoming something that we interact with directly via our computers. For some time, researchers had understood that slime cells emitted a common substance called acrasin also known as cyclic AMP , which was somehow involved in the aggregation process. But until Keller began her investigations, the conventional belief had been that slime mold swarms formed at the command of pacemaker cells that ordered the other cells to begin aggregating.
Shafer showed how the pacemakers could use cyclic AMP as a signal of sorts to rally the troops; the slime mold generals would release the compounds at the appropriate moments, triggering waves of cyclic AMP that washed through the entire community, as each isolated cell relayed the signal to its neighbors.
Slime mold aggregation, in effect, was a giant game of Telephone—but only a few elite cells placed the original call. It seemed like a perfectly reasonable explanation. Much of the world around us can be explained in terms of command systems and hierarchies—why should it be any different for the slime molds?
Emergence : The Connected Lives of Ants, Brains, Cities and Software PDF eBOOK
While all observers agreed that waves of cyclic AMP did indeed flow through the slime mold community before aggregation, all the cells in the community were effectively interchangeable. None of them possessed any distinguishing characteristics that might elevate them to pacemaker status. But Keller and Segel took another, more radical approach.
Turing had focused primarily on the interactions between cells in a single organism, but it was perfectly reasonable to assume that the math would work for aggregations of free-floating cells.
And so Keller started to think: What if Shafer had it wrong all along? What if the community of slime mold cells were organizing themselves? What if there were no pacemakers?
If the slime cells pumped out enough cyclic AMP, clusters of cells would start to form. Cells would begin following trails created by other cells, creating a positive feedback loop that encouraged more cells to join the cluster.
If each solo cell was simply releasing cyclic AMP based on its own local assessment of the general conditions, Keller and Segel argued in a paper published in , then the larger slime mold community might well be able to aggregate based on global changes in the environment—all without a pacemaker cell calling the shots. The response was very interesting, Keller says now. For anyone who understood applied mathematics, or had any experience in fluid dynamics, this was old hat to them.
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Indeed, the pacemaker hypothesis would continue as the reigning model for another decade, until a series of experiments convincingly proved that the slime mold cells were organizing from below. It amazes me how difficult it is for people to think in terms of collective phenomenon, Keller says today. Thirty years after the two researchers first sketched out their theory on paper, slime mold aggregation is now recognized as a classic case study in bottom-up behavior.
We like to talk about life on earth evolving out of the primordial soup. We could just as easily say that the most interesting digital life on our computer screens today evolved out of the slime mold.
At the end of its course, that landslide had somehow conjured up a handful of fully credited scientific disciplines, a global network of research labs and think tanks, and an entire patois of buzzwords.
It also unearthed a secret history of decentralized thinking, a history that had been submerged for many years beneath the weight of the pacemaker hypothesis and the traditional boundaries of scientific research. People had been thinking about emergent behavior in all its diverse guises for centuries, if not millennia, but all that thinking had consistently been ignored as a unified body of work—because there was nothing unified about its body.
There were isolated cells pursuing the mysteries of emergence, but no aggregation. They were wrestling with local issues, in clearly defined fields: You can answer all of these questions without resorting to the sciences of complexity and self-organization, but those answers all share a common pattern, as clear as the whorls of a fingerprint.
But to see it as a pattern you needed to encounter it in several contexts. Only when the pattern was detected did people begin to think about studying self-organizing systems on their own merits.
Keller and Segel saw it in the slime mold assemblages; Jane Jacobs saw it in the formation of city neighborhoods; Marvin Minsky in the distributed networks of the human brain. What features do all these systems share? In the simplest terms, they solve problems by drawing on masses of relatively stupid elements, rather than a single, intelligent executive branch.
They are bottom-up systems, not top-down. They get their smarts from below. In a more technical language, they are complex adaptive systems that display emergent behavior. In these systems, agents residing on one scale start producing behavior that lies one scale above them: The movement from low-level rules to higher-level sophistication is what we call emergence.
Imagine a billiard table populated by semi-intelligent, motorized billiard balls that have been programmed to explore the space of the table and alter their movement patterns based on specific interactions with other balls.
For the most part, the table is in permanent motion, with balls colliding constantly, switching directions and speed every second. Because they are motorized, they never slow down unless their rules instruct them to, and their programming enables them to take unexpected turns when they encounter other balls.
Such a system would define the most elemental form of complex behavior: Say the local rules of behavior followed by the balls ended up dividing the table into two clusters of even-numbered and odd-numbered balls. That would mark the beginnings of emergence, a higher-level pattern arising out of parallel complex interactions between local agents. Yet out of those low-level routines, a coherent shape emerges.
Does that make our mechanized billiard table adaptive? Not really, because a table divided between two clusters of balls is not terribly useful, either to the billiard balls themselves or to anyone else in the pool hall. But, like the proverbial Hamlet -writing monkeys, if we had an infinite number of tables in our pool hall, each following a different set of rules, one of those tables might randomly hit upon a rule set that would arrange all the balls in a perfect triangle, leaving the cue ball across the table ready for the break.
That would be adaptive behavior in the larger ecosystem of the pool hall, assuming that it was in the interest of our billiards system to attract players.
The system would use local rules between interacting agents to create higher-level behavior well suited to its environment.
Emergent complexity without adaptation is like the intricate crystals formed by a snowflake:Getting this book is simple and easy. Not to mention the one-on-one interviews that are so crucial to a book like this one.
This book gives the readers many references and knowledge that bring positive influence in the future. We could just as easily say that the most interesting digital life on our computer screens today evolved out of the slime mold.
The slime mold spends much of its life as thousands of distinct single-celled units, each moving separately from its other comrades. Are you sure you want to delete this list? These organisms and objects do indeed have connected lives and relate as well to planning, community development, and citizen participation. In the coming years, the power of self-organization -- coupled with the connective technology of the Internet -- will usher in a revolution every bit as significant as the introduction of electricity.