Chapter 125 20.4 Questions Worth Asking

Kaufman once told a group of scientists: "We're used to dealing with billions and billions of things!" Anything in clusters is different: more aggregates, one triggering another Such interactions grow exponentially.At a certain point, the increasing diversity and number of aggregates reaches a critical value such that a certain number of aggregates in the system instantaneously form a spontaneous ring, a self-generating, self-supporting, self-transforming chemical network .As long as there is energy flowing in, the network will be active and the ring will not collapse. Codes, chemicals, or inventions that, under the right circumstances, can lead to new codes, chemicals, or inventions.Obviously, this is the pattern of life.One organism produces new organisms, which in turn create newer organisms.One gizmo (transistor) begets others (computers), which (computers) begets newer ones (virtual reality).Kaufman wanted to generalize this process mathematically as follows: functions generate new functions, and new functions generate other updated functions.

"Five years ago," recalls Kaufman, "Brian Goodwin [evolutionary biologist] and I were sitting in a World War I bunker somewhere in northern Italy during a storm talking about autocatalytic systems. .At that time, I had a profound understanding: Darwin’s natural selection is very similar to Adam Smith’s theory of the wealth of nations. Both have a pair of invisible hands. But after seeing Walter Fontana Before the work on autocatalytic systems, I had no idea how to proceed further. Fontana's work is really beautiful." I mentioned to Kaufman a controversial idea: Democracy is bound to emerge in any society where there is just the right level of communication and information connectivity.Where ideas flow freely and new ideas are generated, political organization eventually leads to democracy, the inevitable, powerful attractor of self-organization.Kaufman agreed with the idea: "In about 1958 or 1959, when I was a sophomore in college, I wrote a philosophy paper with a lot of enthusiasm and energy. I wanted to figure out why democracy would work. Very Clearly, democracy does not work because it is the rule of the majority. Today, 33 years later, I recognize that democracy is the mechanism that allows for relatively smooth compromises between conflicting minorities. It avoids ethnic We get stuck in solutions that are locally beneficial but globally unfavorable."

It is not difficult to imagine that Kaufman's Boolean logic network and random genome are the mapping of the way the city government and even the state capital work.Large-scale macro and general revolutions are avoided through constant micro-conflicts and small changes at the local level, without the system as a whole being in disarray or stagnant.While constant change is implemented in small towns, the country remains stable - which in turn creates an environment for small towns to be in a state of constant compromise.This circular support is another "stack-and-sit" game that also shows that such a system is dynamically similar to a self-supporting living system.

"It's just a gut feeling," Kaufman reminded me, "and you'll have your own experience—from Fontana's 'strings beget strings beget strings', to 'inventions beget inventions beget inventions', and then to cultural evolution, and then to the Wealth of Nations.” Kaufmann made no secret of his ambitions: “I was looking for a coherent picture that could connect everything: from the origin of life to the spontaneous order in gene regulatory systems. Emergence, to the emergence of adaptive systems, to the establishment of the non-equilibrium price of the optimal compromise between organisms, and then to the unknown laws similar to the second law of thermodynamics. This is a picture of everything being unified. I really think it is like this .And the question I'm working on now is: Can we prove that a finite set of functions can generate an infinite set of possibilities?"

I call it a "Kaufmann machine".A small collection of carefully chosen functions, connected into a self-generating loop, yields infinitely more complex functions.The natural world is full of Kaufmann machines.The development of eggs into giant whales is one example.The evolutionary machine that produced flamingos from bacteria over a billion years is another example.Can we make an artificial Kaufmann machine?Perhaps it would be more appropriate to call it a von Neumann machine, since von Neumann posed the same problem as early as the early 1940s.Could machines, he wondered, make machines more complex than themselves?Whatever it's called, the question remains one: How does complexity build itself?

"Usually, we can only proceed to the argument when the knowledge structure is established. So the key is to ask questions and ask questions." Kaufman warned me.During the conversation, I often heard Kaufman talking to himself.He would pick one out of a sea of ​​rambling speculations and look at it from all angles, over and over again. "How are you going to ask that question?" he asked himself cogently.He wants the question of all questions, not the answer of all answers. "Once you ask the right questions," he said, "there's a good chance you'll find some kind of answer."

Good question to ask—and that's exactly what Kaufman had in mind when he thought about self-organizing order in evolutionary systems.Kaufman confided to me, “Each of us seems to have some back-of-the-head question for which the answer is crucial. What confuses me is why everyone is asking questions.” On several occasions, I have felt that Stuart Kaufman, MD, philosopher, mathematician, theoretical biologist, and MacArthur Fellow, was deeply moved by the problem he was dealing with. troubled.The "order of disorder" defies traditional science, and may be rejected as such, by rejecting all theories of the underlying creative order in the universe.At a time when the scientific community was seeing runaway nonlinear butterfly effects in every aspect of the universe, Kaufman asked whether the butterflies of chaos could go to sleep.He awakens the overall design structure that may exist in the creation, and it is this structure that appeases disordered chaos and generates orderly calm.Many people are amazed when they hear this statement.It is Kaufman's main source of courage and energy to pursue and formulate this uniquely important problem: "It is no exaggeration to say that when I was 23 years old, I wanted to know how a chromosome with 100,000 genes controls different cell types. I think I've found something deep, I've found a deep problem. And I still think that. I think God has been so good to me."

"If you're going to write something about it," said Kaufman softly, "you've got to say it's just some crazy idea of ​​people. But if there's a situation where rules beget rules beget rules— In the words of John Wheeler—isn’t it amazing that the universe is an inward-looking system!? The universe makes its own rules and emerges from a self-consistent system. It is not impossible: quarks, gluons Create rules with atoms and elementary particles, and transform each other accordingly." Kaufman is convinced that his systems create themselves.He hopes to discover the means by which evolutionary systems control their own structure.When that picture of the network first popped into his head, he had a hunch that the answer to how evolution manages itself lay in those connections.He is not content to show how order emerges spontaneously and inevitably.He also believed that the control mechanism of this order also emerged spontaneously.To do this, he used a computer to simulate thousands of random combinations to see which connections would allow the population to have the greatest fitness. "Adaptability" refers to the ability of a system to adjust its internal connections to adapt to changes in the environment.Kaufman argues that organisms, such as Drosophila, adjust their genetic networks over time so that their result -- the fly's body -- is optimally adapted to the forces created by food, shelter and predation. Changes in the surrounding environment constituted by the person.The question worth asking is: what controls the evolution of the system?Can organisms themselves control their evolution?

The main variable studied by Kaufman is the connectivity of the network.In a sparsely connected network, each node is connected to only one or fewer nodes on average.In a connection-rich network, each node will connect to ten, hundreds, thousands or even millions of nodes.In theory, the upper limit of the number of connections per node is the total number of nodes minus one.In a network of one million nodes, each node can have one million minus one connection, that is, every node is connected to every other node.As a rough analogy, every employee at GM is directly connected to all 749,999 other employees.

In the process of changing the parameters of its GM network's connectivity, Kaufman discovered a fact that wouldn't have surprised the GM president.A system in which only a few individuals can influence other individuals is not adaptive.Too few connections to spread innovation, and the system will not evolve.By increasing the average number of connections between nodes, the system's resilience also increases, and it will "bounce back quickly" when encountering disturbances.When the environment changes, the system can still maintain stability.Such systems can evolve.The completely unexpected finding is that beyond a certain degree of connectivity, continuing to increase the degree of connectivity only reduces the fitness of the system as a whole.

Kaufman uses hills to describe this effect.The top of the hill is the sweet spot for flexibility.On one side of the mountain is a loosely connected system: sluggish and rigid; on the other side is an overconnected system: a deadlocked grid of countless check forces—each node is subject to many conflicting influences, making the whole system Severely paralyzed.Kaufman calls this extreme case the "catastrophe of complexity".To the surprise of many, this overconnection is not uncommon.In the long run, an overconnected system is no different from a mess. The best degree of connectivity is somewhere in the middle, which will give the network the most flexibility.Kaufman found this sweet spot in his network model.His colleagues at first had difficulty believing his results because it seemed counterintuitive.The optimal connectivity for the lean systems Kaufman studied was very low, "only in the single digits."In large networks with tens of thousands of members, the optimal connectivity of each member is less than 10.And some networks even reach performance peaks when the connectivity is less than 2!Massively parallel systems don't have to be overconnected in order to fit.As long as the coverage is adequate, even the smallest average number of connections should suffice. Kaufman's second unexpected finding was that this low optimum seemed to fluctuate little, no matter how many members a network consisted of.In other words, even if more members are added to the network, it does not need (in terms of overall system adaptability) to increase the number of connections between each node.Accelerating evolution by increasing the number of members rather than the average number of connections between members confirms what Craig Reynolds found in his artificial life swarms: you can add more and more members to a swarm without having to change its structure. Kaufman found that when the average number of connections in an organism or meson is less than two, the overall system is not flexible enough to keep up with changes.Without adequate internal communication among members of a group, problems cannot be solved as a group.More precisely, they divide into several isolated cliques, but there is no interaction between the cliques. With an ideal number of connections, the amount of information flowing between individuals is also in an ideal state, and the system as a whole can continuously find the best solution.Even with rapidly changing circumstances, the network remains stable and long-lived as a whole. Kaufman's law also states that fitness freezes when the degree of connectivity between individuals exceeds a certain value.When many actions depend on many other contradictory actions, nothing gets done.Using terrain as a comparison, the extreme connection creates extreme steepness, making any movement possible to fall from the adapted mountain top to the unsuited valley.Another way of saying this is that when too many people can tell everyone else what to do, bureaucratic zombies start to come back to life.Adaptability is bound to an interlocking grid.This low connectivity ceiling is surprising for a contemporary culture that values ​​the benefits of interconnectivity. Those of us postmodern with communication addiction should pay attention to this result.We are constantly increasing the total number of people in our networked society (15% monthly growth rate of global Internet users in 1993) and the number of people and places each member is connected to.In business and government, faxes, phone calls, spam, and vast interlinked databases actually increase the number of connections between everyone.Neither type of growth significantly improves the fitness of our system (society) as a whole.