• All complex systems are built up from numerous components which constantly drive large and small scale change, through common mechanisms, in the overall system.

• The mutual dance of interdependence among organisms is stressed as is the growing recognition of the central role of cooperation in fostering survival as contrasted with reliance on competition.

• Complex systems seem to operate and survive best when they operate on the edge of chaos and order and when behavior is organized from the bottom up.

• To effect a systems behavior or development one must appreciate its patterns and power, apply interventions judiciously, and don’t bet on a limited set of strategies.
  
  

Key Point: All complex systems are built up from numerous components which constantly drive large and small scale change, through common mechanisms, in the overall system.

• "Complex adaptive systems."...all seemed to share certain crucial properties...

• First...each of these systems is a network of many ‘agents’ acting in parallel...Furthermore...the control of a complex adaptive system tends to be highly dispersed...If there is to be any coherent behavior in the system, it has to arise from competition and cooperation among the agents themselves...

• Second...a complex adaptive system has many levels of organization, with agents at any one level serving as the building blocks for agents at a higher level...Furthermore, said Holland - and this was something he considered very important - complex adaptive systems are constantly revising and rearranging their building blocks as they gain experience...At some deep, fundamental level, said Holland, all these processes of learning, evolution, and adaptation are the same...

• Third...all complex adaptive systems anticipate the future...

• Finally, said Holland, complex adaptive systems typically have many niches, each one of which can be exploited by an agent adapted to fill that niche...Moreover, the very act of filling one niche opens up more niches - for new parasites, for new predators and prey, for new symbiotic partners. So new opportunities are always being created by the system. And that, in turn, means that it’s essentially meaningless to talk about a complex adaptive system being in equilibrium: the system can never get there. It is always unfolding, always in transition. In fact, if the system ever does reach equilibrium, it isn’t stable. It’s dead. And by the same token,...there’s no point in imagining that the agents in the system can ever "optimize" their fitness, or their utility...The space of possibilities is too vast; they have no practical way of finding the optimum. the most they can ever do is to change and improve themselves relative to what the other agents are doing." p. 145-148

• What Holland wanted to know was how evolution could explore this immense space of possibilities and find useful combinations of genes - without having to search over every square inch of territory...Indeed, thought Holland, that’s what this business of "emergence" was all about: building blocks at one level combining into new blocks at a higher level. It seemed to be one of the fundamental organizing principles of the world...Once a set of building blocks like this has been tweaked and refined and thoroughly debugged through experience...then it can generally be adapted and recombined to build a great many new concepts....And that, in turn, suggests a whole new mechanism for adaptation in general. Instead of moving through that immense space of possibilities step by step, so to speak, an adaptive system can reshuffle its building blocks and take giant steps." p. 167-170

• "Reproduction and crossover provided the mechanism for building blocks of genes to emerge and evolve together - and, not incidentally, provided a mechanism for a population of individuals to explore the space of possibilities with impressive efficiency. By the mid - 1960s, in fact, Holland had proved what he called this schema theorem, the fundamental theorem of genetic algorithms: in the presence of reproduction, crossover, and mutation, almost any compact cluster of genes that provides above-average fitness will grow in the population exponentially." p. 174
  
  

Key Point: The mutual dance of interdependence among organisms is stressed as is the growing recognition of the central role of cooperation in fostering survival as contrasted with reliance on competition.

• "Any given organism’s ability to survive and reproduce depends on what niche it is filling, what other organisms are around, what resources it can gather, even what its past history has been. "That shift in viewpoint is very important," says Holland. Indeed, evolutionary biologists consider it so important that they’ve made up a special word for it: organisms in an ecosystem don’t just evolve, they co-evolve. Organisms don’t change by climbing uphill to the highest peak of some abstract fitness landscape...(The fitness-maximizing organisms of classical population genetics actually look a lot like the utility-maximizing agents of neoclassical economics.) Real organisms constantly circle and chase one another in an infinitely complex dance of co-evolution." p. 259

• ...he wanted to understand a deep paradox in evolution: the fact that the same relentless competition that gives rise to evolutionary arms races can also give rise to symbiosis and other forms of cooperation...It was a fundamental problem is evolutionary biology - not to mention economics, political science, and all of human affairs. In a competitive world, why do organisms cooperate at all? Why do they leave themselves open to "allies" who could easily turn on them?" p. 262

• In a computer simulation game on competition versus cooperation, a tit for tat strategy (seek cooperation with your competitor, if reciprocated, keep cooperating; if cooperative approach is met by competition, compete back, if approach changes to cooperation, reciprocate) beat all other strategies repeatedly. "The conclusion was almost inescapable. Nice guys - or more precisely, nice, forgiving, tough, and clear guys - can indeed finish first." p. 264
  
  

Key Point: Complex systems seem to operate and survive best when they operate on the edge of chaos and order and when behavior is organized from the bottom up.

• "The most surprising lesson we have learned from simulating complex physical systems on computers is that complex behavior need not have complex roots...Indeed, tremendously interesting and beguilingly complex behavior can emerge from collections of extremely simple components." p.  279

• "...the way to achieve lifelike behavior is to simulate populations of simple units instead of one big complex unit. Use local control instead of global control. Let the behavior emerge from the bottom up, instead of being specified from the top down. And while you’re at it, focus on ongoing behavior instead of the final result." p. 280

• "Living systems are actually very close to this edge-of-chaos phase transition, where things are much looser and more fluid. And natural selection is not the antagonist of self-organization. It’s more like a law of motion - a force that is constantly pushing emergent, self-organizing systems toward the edge of chaos." p. 303
  
  

Key Point: To effect a systems behavior or development one must appreciate its patterns and power, apply interventions judiciously, and don’t bet on a limited set of strategies.

• "You can look at the complexity revolution in almost theological terms, he (Arthur) says. "The Newtonian clockwork metaphor is akin to standard Protestantism. Basically there’s order in the universe...The alternative - the complex approach - is total Taoist. In Taoism there is no inherent order... The universe in Taoism is perceived as vast, amorphous, and ever-changing... So we are part of this thing that is never changing and always changing. If you think that you’re a steamboat and can go up the river, you’re kidding yourself. Actually, you’re just the captain of a paper boat drifting down the river. If you try to resist, you’re not going to get anywhere. On the other hand, if you quietly observe the flow, realizing that you’re part of it, realizing that the flow is ever-changing and always leading to new complexities, then every so often you can stick an oar into the river and punt yourself from one eddy to another." "Notice that this is not a recipe for passivity, or fatalism," says Arthur. "This is a powerful approach that makes use of the natural nonlinear dynamics of the system. You apply available force to the maximum effect... The idea is to observe, to act courageously, and to pick your timing extremely well." p. 330 - 331

• "What has happened is that we’re beginning to lose our innocence, or naiveté, about how the world works. As we begin to understand complex systems, we begin to understand that we’re part of an ever-changing, interlocking, nonlinear, kaleidoscopic world. So the question is how you maneuver in a world like that. And the answer is that you want to keep as many options open as possible. You go for viability, something that’s workable, rather than what’s ‘optimal.’ A lot of people say to that, ‘Aren’t you than accepting second best?’ No, you’re not, because optimization isn’t well-defined anymore. What you’re trying to do is maximize robustness, or survivability, in the face of an ill-defined future." p. 333 - 334