Complexity: The Emerging Science at the Edge of Order and Chaos


Explanations of complexity, self-organization, emergence, order and chaos and some of the pioneers behind this work. It also details the history of the Santa Fe Institute

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  1. Explanations of complexity, self-organization, emergence, order and chaos and some of the pioneers behind this work. It also details the history of the Santa Fe Institute
Key Takeaways
  1. Complex systems – many individual agents interacting and outcomes difficult to predict
    1. Complexity is the science of emergence
  2. Spontaneous self-organization (organization with no central conductor) found all over nature
    1. Complex systems all over nature have somehow acquired ability to bring order and chaos into a special kind of balance – the edge of chaos. The components of the system never lock into place yet never 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; 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.
    2. Self-organization is the most powerful force in biology and living systems operate at the edge of chaos
      1. Evolution always seems to lead to the edge of chaos
  3. Them that has, gets – domino effect once tipping point hits leads to cascades and often winner-take-all systems
  4. The crucial skill is insight. The ability to see connections
  5. At some fundamental level that Brian Arthur didn’t yet understand, the phenomena of physics and biology are the same
    1. Self-organization found everywhere! – positive feedback, increasing returns, lock-in (more niches dependent on a technology, the harder it is to change that technology until something vastly better comes along), unpredictability, tiny events that have immense consequences all seem to be a re-requisite for life itself
  6. Must look at world how it is, not as some elegant theory says it ought to be
  7. Essence of science lies in explanation more than prediction
  8. Increasing returns prominent when marginal cost is minimal (software for example)
  9. Nearly everything and everybody caught up in non-linear web of incentives, constraints and connections
  10. Innovations never happen in a vacuum and often come from someone who is outside the field
  11. Catalysis everywhere and life wouldn’t be possible without it – molecules could have catalyzed the formation of other molecules so that those in the web would have taken over. The web would keep growing and would have catalyzed its own formation, it would become an autocatalytic set – order for free
    1. Autocatalytic set can bootstrap its own creation and evolution by growing more and more complex over time and will also experience booms and busts from small changes
  12. Complex adaptive systems – characterized by perpetual novelty; dispersed, hierarchical, learn / adapt / evolve, anticipate the future
    1. Can never get to equilibrium as new opportunities are always being created by the system – always unfolding, always in transition
  13. Emergence is hierarchical – building blocks at one level combining into new blocks at a higher level. Hierarchies are one of the fundamental organizing principles of the world. Found everywhere because a well-designed hierarchy is an excellent way of getting some work done without any one person being overwhelmed or having to know everything. Also, utterly transforms a system’s ability to learn, evolve and adapt – can reshuffle building blocks and take giant leaps. Can describe a great many complicated things from relatively few building blocks
  14. Adaptive agents always playing game with environment for fitness requires feedback and prediction
    1. In order to learn, must be able to take advantage of what the world is trying to tell it
  15. Implicit expertise – a huge, interlocking set of standard operating procedures that have been inscribed on the nervous system and refined by years of experience
    1. Competition much more essential than consistency
    2. Competition and cooperation may seem antithetical but at some very deep level, they are two sides of the same coin (leading to symbiosis across nature, tit for tat strategy)
  16. Self-reproduction requires medium to be both data and instructions (DNA)
    1. von Neumann and cellular automata
  17. Spectrums:
    1. Dynamical systems: Order – Complexity – Chaos
      1. Complexity is emergent, dynamical, characterized by phase transitions
      2. Interesting things always happen at the edge of chaos
    2. Matter: Solid – Phase Transition – Liquid
      1. First and second order phase transitions – sharp and precise phase transitions (molecules forced to make either or choice between order and chaos) compared to second order which is much less common in nature – much less abrupt because molecules don’t need to make an either-or choice, they combine order and chaos (fluid with pockets of solid or vice versa)
    3. Computation: Halting – “Undecidable” – Nonhalting
    4. Life: too static – “life / intelligence” – too noisy
  18. Life is based to a great degree on its ability to process and store information and then mapping it out to determine proper action
  19. Always ask, “optimal relative to what?
  20. Artificial life – effort to understand life by synthesis, putting together simple pieces to generate lifelike behavior in man-made systems. Its credo is that life is not a property of matter per se, but the organization of that matter
    1. ‘Aliveness’ lies in the organization of the molecules and not the molecules themselves
    2. Fact that simple rules leads to unpredictability is reason trial and error (Darwinian natural selection), although somewhat crude and ‘wasteful’ is the best strategy in nature and evolution
    3. If organization determines life, it shouldn’t matter what it is made of if properly organized
    4. Complex, life-like behavior is the result of simple rules unfolding from the bottom up
  21. Emergence – somehow, by groups of agents cooperating and seeking self-accommodation, they manage to transcend themselves and become something more where the whole is greater than the sum of the parts
  22. Power truly lies in connections – exploitation (improving what you already have) vs. exploration (taking big risk for big reward)
  23. Edge of chaos – found right in between order and chaos, aka complexity
    1. Stable enough to store information but evanescent enough to transmit it
    2. Observe systems in terms of how they behave instead of how they are made
    3. Systems which are too controlled, too stagnant, too locked in will perish
    4. Healthy economies and societies must balance order and chaos via feedback and regulation while leaving room for creativity, change and response to new conditions – “evolution thrives in systems with a bottom-up organization which gives rise to flexibility”
    5. Information has to flow from the bottom-up and from the top-down
    6. Learning and evolution move agents along the edge of chaos towards ever greater complexity, sophistication and functionality
      1. One of the greatest questions and mysteries is why life gains ‘quality’ and becomes more complex over time. It is also one of the most fascinating and profound clues as to what life is all about
  24. Complex phenomena of life only associated with molecular scale due to variety and reactivity
  25. Tao of complexity – there is no duality between man and nature, we are all part of this interlocking network
    1. Once this is realized, conversation changes from optimality to co-adaptation and accommodation – what would be good for the system as a whole
    2. You keep as many options open as possible and go for what’s workable, rather than what’s ‘optimal’
    3. Optimization isn’t well defined anymore. Rather, what you’re trying to do is maximize robustness, or survivability, in the face of an ill-defined future
What I got out of it
  1. Ties together a lot of fascinating concepts and drew some more light on phase transitions and complexity for me

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