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Complex Adaptive Systems

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Analysing Complexity

Университет Маккуори

4.7 (оценок: 49) | Зарегистрировано учащихся: 5.2K

Курс 1 из 4 — Solving Complex Problems Специализация

Просмотреть программу курса

The first course of the specialization ANALYZING COMPLEXITY will teach you what unifying patterns lie at the core of all complex problems. It advances your knowledge of your own field by teaching you to look at it in new ways. ANALYZING COMPLEXITY is constructed in the following way: Week I. "What is Complexity?" - What is at the core of all complex problems Week II. "Complex Physical Systems" - What complex problems all have in common in the inanimate world Week III. "Complex Adaptive Systems" - What complex problems all have in common in nature Week IV. "Complex Cultural Systems" - What complex problems all have in common in human society Week V. "Complexity, Fragility, and Breakdown" - Why complex problems arise Week VI. "Complexity in the Anthropocene" - What complex problems face us today

Рецензии

4.7 (оценок: 49)

5 stars
38 ratings
4 stars
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3 stars
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TA

Oct 24, 2017

You should study Complexity from this course if you are interesting in complex system.

TW

Apr 23, 2017

Super interesting course, I have never seen in my lifetime.\n\nWatch me ;))

Из урока

Complex Adaptive Systems

In this module, we'll explore the ratcheting up of complexity inside adaptive systems, and the impact adaptation has on the rules of the game for constantly evolving complex systems.

Complex Adaptive Systems6:03

Преподаватели

David Baker
Associate Lecturer
David Christian
Professor
Shawn Ross
Associate Professor

The big question for this segment is what are complex adaptive systems?

And why should we care?

[MUSIC]

We've seen that even the simplest complex systems can be fiendishly complex.

Now we shift to a level of even more fiendish complexity.

With what complexity theorists call complex adaptive systems.

In the complex physical systems that we've looked at so

far, the individual components, say the atoms or

electrons or the squares in cellular automata are quite well behaved.

So we can sort of predict their behavior.

It's not easy if there are billions of components.

But we can get some sort of grip on them.

Now with complex adaptive systems, the individual components behave badly.

An example is the stock market, a horribly complex system generated by the behavior

of millions of brokers, buyers and sellers and computers.

All of them behaving in unpredictable ways.

The number of moving parts here is much greater and suddenly, it's much,

much harder to predict the behavior of the system as a whole.

In fact, it's so hard to predict the behavior of complex adaptive systems.

Think of your dog.

That it often seems that each system is acting with perverse intent.

That it has its own goals and it's working through a sort of weird do list.

With complex adaptive systems, we enter a new level of complexity.

And explaining how we get to that level is well, extremely complex.

We begin to see new feedback loops that can speed up change or dampen it down.

We see unexpected tipping points of which things suddenly change.

We see chaotic things, suddenly seem to self-organize into more complex things.

We see tiny changes cascading to produce huge butterfly effects,

just as the assassination of a member of the Hapsburg royal family on June

the 28th, 1914.

Unleash the cascade of events that led to World War I.

The first complex adaptive systems we know of are living organisms.

We really don't know how widespread life is in the universe,

though we may get some clues in the next few decades.

But even explaining how life appeared on Earth

remains one of the hardest problems facing modern science.

Any explanation, let's begin with geology and chemistry.

Explaining how and why the young Earth proved such a wonderful environment for

complex chemistry.

An environment in which atoms and molecules could combine

to form increasingly exotic combinations that seemed to work together.

Exactly how we got from large organic molecules,

such as proteins, to the first prokaryotic cells remains tough to explain.

The first living organisms were single celled prokaryotes,

made up of many billions of molecules organized with exquisite precision.

They could tap free energy from their surroundings and could reproduce over and

over again.

So that individuals slowly evolved and adapted to different environments.

This is the beginning of biology.

This module begins with the discussion of the role of free energy

in living organisms.

And how evolution seemed to generate increasing biological complexity.

But it also reminds us that more complex things,

are not necessarily more robust or efficient than simple things.

Perhaps simple things like the strange little organisms known as tardigrades

are actually tougher than more complex organisms.

Tardigrades it seems can survive high doses of radiation and

short periods in space.

Prokaryotes are much simpler but even tougher.

They've been around for

almost 4,000 million years while we humans popped up just over 100,000 years ago.

Are we better?

Well, from some perspectives we look over-elaborate and pretty fragile.

Then we look at some of the new levels of complexity created as living organisms

evolve from prokaryotes to eukaryotes to multi-cell organisms such as us.

Do nervous systems and brains constitute a new level of complexity?

Does consciousness represent an entirely new emergent property of organisms with

brains?

Finally, if you stick millions of complex organisms together,

you get an ecosystem, which represents another level of complexity.

In ecosystems, we see complexity nested within complexity,

nested within complexity.

Interactions within ecosystems are full of complex feedback loops

between the different components.

Negative feedback systems can stabilize complex systems just as

thermostats stabilize the temperature in a room

by constantly adjusting different types of change.

But positive feedback systems can speed up change by creating new cascades of change.

To move faster and faster until they cause sudden switches or catastrophic crashes.

Subtle changes,

either within or outside of an ecosystem can suddenly destabilize them.

We humans live within the global ecosystem of today's biosphere.

So any insights we can gain into how extreme complexity works within

the entire ecosystems could be very, very helpful.

[MUSIC]

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