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26 Feb, 34 tweets, 6 min read
@normonics' Intro to Applied Complexity #ACS101 #SpringA2021 Highlights

Session 2: Intro to Dynamics

1/n
@chrismanfrank & @bavoter appear:

Imparts some wisdom from Dr. Dwanye Beck.

'Diversity is important in emulating natural systems.'

'Pests, weeds, & disease are a sign of a lack of diversity. Nature's way of replacing the diversity that was lost.'

2/n
In nature pillage is a catastrophic event.

3/n

(Brain transplants/Brian transplants?)
A further Brian gem:

'Quite often we try to simplify our real-world system to match the model rather than adapt the model to match the real world.

A dangerous place to go.'

4/n
A system is carving out a piece of the world.

It takes a heroic effort to isolate a system in science but this is not typical of the real world, so you have to be careful applying conclusions from an isolated system to the real world.

5/n
A simplified example is the H20 molecule.

At room temperature water is in a substance phase.
But is there any sense asking if a molecule is a solid or a liquid?

No, not by itself.

6/n
Put together then they can interact.

7/n
The property of liquidity is a scoping issue arising from the interactive transient coupling of a multiple of molecules.

8/n
Lower the temperature parameter and you hit a critical threshold where attractive forces overpower the repellent forces abruptly - phase transitioning into an organised solid (more ordered).

(Consider the gas as an even more disorganised system of strong repulsive forces.)

9/n
Definitionally a 'parameter' as a system dynamically behaves is constant.

10/n
Again, the bandwidth of an agent is always limited.

11/n
Unlike models, in the real world we might not know where phase transitions exist in a system.

12/n
Non-linearity is generic, linearity is more the exception.

There are a lot of assumptions of linearity where there should not be.

There's only one way to be linear.

There's many ways to be non-linear.

(non-linearity is an emergent property)

13/n
J W Norman
'Scientific Truth', 2021
Apple pen on EasyCast
1080p

14/n
Phase transitions are all over the place.

Consider music e.g. Major chords & minor chords.

The substance differs in quality & falls out of the invariant distance between they notes & their relation/interaction.

15/n
Patterns are the primary drivers of the properties we observe.

Patterns (interactions, relations, organisation) that things embody rather than just the things themselves.

16/n
It's a cliché but the whole is different (less/more) than the sum of its parts.

17/n
Complexity is hard because of a cultural overreliance on reduction, linearity, summing type operations, etc. and their simplicity.

18/n
The century of complexity quote by Hawking is wrong.

19/n
There is an inversion in our thinking between the special and the general.

20/n
Scoping out, experimenters have to contrive all sorts of ways to isolate a system.

It's 'easy for us to work with' so we consider it general.

21/n
The general condition is open systems locally receiving flows of energy and flows of matter.

22/n
If you have something very huge but it's homogenous there's not much information there, but if some small material but with lots of details then it has a much greater richness.

23/n
Boundaries/evidence:

Look for where abrupt behavioural shifts occur.

Cells have boundaries, as do organs.

Social systems have Boundaries.

24/n
The Machine Metaphor:

Machines are assembled by putting parts together.

When an organism grows where do its parts come from?

25/n
A foetus has massively complex structural intricacy that differentiates internally to generate functional complexity.

26/n
A developing organism synthesises into a whole from which the parts emerge.

A machine is fabricated from pre-existing part and put together.

You can't take a mouse apart and then put it back together.

27/n
Social systems are more complex because ultimately more complex because agents can learn, so the behaviours can be richer, but not necessarily.

28/n
"Even" physical systems are able to display a richness of behaviours that we see in the likes of e.g. social systems.

(Analogise boiling water to a riot.)

29/n
The fact that it maps is interesting because in certain conditions details don't matter, regardless of the difference between physical & (with the intricate details of its agents) social systems.

30/n
Something like trust can't be discussed in a physical, but in general, as you scope out and stack layers of systems you are always getting new novel properties.

But maybe trust can be modelled as a physical property in a certain context.

31/n
One of the challenges is finding which details matter and which don't.

The largest scale behaviour is often helpful to discover what details don't matter.

32/n

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More from @evolvingcalm

27 Feb
Session 3 @normonics' Intro to Applied Complexity #ACS101 #SpringA2021 Highlights

(with some continuation from session 2)

1/n
Ask not 'what is a thing?' but 'what does it do?'

2/n
We can dismantle Newton's house with Newton's tools.

3/n
Read 36 tweets
25 Feb
For the past month or so I've been taking @normonics ACS101 which I can thoroughly recommend.

Seeing as we're about half the way through #ACS101 I thought I give a recap of my notes of some of the highlights so far.

/thread
I've being going back through the sessions so far of ACS101 #SpringA2021 in my spare time.

It's remarkable how much more everything clicked that much more the second time around after the time absorbing everything.

1/n
Truly no book is read twice by the same man.

2/n
Read 39 tweets

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