Complexity Theory Overview

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In this video, we will be giving an overview to the area of complexity theory by looking at the major theoretical frameworks that are considered to form part of it and contribute to the study of complex systems. For full courses see: complexitylabs.io/courses
Transcription excerpt:
Complexity theory is a set of theoretical frameworks used for modeling and analyzing complex systems within a variety of domains. Complexity has proven to be a fundamental feature to our world that is not amenable to our traditional methods of modern science, and thus as researchers have encountered it within many different areas from computer science to ecology to engineering they have had to develop new sets of models and methods for approaching it. Out of these different frameworks has emerged a core set of commonalities that over the past few decades has come to be recognized as a generic framework for studying complex systems in the abstract. Complexity theory encompasses a very broad and very diverse set of models and methods, as yet there is no proper formulation to structure and give definition to this framework, thus we will present it as a composite of four main areas that encompasses the different major perspective on complex systems and how to best interpret them.
Firstly systems theory; Systems theory is in many ways the mother of complexity theory, before there was complexity theory, systems theory was dealing with the ideas of complexity, self-organization, adaptation and so on, almost all interpretations to complexity depend upon the concept of a system. In the same way that modern science can be formalized within the formal language of mathematics, all of complex systems science can be formalized within the language of systems theory but, systems theory is a very abstract and powerful formal language and it is typically too abstract for most people and thus is understood and used relatively little. Cybernetics is another closely related area of systems theory, it was also part in forming the foundation to complexity theory, cybernetics during the mid to late 20th century studied control systems and provided a lot of the theoretical background to modern computing, and thus we can see how the interplay between computing and complexity science goes all the way back to its origins as the two have developed hand-in-hand. A lot of systems theory is associated with and has come out of the whole area of computation. The areas of computer science and its counter part information theory have continued to be one of the few major contributors to complexity theory in many different ways, though systems theory is about much more than just computers it is a fully fledged formal language.
Next nonlinear systems and chaos theory; Nonlinearity is an inherent feature and major theme that crosses all areas of complex systems. A lot of nonlinear systems theory has its origins in quite dense and obscure mathematics and physics. Out of the study of certain types of equations, weather patterns, fluid dynamics and particular chemical reactions has emerged some very counter intuitive phenomena in the form of the butterfly effect and chaos. Chaos theory, which is the study of nonlinear dynamical systems, was one of the first major challenges to the Newtonian paradigm that was except into the mainstream body of scientific knowledge. Our modern scientific framework is based upon linear systems theory and this places significant constrains upon it, linear systems theory is dependent upon the concept of a system having an equilibrium, although linear systems theory often works as an approximation, the fact is that many of the phenomena we are interested in describing are nonlinear and process of change such as regime shifts within ecosystems and society, happen far-from-equilibrium they are governed by the dynamics of feedback loops and not linear equations. Trying to model complex systems by using traditional linear systems theory is like trying to put a screw into a piece of wood with a hammer, we are simply using the wrong tool because it is the only one we have. Thus the areas of nonlinear systems and their dynamics is another major part to the framework of complexity theory that has come largely from physics, mathematics and the study of far-from-equilibrium processes in chemistry.

[@uscdave1124]

I don't know how, but my brain is just intuitively able to grasp the relationships between sets of things in a way that I never appreciated before these videos. Understanding the fundamentals of the abstract parts of how systems function together really helps me to extrapolate and notice patterns in practically every area of life. Thanks so much for these videos.

[@ScottHaley12]

KUDOS! This is the best intro to complexity theory I've seen thus far. From a retired environmental geographer/human ecologist--- Many thanks, and Happy Trails🤠

[@heshamsugail2623]

So in a nutshell, "Complexity Theory" basically helps u as an individual to connect the dots (develop systems thinking) after understanding the fundamentals of the abstract parts of how systems function together. Also, it will help ur thinking extrapolate & notice patterns while considering complexity aspects.

[@SystemsInnovationNetwork]

Reupload of our overview of complexity theory, redid the graphics and audio to try and improve them. For those academics interested, I will be posting a link to the paper with all the relevent references in the near future.

[@MOSSZEEtHeEXCAVATIONProject]

Complexity Labs in the process of developing complexity we discover its effects

[@philledwith8307]

I'd definitely be interested in more academic references; especially of a mathematical nature, although the field seems to be advancing quickly. Certain basics like bifurcation theory and limit cycles (and theories about the stability of those cycles, e.g. lyapunov stability) are a given; I'm interested in more novel approaches from the community, if they exist.

[@kennethgarcia25]

Can you suggest a curriculum for medical individuals interested in developing a formalism of this field?

[@SpacePonder]

It's kinda strange but probably just a coincidence but this is the exact video I have been searching for and every part of it was greatly explained. It is almost as if that complexity has been deliberately been fine tuned into the universe with some ultimate goal like life, then more complex life, conscious animals then to us and since that we humans have come along, we have shot up the complexity like the universe has never seen before. Planet earth must be the complex place in the universe! The amount of variation of life is staggering, music, traffic flow, ants, language, maths, cells, dna, crystals, and a lot more complex things makes earth very unique.

[@ramiajjuri]

Binge watching complexity theory videos and your series is among the best. Thank you, please continue making videos. Very useful.

[@MichaelHeinz4]

This is an excellent overview of Complexity Theory, well narrated and very well visualised! Congrats for this great educational artefact... A fine intro into this important and emerging field of modern thinking! Well, we need this thinking for survival, I am convinced and so I hope that many young folks should dive into this field, everywhere!

[@philippweisang]

Da kann ich dir nur zustimmen

[@toffee129]

amazingly precise and transpicuous

[@phionahingabire8740]

Amazing simple and clear definitions

[@preditor467]

Great video! Wonderful presentation! I hope this channel gets the amount of subscribers and viewers it deserves soon enough.

[@brendawilliams8062]

Yes. This channel is truthful and hits the nail in it’s head.

[@layo7076]

Amazing expression of the Theory. Loved it, really appreciate you guys!

[@vishalkumarvenkatesan3876]

Wonderful explaination about complex theory

[@WernervanZyl]

Such a great animation and explanation

[@orikacruzeiro]

great work, there should have been more emphasis on Education and teaching fields too.

[@VrilYa100]

Superb presentation. Thanks.

[@SystemsInnovationNetwork]

You are welcome

[@boys7371]

very good video, worth to recommend to others

[@Value_Pilgrim]

Absolutely brilliant videos. Binge watching the entire series with a sandwich, chips and coke! ☺

[@pedrozaragoza2253]

Great video. Of the four systems the most precise and powerful is non linear systems. But the inherent limitations of each are our incapacity to the apparent individual parts as a coherent and integral whole.

[@kristentaneil]

Pedro Zaragoza I’m rooting for network theory to do just that!

[@angieq9539]

Great presentation on Complexity Theory! Can you make a video focusing on the role played by the feedback loop in moderating changes in complex systems?

[@vicktorioalhakim3666]

It's called control theory.

[@u03agc4]

I’m sensing a bias on maths and physics (ecologist over here!) but very good video (and series). Thanks!

[@TheGodfatherjohn]

It is what it is.

[@philosophize24]

Thank you!

[@t.j.kneale7580]

This is fascinating, but hard to truly grok. I feel like I need a back and forth with an actual human to really get it. Does anyone else feel this way?

[@trantaylor2960]

Nice job

[@ezbo1883]

7:49 This is evolution theory in terms of analyzing complex systems right ? Like understanding the nature of the process and not exactly the consequence or the outcome of a certain effect. The process of the change in an organisms behavior in terms of individual selection might resemble replicator dynamics when cognitive functions change after facing a certain reciprocal altruistic situation for example. In other words, the cognitive process concerning selection, after the consequences of a given situation occur, might resemble the process of a replicator equation coming up with different strategies to ensure survival or reproduction of the individual or kin etc.

[@gomojo1024]

good stuff

[@Csartreweghhgf]

Exquisite

[@francescos7361]

Thanks.

[@okaynope5197]

I'm not sure I entirely understand the point. It sounds like just an extension upon newtonian linear understanding. It's just a lot of lines to put it simply. Why are we calling these different theories? We still need to test without other factors to observe the effect of one action upon the system given the state involved so that we can understand how all those components would work together, or against eachother.

[@samuelosebemoriasi2217]

This is Hermeneutics in science?

[@jrtao3709]

i love school of fish and birds !

[@LostArchivist]

Moderna Via, Via Antiqua accepit.

[@aniksamiurrahman6365]

The only problem is that most of the models quickly becomes computationally intractable :(

[@aniksamiurrahman6365]

@@cristianotalon8895 U r creepy.

[@Bangy]

NRx people won't stop talking about this.

[@Redrios]

is this text-to-speech voice? I can't tell, It sounds as if a person tried to imitate google assistant

[@philipkilmartin2312]

umm........ i don't belong here.. bye !

[@keithleeuwen877]

Horrendous ?

[@rohel5419]

How can Newtonian laws be "linear" if they are described by differential equations, and the functions involved are mostly vectors? It is algebra, in fact, properly termed linear algebra, which is so far the only basis for machine learning that is linear.Number sets and series are also linear and scalar and do not represent any real organic systems. Much of the phenomena that engineers, who pretty much have constructed the civilization we inhabit, are "inherently interested" are still treated reasonably well by Newtonian physics as it's laws still hold on our planet because nothing here moves anywhere with the speed of light. To me, as a materials science engineer, the relativity theory is wholly useless. That's why they didn't even teach it to us. We know that the laws of mechanics and classical thermodynamics are so-called Ideal, so we use that as such; we know that we need to account for, say, friction and heat loss, etc, while we design stuff. Ideal or closed system does not mean "linear". The idea that Matter is chaotic is a throwback to the Middle Ages, actually. Matter is highly organized at its every level, every single scale of magnification. Define non-linear, please. Define "far-away from equilibrium". Which equilibrium? How far away? Liquids used to be considered chaotic, now even gasses are thought to possess certain structure. Grain boundaries used to be thought of as chaotic, not anymore. It seems this new science is actually a throwback into earlier times. In physics (math) and philosophy every working concept--except for the most entry-level fundamental assumptions--must be strictly defined before they are used in either working formulae or an arguments. Computer men, driven by the proposition that the thinking machine is just around the corner, confidently throw around their own undefined conceptions or those borrowed from various unrelated fields. The "Butterfly effect" is only exhibited DURING the phase transition, not while the system is stable. A complex system, in fact, is such that small-scale fluctuations caused by either the internal or external forces are continuously negated. QUESTION: I am seriously interested in the answer. What is the academic source of the proposition/assumption that the complex systems exist in enormously large ever-changing number of forms? This cannot possibly true, nature is very conservative. Because all the possible structures, the natural ones that organically "jell" by themselves, must obey the energy laws. For example, the surface tension of the adjacent structures in a complex system in our dimension must be minimal, that's why the larger guys gobble up the smaller ones and eventually they all look like perfect hexagons. There must be a limited number of all possible internal structures that are energetically feasible. On all the levels of magnification. Precisely because the parts of a complex system are highly interactive, so they would adjust the way they inhabit the the Space. But I'd like to see if I am wrong. The way I see it, it is the computer scientists who need enormous amounts of data (the one that is the King now, hallelujah). This data they need to "mine" because this is the only way the Backward Propagation worksl But is it right to assume that Nature works the same? Rohel

[@Tadesan]

Leonard susskind describes complexity as the smallest number of steps needed to achieve a given configuration from a given starting point. In your bubble example, you have fixed the end configuration but not the initial configuration. So you can't discuss the complexity.

[@jesussanchezherrero5659]

Most of the equations (differential among them) we engineers use are linear. This means the result of the differential operator upon a function yields the same function by some constant. So the solution to that eq is one which keeps kind of the same form after being differentiated. That's why it can be usually solved with exp or sin, cos

[@reason827]

Everything is just basic physical laws. Complexity and chaos are worng.

[@byattwurns1553]

Physicists found out you can't always predict everything a long time ago. I think good examples are the uncertainty principle and chaos theory.