Introduction to Complexity: Introduction to the Study of Complexity

Summary

This script explores the concept of complexity through examples from ant colonies to human genomes, highlighting how simple agents self-organize into complex systems without central control. It delves into the study of complex systems, touching on topics like decentralized self-organization, genetic regulatory networks, and the interconnectedness of networks in nature and society. The script also introduces NetLogo as a tool for simulating complex systems, aiming to demystify the intricate dance of simplicity and complexity in our world.

Takeaways

• 🧠 The complexity of systems is difficult to define precisely but can be explored through examples of phenomena studied by complex systems scientists.
• 🐜 Ant colonies demonstrate self-organization and cooperative behavior without central control, accomplishing complex tasks through simple individual actions.
• 🌉 Ants can build bridges using their bodies and chemical communication, showcasing decentralized self-assembling systems in nature.
• 🧠 The human brain, with its approximately 100 billion neurons and 100 trillion connections, is a complex system where cognition and intelligence emerge from simple components.
• 🛡️ The immune system is a distributed and adaptive complex system that protects the body through coordinated actions of trillions of cells without central control.
• 🧬 The human genome, with about 25,000 genes, is a complex system where genes interact in regulatory networks, contributing to our biological complexity.
• 🔗 Networks are central to the study of complexity, with examples ranging from food webs to social networks, each displaying unique patterns and behaviors.
• 📊 Social networks exhibit interesting patterns that are also found in biological and technological networks, which are of great interest to complex systems scientists.
• 💼 Economies are complex systems where the connectivity and types of links in financial networks can significantly impact stability and resilience.
• 🏙️ Cities, often likened to living organisms, are studied as complex systems to understand their structure, growth, scaling, and operation.
• 🔬 The interdisciplinary field of network science, emerging from complex systems research, investigates network phenomena across various disciplines.

Q & A

What is the main question explored in the first unit of the course?

The main question explored in the first unit is 'What is complexity?', which is a challenging question to define precisely.

What is the purpose of starting the course with examples of complex phenomena?

The purpose is to provide an intuitive understanding of complexity through real-world examples that complex systems scientists study, serving as a preview of the course topics.

What important properties are common to most complex systems according to the script?

The script does not specify the properties but mentions that a list of important properties common to most complex systems will be made, highlighting decentralization, self-organization, and adaptation as key characteristics.

Why are ants a great example to begin exploring complex systems?

Ants are a great example because, despite being individually simple, they can collectively accomplish complex tasks without central control, demonstrating decentralized self-organization.

How do ants communicate with each other when building structures?

Ants communicate with each other by secreting chemicals, which allows them to coordinate their actions and build structures like bridges without any central control.

What is the human brain's role in complex systems research?

The human brain is studied to understand how simple agents, such as neurons, with approximately 100 billion neurons and 100 trillion connections, produce complex behaviors like cognition, intelligence, and creativity without central control.

How does the immune system demonstrate the characteristics of a complex system?

The immune system is a complex system because it is distributed across the body, involves many organs and trillions of cells that communicate through chemical signals, and adapt to threats without central control.

What is the significance of genetic regulatory networks in the human genome?

Genetic regulatory networks are significant because they represent the interactions between genes in a decentralized way, controlling each other's expression and contributing to the overall complexity of the human genome.

How are food webs relevant to the study of complex systems?

Food webs are relevant because they are networks where nodes represent species groups, and arrows represent predation relationships, showcasing decentralized self-organization and the dynamics of ecological systems.

What patterns are observed in social networks that are also found in biological and technological networks?

The script does not detail the specific patterns but mentions that social networks, like biological and technological networks, exhibit interesting patterns that will be explored in depth later in the course.

Why are cities considered as complex systems in the study?

Cities are considered complex systems because they resemble living organisms in their structure, growth, scaling with size, and operation, which is a rapidly growing area of complex systems research.

What is the role of Netlogo in the course on complex systems?

Netlogo is a simulation and programming platform that will be used to illustrate many of the ideas of complex systems throughout the course.

Outlines

00:00

🐜 Introduction to Complexity and Complex Systems

The first unit of the course delves into the challenging question of defining complexity. It begins with intuitive examples from complex systems science, such as ant colonies and their remarkable ability to perform complex tasks without central control. The unit outlines key properties of complex systems and briefly introduces the concept of complexity. It surveys the core disciplines, goals, and methodologies of complex systems research and introduces guest spots with interviews of prominent scientists. The latter half of the unit focuses on Netlogo, a simulation platform used to illustrate complex systems concepts, with a detailed look at how simple agents like ants can self-organize into complex structures, and how this principle applies to other systems like the human brain and immune system.

05:01

🧬 Networks and Adaptation in Complex Systems

The second paragraph explores the adaptation characteristic of complex systems, exemplified by the human genome, which consists of thousands of genes interacting through genetic regulatory networks. The concept of networks is central to the study of complexity, with food webs and social networks being highlighted as examples of such systems. Social networks, in particular, are of interest to scientists studying information transmission and structural patterns. The paragraph also touches on economies as complex systems, with the international financial network being a case study for understanding stability and connectivity. The emerging field of network science is introduced, which studies these phenomena across various disciplines. Finally, the paragraph concludes with the study of cities as complex systems, examining their resemblance to living organisms in structure, growth, and operation.

Keywords

💡Complexity

Complexity in this context refers to the quality of a system or phenomenon that involves many interconnected parts, making it difficult to understand or predict. It is central to the video's theme, as it explores the intricate behaviors of systems without central control. The script uses examples such as ant colonies and the human brain to illustrate how complexity arises from the interaction of simple components.

💡Complex Systems

Complex Systems are interdisciplinary fields of study that focus on systems whose behaviors are difficult to predict due to their complex interactions. The video discusses this concept by highlighting various examples like ant colonies, the brain, and the immune system, emphasizing the decentralized nature of these systems and their ability to self-organize.

💡Self-organization

Self-organization is a property of complex systems where components organize themselves without external direction to form a coherent structure or pattern. The video script describes how ant colonies build tunnels and bridges without a central leader, exemplifying self-organization in action.

💡Decentralized Systems

Decentralized Systems are those that operate without a central authority or control. The video uses the term to describe how ant colonies and other complex systems like the brain function effectively without a single point of control, illustrating the power of distributed decision-making.

💡Ant Colony

An Ant Colony is a complex system composed of individual ants that, despite being simple organisms, can collectively perform sophisticated tasks. The video script provides examples of how ants build bridges and tunnels, demonstrating the emergent complexity from simple behaviors.

💡Neurons

Neurons are the fundamental units of the nervous system, responsible for transmitting information through electrical and chemical signals. The video script discusses the human brain's complexity, which arises from the interactions of approximately 100 billion neurons, each simple but together forming the basis of cognition and intelligence.

💡Genetic Regulatory Networks

Genetic Regulatory Networks are systems of interactions among genes that control the expression of other genes. The video script explains how the human genome's complexity is due to the decentralized interactions within thousands of such networks, controlling the expression of approximately 25,000 genes.

💡Food Web

A Food Web is a network that represents feeding relationships among species within an ecosystem. The video script describes how each node in a food web represents a group of species, and the arrows show the predator-prey relationships, illustrating the interconnectedness and complexity of ecological systems.

💡Social Networks

Social Networks are networks of social interactions and personal relationships. The video script mentions social networks to highlight the patterns and structures that emerge from the connections between individuals, drawing parallels to patterns found in biological and technological networks.

💡Economies

Economies, in the context of complex systems, are networks of financial interactions between institutions. The video script uses the example of the international financial network to show how connectivity and types of links can impact the stability of the economic system.

💡Network Science

Network Science is an interdisciplinary field that studies the structure and dynamics of networks across various domains. The video script mentions this field as arising from complex systems research, focusing on phenomena like self-organization in different types of networks.

💡Cities

Cities, as complex systems, are likened to living organisms in terms of their structure, growth, and operation. The video script raises questions about the extent to which cities resemble living organisms, indicating a growing area of research in complex systems.

Highlights

Complexity is a challenging concept to define precisely, with the course starting with intuitive examples from complex systems science.

The course will cover common properties of complex systems and delve into defining complexity.

Complex systems research includes a variety of disciplines, methodologies, and aims to be surveyed in the course.

Guest spots featuring interviews with prominent complex systems scientists will be a part of the course.

Netlogo, a simulation and programming platform, will be used to illustrate complex systems concepts.

Ant colonies demonstrate complex, decentralized behavior without central control, showcasing self-organization.

Ants build bridges and tunnels through cooperative actions, highlighting the power of simple agents in complex systems.

Social insects like termites also exhibit complex behavior, constructing intricate nests.

The human brain, with its vast number of neurons and connections, is a prime example of a complex system.

Neurons self-organize into functional areas, contributing to complex cognitive behaviors.

The immune system is a distributed, complex system with cells communicating and adapting to threats.

The human genome, with its genes and regulatory networks, is a complex system of genetic interactions.

Food webs are networks representing species interactions and showcase decentralized self-organization.

Social networks display patterns found in biological and technological networks, important for information transmission.

Economies are complex systems with financial networks impacting stability and change.

The interdisciplinary field of network science studies phenomena across various network disciplines.

Cities as complex systems are compared to living organisms in structure, growth, and operation.

Transcripts

Our first unit explores the question "what is complexity?"

As you'll see this turns out to be a hard question to answer precisely.

We'll start out very intuitively by giving a series of examples of the sorts of phenomena studied by complex systems scientists.

This will be a preview of the sorts of topics that we'll be covering in this course.

Then we'll make a list of some important properties that are common to most complex systems.

We'll briefly look at defining the notion of complexity, something that we'll come back to later in the course.

We'll also survey the core disciplines, goals and methodologies of the field of complex systems research.

At that point we'll be ready for the first in a series of what I call "guest spots", that is

in which I interview prominent complex systems scientists about their views on the field.

The last half of this unit will focus on Netlogo, the simulation and programming platform

that we'll be using to illustrate many of the ideas of complex systems in this course.

You're ready to get started? Let's go.

A great example to begin with is ants. Nigel Franks, a well known ant researcher once wrote

that the solitary army ant is behaviorally one of the least sophisticated animals imaginable.

In extremely high numbers however, it's a different story.

Here for example, is a colony of army ants building a tunnel.

Each ant on its own is very simple, but the colony as a whole can work together cooperatively

to accomplish very complex tasks without any central control,

that is without any ant or group of ants being in charge.

In other words, ant colonies can organize themselves to produce structures much more

complicated than any single ant can produce.

Here's an example of ants building a bridge with their bodies, so that other members of the

ant colony can cross the gap between the two leaves.

This video shows ants assembling this kind of bridge.

They start up here, come in here on a stick, all the way up to the top, and they're going to

eventually chain themselves to go all the way down to the ground.

You can see them gradually adding themselves to the structure.

Each ant is secreting chemicals to communmicate with the other ants, and the whole

bridge is built without any central control.

You might call this an example of a decentralized, self-organizing or self-assembling system.

Other social insects produce similar behavior.

For instance, here is an example of the kind of complex structure built by termites.

It serves as a nest. A major focus of complex systems research is to understand how individually

simple agents produce complex behavior without central control.

In these examples, the simple agents are insects, but we'll see many other kinds.

Another classic example of a complex system is the brain. Here, the individual simple agents are

neurons. The human brain consists of about 100 billion neurons, with a 100 trillion connections

between those neurons. Each neuron is relatively simple compared to the whole brain,

and again there's no central control. Somehow, the huge ensemble of neurons and

connections give rise to the complex behaviors that we call cognition, intelligence, or even

creativity. Brain imaging has shown that these neurons organize themselves into

different functional areas. Just like the ants or termites, neurons can self-organize into complex

structures that help the species function and survive. Yet another complex system is the immune system.

The immune system is distributed across the body,

involving many different organs as shown in this picture, and trillions of cells moving around

in the bloodstream or lymph stream protecting and healing the body from damage or disease.

For example, this is a picture of immune cells, these ones in blue here, attacking a cancer cell

here in the center. Like the ants we saw before, immune system cells communicate with

one another through chemical signals, and work together without any central control

to launch coordinated attacks on what they perceive as threats to the body.

In addition, the population of immune cells in the body is able to change, or adapt itself

in response to what that population of cells perceives in its environment.

This kind of adapatation is another key characteristic of complex systems.

Another familiar example of a complex system is the human genome. Here's an image of

a human genome. Each of these worm-like structures is a chromosome, and there're 23 pairs

of them. You can see that this is a male, because it has an X-Y pair.

Each of these chromosomes is made up of thousands of genes. Genes, of course, are

strings of DNA along the chromosome. It's currently thought that the human genome has about 25,000

genes which code for proteins. In complex systems terms, you could think of the genes as

simple components that interact with other genes in a decentralized way. And the way that they

interact is through genetic regulatory networks. They control one another's expression, where

expression means translation into proteins. Here is one small genetic regulatory network

that's been mapped out by researchers. Here, each of these rectangles or ovals represents

a gene, and an arrow from one gene to another means that the first gene controls the

expression of the second gene. It turns out that the human genome is made up of thousands of

networks like this one, in which genes interact with one another in complicated ways,

and it's these interactions largely responsible for our own complexity.

The idea of networks is central to the study of complexity in nature.

Here's another kind of network- a food web.

Here, each node, or entity in the network, is a particular group of species, and the arrows

represent who eats whom. If one species group points to another, that means that the first

is food for the second. For example, you can see that foxes here are at the top of this particular

Alaskan food web since they eat several kinds of animals but nothing eats them,

at least not on this chart. Here's an abstract diagram of an even more complicated food web

from the gulf of Alaska. When we talk about networks later in the course, we'll see some very

interesting examples of decentralized self-organization in food webs like this, and other kinds

of networks. Probably the kind of network you're most familiar with is a social network.

Here's part of my own social network with me here. These links represent friendship relationships.

My friends are linked to their friends and so on and so forth. Social networks turn out to have

some very interesting patterns, ones that also turn up in biological and technological networks.

Later in this course, we'll look in depth at what those patterns are, and how they form.

Complex systems scientists are very interested in studying large social networks such as

Faceook, to understand their structure, how they form, how they change over time, and perhaps

most interestingly, how information is transmitted in such networks, among other questions.

Economies are another type of complex system, in which networks of interaction are

fundamental. Here, we see a sample of the international financial network, where

nodes represent financial institutions, and links represent relations among them. For example,

if a bank owns shares of another bank, the two are linked. It turns out that the amount of

connectivity in such a network, as well as the kinds of links present, can have a big effect

on how stable the network is to changes, such as a bank going out of business.

The new interdisciplinary field of network science, which arose from the complex systems research

community, studies these kinds of phenomena in networks from many different disciplines.

As a final example, we look at the study of cities as complex systems.

It's often been said that a city is like a living organism in many ways.

But to what extent do cities actually resemble living organisms,in the way that they're structured,

grow, scale with size and operate? These and other questions form the basis of a rapidly growing

area of complex systems research, which we'll look at in detail later in the course.

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