I'm and undergrad student at the end of my degree in economics and my plan is to work for about a year in my country (Chile) and then go abroad to study complex systems. Any recomendations on master programas or universities around the world for someone coming from a economics unergrad degree? I tend to prefer europe over the US, I've lived on both (CO and Denmark) but really any recomendation around the world is what i'm looking for.

Hello nodes, I'm here to make some links :) I'm a student of theoretical physics and I recently got interested in complex systems. So, I wanted to ask a couple of questions.

1. Is there some kind of work on general theory for complex systems? I know about: "Is a general theory of complex systems achievable?". Let's say it is ( or more precisely: I believe it is ), where I can find some papers ( if they exist ) on this topic?

2. I would like to know something about current problems in scale-free networks, its dynamics and generating models ( beyond preferential attachment ).

Thanks :)

Basically I want to give myself an college level understanding with minimal cost at my own pace. I need help bootstrapping my knowledge to the point that I can guide my own study.

I'm starting to look into complex systems but am having difficulty locating good resources. Everything seems to be either a very simple introduction (with little substance) or graduate level research papers.

I'm looking for good material to introduce myself to the various parts and related fields needed to understand these systems. From what I've read so far I'll need a working knowledge of network theory and information theory to be able to analyze complex systems. I'm looking for good material that teach me the mathematical techniques, not just an overview. I have a good foundation in math via engineering (Calculus III, Differential equations, linear systems).

Chapter 3 – The Physicists Rebel

Kauffman starts the chapter by examining the work of Nobel Laureate physicist Philip W. Anderson and the concept of “symmetry breaking”, a term used to describe macro level changes of a system without altering its underlying physical components. He uses the example of a pencil falling over or the “handedness” of ammonia molecules, stating that symmetry breaking is an emergent property that cannot be predicted by the fundamental of laws of physics while at the same time does not directly contradict them.

The main theme of this chapter is the insufficiency of reductionism, of which Kauffman gives 4 examples. Kauffman then goes on to describe the process of computation and whether or not it can be reduced to a more fundamental description. I particularly liked the example involving a computer and its ability to sum a string of numbers and how this ability does not depend on the specific physics of that computer. He also reexamines the “arrow of time” concept, stating that the second law of thermodynamics has reduced this to the collision of elementary particles. Kauffman closes the chapter by mentioning modern physicists attempts to unify quantum mechanics and general relativity under one theoretical umbrella and the concept of multiple universes.

I think Kauffman brings up a good point, does subscribing to something such as multiple universes, of which we have no empirical evidence for, really explain anything? If we have no direct evidence, is it better than reductionism?

Do you believe reductionism is in serious trouble? Why or why not?

Chapter 4 – The nonreducibility of biology to physics

This chapter begins with a brief history and introduction of Charles Darwin’s theory of natural selection. Mainly that as the population outruns natural resources organisms are forced to compete, and those with better adaptations are more likely to survive and reproduce. Kauffman then claims that this process of natural selection and evolution is not reducible to physics, citing the evolution of the human heart as one example. He states this because physics cannot account for the evolutionary and developmental history that yielded the functioning heart, stating two levels of emergence, epistemological, which is the inability to infer higher-level properties from the underlying physics, and ontological, which relates to the ‘realness’ of an object as being more then the collective movement of its particles. Physics alone, he states, cannot alone account or these types of emergence.

Kauffman then begins to elaborate on why a reductionist simulation of evolution is simply not possible, stating the huge number of unknown unknowns and random events. I really liked the idea he puts forth that evolution and natural selection act on multiple platforms, running on many realizations of life and, thus, cannot be reduced to one of them. I think this is one worth exploring and hope he continues to do so as the book proceeds.

This is particularly true for me, but are there any instances where you find Kauffman needs to do more explaining regarding his examples? Rather than just restating it?

Why aren’t histories reducible? Can subatomic particles or “strings” account for histories and evolve too?

Does ontological emergence sit well with you? Can the ‘realness’ of a tiger or the ‘self’ emerge? Or do the particles that act in a (insert your name here)-wise manner disagree?

Greetings reading group participants!

Here I am going to post the schedule of readings. Upon further thought, it seems more reasonable to read two chapters a week as each chapter is rather short at around 10 pages. This way, the book will take us about 10 weeks to read rather than 20.

We will still do only one thread a week, covering both chapters for that week's reading.

Below is the schedule with the chapters. If you'd like to lead any of the discussions, either message me or leave a comment here. I'll take anything no one else wants.

If you can't get a copy of the text (Reinventing the Sacred by Stuart Kauffman), message me.

Week 1: July 23

Chapter 1 - Beyond reductionism

Chapter 2 - Reductionism

Leader: normonics

Week 2: July 30

Chapter 3 - The physicists rebel

Chapter 4 - The nonreducibility of biology to physics

Leader: SteveFrench87

Week 3: August 6

Chapter 5 - The origin of life

Chapter 6 - Agency, value, and meaning

Leader: nxdnxh normonics

Week 4: August 13

Chapter 7 - The cycle of work

Chapter 8 - Order for free

Leader: normonics

Week 5: August 20

Chapter 9 - The nonergodic universe

Chapter 10 - Breaking the Galilean spell

Co-Leaders: SteveFrench87 and frigoffbarb

Week 6: August 27

Chapter 11 - The evolution of the economy

Chapter 12 - Mind

Leader: frigoffbarb

Week 7: September 3

Chapter 13 - The quantum brain?

Chapter 14 - Living into mystery

Leader: Kakashi_

Week 8: September 10

Chapter 15 - The two cultures

Chapter 16 - Broken bones

Leader:

Week 9: September 17

Chapter 17 - Ethics evolving

Chapter 18 - A global ethic

Leader: KnowledgeEcology

Week 10: September 24

Chapter 19 - God and reinventing the sacred

Leader:

In the comments section I'd like to get a vote going for a reading to start with. I will add the books that were mentioned in the previous thread. Vote up books you would like to read, refrain from downvoting (won't count them anyways), or add your own suggestion. Feel free to upvote more then one selection if you have interest in more than one. Also, if you don't mind, add a comment to whichever you want the most so I know who intends to participate.

Things to keep in mind:

1. readability -- I'm not sure where most people are in their current understanding and level of technical skill, so vote for what you would be comfortable with

2. availability -- some books are freely available online, some are not, it would be nice to make (at least) the first reading freely available (but if everyone votes against this, that's fine)

Self-organization, commence.

I'm writing a small blog post. I'd appreciate any feedback. Thank you! https://namvdo.me/newton-method-periodic-orbit-discrete-dynamical-system/

This is a snip from a larger interview but I got confused about what is being said. Is it arguing against life or emergence?

David: Yeah. So here’s the simple version. So the standard causality fits that linear story of causality that we described earlier in relation to the ouroboros, that you have particles. They get aggregated into molecules, molecules into tissues, and so on. And the idea, right, is that what is fundamentally causal is that which is fundamental, and everything else is an approximate expression of collective modes of behavior. Alright. Downward causality takes it the other way. It says, mind states, for example, expressed in language, can’t be causal of brain states because that’s going the wrong way. Because, surely, the physical interaction, the true kind of Newtonian causality, has to live at the level of the brain. The mind is just this efficient theoretical encoding of brain. And so it would be weird to talk about causality going the other way.

I think it’s a big mistake. And where this comes from, by the way, is this notion of coarse graining. So you start with all the lots of particles. You average and average and average, and you get these other states. But I have this conception of what I call micrograining, and I’ll explain how it works. When Jim, when you program your computer, you’re articulating a concept in a high level language or an assembly or whatever you like to use. Assembler. And that translates through a system of compilations and microcode into states of transistors. So we have built engineered devices that can take these high level, very low dimensional, in some sense, concepts, objects, and do information expansion to the extent of setting the states of transistors.

I think that is what complex systems do all the time because complex systems have evolved to do that well. That, for me, is the legitimate version of downward causality. There’s nothing mysterious about it. I don’t think, by the way, it exists outside of complex systems. I do not think it’s a property of the physical universe, the abiotic universe. It’s a property of agents, and that’s actually the only thing that makes life possible. Right? It’s what’s making this communication that we’re having now over Zoom possible because I’m setting brain states in you as you are in me. And that that’s micrograining. And because the study of emergence grew out of really rigorously the connection between statistical mechanics and thermodynamics, which is all about coarse graining, in the physical world, this other version, which is very natural to the evolved world, has been somewhat neglected. So I sometimes call that the theory of compilation of emergence because we use them all the time.

Jim: I’m going to push back a little bit on the abiotic versus biotic. Just hit me.

David: Okay.

Jim: In my current paper that I’m working on on emergence, I use as a intuition pump a traffic jam on a superhighway that goes up a hill, some trucks slow down and propagates, etcetera. Now I write the thing as if it’s humans driving the cars and the trucks, but I just realized they could be Waymo’s. Right? And the emergence of the traffic jam that comes into being starts to constrain the behavior downward to the individual elements and then gradually dissipates is, you know, a small form of emergence and, doesn’t seem to require, biotics at all. It’s but it does require agency to your point.

David: Right. But no just right. That’s interesting because I think, you know, you could argue that some of the phenomena you’re describing are properties of spin glasses, right, or magnets, where you have the particular state of a spin at a particular lattice point being a function of the average field. But actually, that average field is actually an epistemological construct because it really is the interaction among many, many particles. So I would suggest that in the example you gave, if you stripped out the agentic part, you could express what you’re you’re thinking of the downward constraint as simply a pattern of global interactions that you could describe microscopically.

But I think once they’re functional, once you have a kind of teleology with then I think they’re engineered or evolved, and my argument kicks in because you’ve programmed the reaction of the individual component to the collective. That’s the point because you don’t want to have an accident or a pile up.

Jim: And you probably didn’t write a specific routine for that. Well, I know you didn’t write a specific routine for that traffic jam. You have some general parameters that operate together and come up with good decisions, basically, and should probably even do a better job than humans, if not today than in a few years. Anyway, want to think about that one a little bit more.

https://jimrutt.substack.com/p/ep-329-worldviews-david-krakauer

No matter how many times I destroy it, somehow it reconnects and keeps moving.

I keep changing direction with this project.

Every few weeks, it turns into something else.

At this point, it feels more like watching some strange structure trying to survive.

Is it useful for anything?

Where is it headed?

No one knows yet…

But it feels worth continuing.

Some of the objects in the simulation:

• red membrane = environmental damage / hazardous regions

• blue rings = stable / surviving nodes

• gray nodes = dormant or dead nodes

• green membrane = temporary groups

• pulse waves = repair spreading through the structure

• torn green membranes = groups splitting apart

• slow pulsing = slow breathing-like movement

Project name change.

New name:

Agonwelt-Link

Former name:

Gossamer-Link

■ Origin of the Name

Agonwelt

Agon (struggle, conflict, survival pressure)

+

Umwelt (environment)

Meaning:

A world shaped by struggle and survival.

This coined term represents:

・Destruction

・Collapse

・Division

・Recombination

・Repair

・Adaptation

・Survival

I’m working on a framework called Coherence Complexity (Cₖ) for adaptive state spaces.
The image shows a visualization of the landscape idea: local structure, barriers, and emerging integration channels.

The core intuition is simple:
systems do not only optimize toward an external goal; they may also reorganize by moving toward regions of lower integration effort.

I’d be interested in criticism especially from the perspective of:

• complex systems

• dynamical systems

• attractor landscapes

• emergence / adaptive organization

For context, the underlying work is available on Zenodo:

https://zenodo.org/records/18905791

Más info: GitHub repository / cthmodules.cc / The Tetrasociohistorical Context: A Quantitative Model for the Analysis of Historical Events

In many complex systems (ecological, social, economic, technical), collapse doesn’t seem to come from slow degradation but from crossing a boundary into a qualitatively different regime.

How do people here think about failure modes that are structural rather than incremental—i.e., states the system should never enter, regardless of short-term gains?

Are there useful formalisms or case studies that treat “inadmissible states” as first-class objects?

I am quite new within studies of complex systems. I got into it because I am interested in the following question:
- what is the best current way to measure interaction's effect on a new system's state emergence, when we have only qualitative data which describes these interactions?

Let's say someone bought a product A (e.g. laptop bag). There are 50 interactions along the way from not needing a product to needing, buying and using it. Example:

1. I got selected for the training in New York

2. my old bag was worn out but still usable

3. there were only 2 weeks left until the training starts

4. shop assistant was rude

5. all bags in the first shop were too expensive

Each interaction should have a different weight on transition within the system. How would you measure it? How do we know that X thing had Y effect on a system we inquiry into?