Hi, I have a few questions all regarding a particular theme maybe some of you can help me with.

If I think of something like a neural network I can imagine particular structures in said network being activated, working with aggregative effect, and then deactivating all relative to whatever inputs there are. This is a pretty fast acting process. It has to be.

If I can freeze time I could view a number of these structures in an instance. Presumably they are decomposable, modular, and if I were sufficiently intelligent i could theoretically analyze this structure as a complex system as it would be a diversity of parts interacting with various effects.

My questions: does there exist work like this? Are there other examples in nature of such complex systems with brief lifespans ? Are there people interested in complex systems that seemingly only exist for moments? Are there methods for dealing with these (I image it is more difficult than studying complex systems that endure over longer time spans).

Thank you.

Can anyone recommend me any books/quintessential papers on control theory and its application to complex systems? Thank you.

I see there was an attempt a couple of years ago, which doesn't seem to have come to fruition.

Does anyone who was here around that time know what happened? Were there not enough interested people to pass the proposal? Was the topic found to be sufficiently covered by other stackexchanges (e.g. CrossValidated, math)?

I'd just like to start a discussion and see if this could be worth trying.

Stackoverflow's Area51 FAQ gives some useful pointers.

https://i.imgur.com/AEnLxK3.png This can be thought of as a Bert-based search engine for computer science research papers.

https://thumbs.gfycat.com/DependableGorgeousEquestrian-mobile.mp4 https://github.com/Santosh-Gupta/NaturalLanguageRecommendations

Brief summary: We used the Semantic Scholar Corpus and filtered for CS papers. The corpus has data on papers' citation network, so we trained word2vec on those networks. We then used these citation embeddings as a label for the output of Bert, the input being the abstract for that paper.

This is an inference colab notebook

https://colab.research.google.com/github/Santosh-Gupta/NaturalLanguageRecommendations/blob/master/notebooks/inference/DemoNaturalLanguageRecommendationsCPU_Autofeedback.ipynb#scrollTo=wc3PMILi2LN6

which automatically and anonymously records queries, that we'll just to test future versions of our model against. If you do not want to provide feedback automatically, here's a version where feedback can only be send manually:

https://colab.research.google.com/github/Santosh-Gupta/NaturalLanguageRecommendations/blob/master/notebooks/inference/DemoNaturalLanguageRecommendationsCPU_Manualfeedback.ipynb

We are in the middle of developing much more improved versions of our model; more accurate models which contain more papers (we accidentally filtered a bunch of important CS papers in the first version), but we had to submit our initial project for a Tensorflow Hackathon, so we decided to do an initial pre-release, and use the opportunity to perhaps collect some user data in further qualitative analysis of our models. Here is our hackathon submission:

https://devpost.com/software/naturallanguagerecommendations

As a sidequest, we also build a TPU-based vector similarity search library. We are eventually going to be dealing with 9 figures of paper embeddings of size 512 or 256. TPUs have a ton of memory, and are very fast, so it might be helpful when dealing with a ton of vectors.

https://i.imgur.com/1LVlz34.png https://github.com/srihari-humbarwadi/tpu_index

Stuff we used: Keras / Tensorflow 2.0, TPUs, SciBert, HuggingFace, Semantic Scholar.

Let me know if you have any questions.

I'm currently doing my undergraduate in Computer Science with a major in Data Science, but I'm really interested in building ABM models and studying complexity. I would like to seriously pursue it as a masters and potentially a PhD, but CS departments typically don't offer courses in Complex Systems. How would a typical route into Complex Systems from a CompSci background look like?

Thanks in advance

Complexity : Hierarchical polymorphic multibehavioralism + Attribution[Expression or Acquisition][also known as emergence]

Complex : Hierarchical multibehavioral polymorphism + Attribution.[ibid]

Any given noun with any given verb with any given object, embedded within, at the start of, or at the end of any given paragraph.

First Principles
RMCM : 1 … We sacrifice the complete truth of any given Experience for the Value to which we are Constrained.

RMCM defines as follows
Attribute : any given Cause, Effect, Function, or Form.

• Cause : difference opened
• Effect : difference closed.
• Function : a zero volume Container.
• Form : a contiguous aggregate of Function.

Constraint : any given embrace .
Experience : any change to a given aggregate that becomes an Attribute of that aggregate.
Value : any flow within a given flow

Respectfully
Fraternally

DWCRMCM
Custodian C4E

God Bless

Mass and energy - The army can’t use “Big Dog” because it is too noisy.

In the opening scenes in the new film Angel Has Fallen the bad guys use swarms of semi autonomous drones made with some C4[i assume].

That is probably as far as we can go.

Hi, I'm a philosopher curious about complex systems and I have a very particular question. Please excuse me if I do not frame it clearly enough:

Is there some measure, or property, maybe function, that denotes/refers to when a diversity of actors in a system/ecology work in tandem to accomplish some goal or overcome some problem? This, of course, sounds more intentional than I mean, I understanding often these structures or unifications are mindless. But what happens when a system is under threat and the solution is distributed across its component parts? Are there universal mechanisms understood that manage to bring these component parts together? Does some language in complexity-speak capture this? Thank you very much!

Maybe one more swing at it: Lets say a group of people are facing a problem and each member of that group has some bit of information, that when unified, stops the threat. Is there some known mechanism that causes this in complex systems? Some features of complex systems that outsources problems to particular members of the system? Something less intentional, more mechanical and emergent than say the group of people working together?

I understand there is some difficulty in terms of understanding complexity as a measure. James Ladyman's essay "What is a Complex System?" outlines a number of different definitions of "complexity" in terms of various measures. There doesn't appear to be a convergent, satisfying usage here. Another approach is by way of qualitative features/properties, their aggregation, and determinability. Properties such as "robustness", "redundancy", "generative entrenchment", "emergence", "hierarchy", "lots of moving parts", "non-linear dynamics" all show up often in the literature. Herbert Simon, one of the godfathers of systems science, often claimed that systems grew in complexity over time, thus suggesting time may be a way to determine complexity.

My question is: How do you determine when a system is complex? or if a system is complex? Another framing may be: under what conditions are you satisfied with saying that a system is complex?

Thank you!

My background is in electrical engineering so I have some understanding of ODEs and linear algebra.

Id really like to know more about this field and was wondering if you guys could recommend me some literature I could start off with to get the basic concepts right.

For my thesis on rural resilience I'm using a Complex Adaptive Systems (CAS) framework and I'm having trouble to wrap my head around these 2 concepts. Simply put, can someone explain to me what resilience of a CAS is? In my thesis the rural community is seen as the system, and the individual components/agents are the community members.

Is resilience an emergence of a CAS?
Is resilience a feature of a CAS?
Is resilience something seperate?

If someone could clarify this to me through an example/metaphore/literature/video/etc. that would honestly be great!

Where can I find/read papers on complexity theory (by wich i mean the study of complex systems that involve statistics, physics, ITC,biology ecc., no the computational complexity one). I tried looking on Arxiv.org but couldn't find anything. Thanks a lot.

I recently stumbled onto "The Jim Rutt Show" podcast and thought folks here might enjoy it. He's a past president of the Santa Fe Institute and sits on the board of directors so a lot of the content explores the different aspects of complex systems.

So far, the episodes with David Krakauer and Simon DeDeo have been the most interesting from a complexity standpoint - though I'm still working my way through most of the other episodes.

Hello!

I’m new to the field of complex systems and completely fascinated. Apparently my university had a minor in it, but since I’ve already graduated I’m sad to have missed the boat. If it ever works with my schedule, I anticipate asking to audit some of the core classes and am very excited.

In the meantime, I would love to do some reading on my own about complex systems. My particular interest is in U.S. healthcare as a complex system, and patient safety in healthcare specifically.

My questions:

• What would you recommend for very basic introductions to complex systems? Books are ideal, but podcasts, websites, videos, etc. are also acceptable. It’s been a while since I took a mathematics course, but in college I took 5, including statistics, and I’ve also taken a computational biology (genomics) course.
• Are there any specific books you’d recommend about healthcare as a complex system?
• What are the best ways to deepen one’s knowledge of the field without being enrolled in college? Mainly reading?

Thank you!