hdarshane

Thank you so much for the link to those two papers. I'll try and go through them.

>Like, they undergo many cell cycles during one organism's life, but they're not really evolving or being selected during each cell cycle.

This is a really interesting perspective.

>You ought to get yourself connected with some folks at the Santa Fe Institute, if you haven't already. I know one affiliated professor, let me know if you want an introduction.

I have read a few posts from SFI faculty and seen some video lectures of Krakauer and others, but as you said, I should get in touch to some degree.

You're very kind and I really appreciate you offering to intro me! I would really love that!

Would you mind if I follow up on this via e-mail? Can I send one to the address mentioned on your Vanderbilt department page?

Thanks a lot!

>This is especially tricky in the field of bio / biochem, which feels like it requires memorizing a million facts before one gets to do any real thinking and reasoning. This unfortunately tends to filter out a lot of more mathematically-minded people who are stimulated by puzzles, which I think is a shame.

yes, this is exactly the part that makes it really really hard...

thanks a lot for the recommendation!

Huge thanks for the list! Interesting to wonder just how influential or generally just of what nature cybernetics would be today without funding issues, lack of categorisability and the field slowly drifting away from the original vision Wiener had.

Thanks a lot for your kind words!

Really like your thoughts!

Indeed, lack of time-series observability makes it harder for us to find general patterns or causal events.

Definitely agree that biology is the pinnacle of all complexity - IMO something like macroeconomics or human behavior within set systems (society, politics, etc.) is fairly reducible to a very small and finite set of incentives that agents optimise for (food, shelter, status, acceptance, etc.).

Given this, Non-linearity and stochasticness still adds up to a general nature of non-determinism for the entire system.

With Biology on the other hand is extremely more complicated to study as - correct me if I'm wrong - it's still hard to realise what agents in systems are optimising for. reduction of free energy? reproduction? general homeostasis? etc. and then all these play varying roles in diff contexts, and then we'll still have to figure out how/why self-assembly and "wholes" emerging from smaller "wholes" (... ad infinitum) actually happens.

Really fuzzy thoughts but I believe There is some merit in exploring reducibility and observability from a time series perspective while considering effects of synchronity/asynchronity of observability and later how much we can desirably steer systems. Really fuzzy but I hope to work on this a bit more.

Thanks a lot for your very interesting comments! Not discouraged at all, love your view on systems theory being a "routine analysis" like statistics, i.e. a very generally applicable layer or meta-science that's an entirely new way to see things, which I should've articulated better in my post.

Thanks a lot!

I think that tool might be just any general framework that gives a better idea of what any small microscopic actions might lead to at a high-level. We definitely cannot qua(nt/l)ify how actions seep through given free-will and a general fringe-ness to us. We can still at least identify most probably scenarios without much difficulty. I believe behavioral economics or even epistemic studies do a good job of identifying general trajectories, by virtue of a fairly high sense of reducibility given human behavior and the benefit of hindsight respectively.

Indeed the human mind by itself isn't really trained to think beyond maybe one or two orders of implications that actions hold. Hindsight and somehow modelling agentic behavior by understanding incentives might do the trick.

Thanks again!

Thank you so much for the kind words! I'm definitely a little ignorant with respect to systems biology efforts. I have an okay-ish idea of the work of someone like Uri Alon, it's definitely not enough. What resource would you recommend for me to jump into? Uri Alon's course? I believe I lack many pre-requisites to take it.

Oof yeah. The legibility-gained per effort put in for most admins working in a system that inherently incentivises tangibility and observable "utility" (whatever that may be in this case) reduces any hope of seeing much change.

Maybe this is another good problem that Systems Sciences might hold a great explanation too :-O.

Thanks!

Yeah, entropy definitely has been included in some forms of thought that are very correlated with complex systems. Schrodinger early on had a very interesting insight on life and entropy, people like Jeremy England are taking that view forward. Work by England, Crooks, etc. very beautifully relates entropy and the probability of any state x existing more than all others.

The information theory counterpart of entropy seems extremely relevant in describing coordination failures, some forms of stochasticness that aren't necessarily derived from lots of molecules with high degrees of freedoms interacting together. Also might hold high explanatory power in describing why trickle-down/bottom-up and top-down effects are slowly negated and diluted - although I believe this is fuzzy thinking and we need a better tool than just entropy to understand this.

Thanks!

Wow. This is a really informative comment.

>While I agree that nitty gritty formalizations are important to grasp, it's been made clear that the formal sciences were often insufficient in facilitating insight on the type of complexity cyberneticians cared about -- especially that of process oriented circular causality, which often involved paradox and self-reference.

I wholeheartedly agree. Hence why I think we are dealing with an entirely new type of science, the basic principles and theorems are yet to be discovered.

Lots of interesting pointers and links throughout. Thanks again!