Dear Eric and Steve, and the gang,
When I first moved to Santa Fe on Sabbatical 12 years ago, I was merely 67, and
there was a chance, just a chance, that I might become expert enough in
complexity science and model programming to deal with you guys on a somewhat
equal footing. But that never happened, and, now, it is too late. I am amazed
by the intricacy of your discussion and the broad reach of your thought. There
is really little more than I can do then wish you all well, and back out of the
conversation with my head bowed and my hat clasped to my chest.
Before I leave this conversation, I would like to offer the dubious benefits of
what expertise I do have, which concerns the perils of circular reasoning. I
come by that expertise honestly, through years of struggling with the odd
paradox of evolutionary biology and psychology, that neither field seems every
to quite get on with the business of explaining the design of things. When
George Williams famously defined adaptation as whatever natural selection
produces he forever foreclosed to himself and his legions of followers, the
possibility of saying what sort of a world an adapted world is, what the
products of natural selection are like. One of you has pointed out that this
is an old hobby horse with me, and suggested, perhaps, that it's time to drag
the old nag to the glue factory. But I intend to give it one last outing.
So, I have a question for you all: Do you guys know what you are talking
about?! Now I DON’T mean that how it sounds. I don’t mean to question your
deep knowledge of the technology and theory of complexity. Hardly. What I do
mean to ask is if, perhaps, you may sometimes lose sight of the phenomenon you
are trying to explain, the mystery you hope to solve. Natural selection theory
became so sophisticated, well-developed and intricate that its practitioners
lost track of the phenomenon they were trying to account for, the mystery they
were trying to solve. We never developed a descriptive mathematics of design
to complement our elaborate explanatory mathematics of natural selection.
Until we have such a descriptive system, natural selection theory is just a
series of ad hoc inventions, not a theory subject to falsification but “a
metaphysical research program” as Popper once famously said, which can always
be rejiggered to be correct. Is there a risk of an analogous problem in
complexity science? You will have to say.
So, I will ask the question again: Do you guys know what you are talking
about?! What is complexity?? If the answer you give is in terms of the deeply
technical, causal language of your field, there is a danger that you have lost
sight of what it is you are trying to account for. And here a little bit of
naivety could be very helpful. Naivety is all I have to offer, I will offer it.
Whatever complexity might be, it is the opposite of simplicity, no? It is in
that spirit that I propose a working definition of complexity with which to
explore this thread’s question: “Are any non-biological systems complex?”
An object is any collection or entity designated for the purposes of
conversation.
A system is a set of objects that interact more closely with one another than
they do with entities outside the set.
A system is complex if the objects that compose it are themselves systems.
Only when complex systems have been clearly defined, is it rational to ask the
question, “Are any natural systems complex?” Now you may not like my
definition, but I think you will agree that once it is accepted, the answer to
the question is clearly, “Yes!”
Take hurricanes. Is a hurricane composed of thunderstorms?
Clearly, Yes. Are thunderstorms themselves systems. This is a bit less clear,
because the boundaries among thunderstorms in a hurricane may be a bit hazy,
but if one thinks of a thunderstorm as a convective cell -- a column of rising
air and its related low level inflow and high level outflow – then a
thunderstorm is definitely a system, and a hurricanes are made up of them.
Hurricanes may also display an intermediate system-level, a spiral band, which
consists of a system of thunderstorms spiraling in toward the hurricane’s
center. Thus, a hurricane could easily be shown to be a three-level complex
system.
Notice that this way preceding saves all the intricate explanatory apparatus of
complexity theory for the job of accounting for how hurricanes come about. Now
we can ask the question, What kinds of energy flows (insert correct
terminology, here) occur in all complex systems? Notice also, that this
procedure prevents any of us from importing his favorite explanation for
complex systems into their definition, guaranteeing the truth of the
explanation no matter what the facts might be, and rendering the theory
vacuous. .
One last comment. When I wrote that perhaps we might inquire of the system
whether it is complex or not, I left myself wide open to be misunderstood. I
meant only to say, that it is the properties of the system, itself, not its
causes, that should determine the answer to the question. Remember that, in
all matters, I am a behaviorist. If I would distrust your answer concerning
whether you are hungry or not, I certainly would not trust a systems answer
concerning whether it is complex or not.
I miss you all already. If any of you have any inclination to envy a sojourn
in the East, just be advised that the sun has barely been out since we got
here, the temperature has NEVER been above 75, and… and … I can walk to my
mailbox without touching the ground on the backs of the deer ticks waiting in
ambush outside my front door. Why Roger has not died of exposure or rickets in
Boston Harbor is a mystery to me.
All the best,
Nick
Nicholas S. Thompson
Emeritus Professor of Psychology and Biology
Clark University
http://home.earthlink.net/~nickthompson/naturaldesigns/
-----Original Message-----
From: Friam [mailto:friam-boun...@redfish.com] On Behalf Of Eric Smith
Sent: Saturday, June 03, 2017 11:53 AM
To: Stephen Guerin <stephen.gue...@simtable.com>
Cc: The Friday Morning Applied Complexity Coffee Group <friam@redfish.com>
Subject: Re: [FRIAM] Any non-biological complex systems?
Hi Steve and Nick,
Sorry to have dropped off. I tried to read the very vigorous thread, to the
extent I could, as it went by. There is a lot there that seems to remain in
the core of one thing that brings this crowd and several others together, and
is conceptually far from finished business. I can’t aim for Nick’s precision,
or Steve’s coverage, unless there is some particular thing to solve, so my way
of doing these things tends to be more limited than the main thread was.
On Russ’s question, I tried to give a lecture in an informal summer school a
couple of years ago, to propose what sequence of changes in physical
architecture would justify bringing in each of a series of new concepts. I
don’t have worked examples behind any of these cases (for a couple of them
there are toy-model ideas), so this is the kind of work that is probably of
little value and even less trustworthiness. I don’t remember exactly the
layout, but I think the sequence contained something like this (ALLCAPS are
meant to be informal descriptors for concept keywords):
1. Protected degrees of freedom are a precondition to even the possibility of
MEMORY. If you are a mere physical degree of freedom, and you are always
coupled to your environment, you are nothing different than an
instant-by-instant reflection of the immediate local state of your environment.
All of the later concepts in the list require various forms of internal state
that have enough insulation to be protected from constant harassment. So where
in the physical world are suitably decoupled degrees of freedom available to be
found? (Much later, to be built, but not yet.)
2. Some kind of dynamical variables need to be capable of being couplers that
can become DOORWAYS, so that the other DOF are sometimes coupled and sometimes
not. A DOF that is always behind a wall (a chemical reaction behind such a
high energy barrier that it is never achieved) can’t remember anything because,
although it can certianly hold a state, it is never in contact with the
environment that would imprint anything on that state. This doesn’t yet talk
about how the open/close states of the doorway happen, which will determine
when and what it allows the environment to imprint on the memory variable, and
for how long that imprint can be held. Here one can be quite precese with
examples without invoking biology. Organic chemistry at low energy in water is
largely non-active. Metal centers, particular d-block elements, are the major
doorways that govern the sectors of organic chemistry available to early
ocean-rock worlds. Many enzymes still use them in something not too far from a
mineral or soluble metal-ligand complex state, with a little tuning. In this
case, the doorway works just through physical drift. Molecules free in
solution are inert; those that bump into a metal can potentially become active;
when they dissolve and drift on, they become inert again. This leads to a very
different set of relations between thermal energy and information in reactions,
than simple thermally-activated reactions among the same species. Probably one
can invoke many other examples.
3. Some of the internal variables need to be capable of carrying on an
AUTONOMOUS dynamics or internal process. I guess a memory variable can sit
there passively and still, at some level, categorize the way a system (set of
DOF) responds to an environmental event, but for most of the later levels,
there needs to be actual internal dynamics. This in itself is not so hard; the
world is far from equilibrium in any number of dimensions, and for something to
be moving in a direction is not rare.
4. Internal dynamics can be autonomous, but it isn’t really “about” anything
unless something about the configuration constitutes a MODEL in the sense of
Conant and Ashby from old 1950s control theory. How the model is registered,
and how reflexive or self-referential the internal dynamics needs to be for a
meaningful model to be imprinted, probably ramify to many differenent
questions. I would of course be happy to produce an interesting case of the
emergence of any of them.
5. At some stage, a protected internal process of which the state of the model
is part needs to act back on the doorway, if we are to be justified in saying
the basic relation of a CONTROL SYSTEM has come into existence. Here again I
intend a Conant and Ashby line of thought: that “Every good controller
“contains? entails?” a model of the system controlled. There has to be some
internal state that is capable of being in different relations to the state of
the world, and then the internal dynamics has to take an input from a
comparison of those two states. Only if the resulting action feeds back on the
state, does the system start controlling its own interaction with the world
(for instance, what gets remembered).
6. The next one is hard for me to say, even at the very low standards of the
previous five: I can be a control system with a model of my world, even if I
have only modest machinery. A membrane-bound protein that lets in some
molecules and ignores others, and which is preserved in a population through
some kind of filtering, is a perfectly good control-theoretic model in the C&A
sense. But it only implicitly models its environment. I have not yet added
the assumption that there is some kind of REFLEXIVITY or REFLECTION (in the
sense of Quines) so that the model includes representations of possible
counterfactual states of the internal variables themselves. If there is a
physical process that drives a system’s parts into a configuration where that
happens, then one of the things an internal process _could_ do is use the
modeled futures to internally select among many responses to a situation of
which it is capable. Only at that stage would I feel compelled to introduce a
concept of AGENCY, where for my practical purposes, I am happy to use the word
as game theorists use it. An agent is a kind of thing that fills one of the
slots that games have for “players”, which must be provided for the mechanics
of the game to execute, and where the agents have some way to convert
specification of the game into a sequence of moves that are not individually
dictated by the game itself. I am sure there are lots of other notions of
agency (ABM has a much more permissive notion, which can be as little as a
dynamical Monte Carlo, or can be full-blown game-theoretic player), but for the
purpose of trying to draw levels from the foregoing, this one seemed enough to
me to propose a concrete problem.
I am sure there are more, but I think I stopped there, and this was about as
far as Russ was asking, too, I think.
So the challenge (speaking only for myself, of course) is to find places in
matter where the structure of the dynamics as one starts with it, drives the
activity into regions of material architecture that take on first one, and then
another, of the above new patterns. I assume they have to occur in more or
less this order, because it is hard for me to see how to build the later
concepts without having the earlier ones as building blocks. I like chemistry
as a medium, because the state space itself supports a lot of complexity, and
the temporal variability of reactions, plus the fact that catalytic relations
exist, offer large separations of timescales that can be used to fill
functional classes like memories. Whether it becomes hard to build much
hierarchy in any system that doesn’t benefit from the intensive way chemistry
makes complexity easy, is a question I find interesting. I don’t know how one
answers it with better than musing.
This is all kind of armchair statements of the obvious, and I don’t mean to
make it out as more. I know there are people like Rosen who made long careers
of trying to tease all this out at length, and have written a lot on it. Maybe
they include all this obvious stuff and also much more.
But branching, to Nick’s point about the extent to which “a system” “chooses”
something about the relevant delimitations of itself. I think this becomes an
operationalizable question in the spirit of Leslie Valiant’s PAC learnability
framework. (Probably Approximately Correct). Valiant’s wish was to show that
the learnable tasks, like the computable functions, make a formally definable
class. I don’t think that discussion is anywhere near being closed one way or
another, but the attempt to systematize what can be learned, how hard it is,
and how much either of those depends on the embedding context, seems very
helpful and clarifying to me.
The connection would be this: Suppose you have some internal state, and some
internal dynamics, and the state under the influence of the dynamics — or even
intervals within the dynamics under the influence of their longer trajectory —
can pass through many different patterns. Suppose that somewhere there is a
reinforcement learner working on those patterns in some systematic way. It
could be an environment selectively filtering many copies of you with slight
variations, or it could be some other subroutine within your internal dynamics.
The kind of thing I have in mind is: suppose there is a synthetic organic
chemistry generating small molecules, lots of copies of some of them, fewer
copies of others, and as a by-product of that molecular pool, something like
polymers large enough to be capable of function, but happening to have
functions only at random, are one of the things that can arise. Out of all
this mess, focus on the PAC-learnability problem of evolving an enzyme. The
things that should determine whether a given selective protocol can find and
then fix something should be:
1. how frequently is that substrate even encountered? If not often, it is hard
to maintain any memory about it. It is easy for farmers to remember to water
the crops during dry spring winds, because that happens every year. It is
harder for a culture to remember to run uphill when the tide goes way out for a
very long time, since maybe that hasn happened where they live in the past 600
years.
2. how consequential is the particular molecule. If very consequential,
selection can be more severe, and leave a stronger signal, which maybe can be
remembered a little longer.
There is probably lots of other fine structure to learnability, such as whether
the environment is effectively serving as a “teacher” with respect to that
particular problem (Valiant’s term, used to illustrate concrete cases), but I
won’t ramble more than this.
How does that relate to Nick’s point; one more indirection on the way to
getting there:
Steve mentioned (in some thread, a few weeks ago) the concept of Order
Parameter, which is a kind of predictive statistic that suddenly starts to have
a lot more predictive content, and to be more stable, when a system goes into
an ordered phase. If you are going to try to use reinforcement learning to
select higher-order structure on some low-order patterns that you are already
producing, the order parameters are the things that take the most regular
values, and they most robustly support induction, which is what all
reinfocement learning is. (A finite system cannot help but induct: in a world
of potentially unlimited variability, it has only finitely many possible
states, so perforce it will make infinite equivalence classes of environmental
states, by responding to many situations that in detail are different, with the
same response. That doesn’t mean that “the problem of induction” “has” any
solution. It only means that every finite system is perforce a commitment to
some inductive hypothesis.)
So I would argue that, with respect to the accumulation of hierarchy, there is
a natural sense of a system’s own delimitation, to the extent that the parts
that are sufficiently stable and sufficiently consequential to build something
on top of by reinforcement become the foundation that holds other parts
together. I agree with the purpose underlying Steve G’s point: that this can
depend in part on what kind of environment there is, since this is part of the
learning protocol. But we also all recognize that — at least insofar as the
statistical concepts found useful in equilibrium thermo and fundamental
processes continue to be useful in more elaborate dynamical realms — the Order
Parameter as a Minimum Sufficient Statistic for distributions over future
states is an informationally special quantity.
Sorry for long harangue, and I don’t know whether this has anything new in it
that the list hasn’t revisited many times.
All best,
Eric
> On May 29, 2017, at 8:29 PM, Stephen Guerin <
> <mailto:stephen.gue...@simtable.com> stephen.gue...@simtable.com> wrote:
>
>
>
> ______________________________________________________________________
> _
> <mailto:stephen.gue...@simtable.com> stephen.gue...@simtable.com
> CEO, Simtable <http://www.simtable.com> http://www.simtable.com
> 1600 Lena St #D1, Santa Fe, NM 87505
> office: (505)995-0206 mobile: (505)577-5828
> twitter: @simtable
>
> On Mon, May 29, 2017 at 12:10 PM, Nick Thompson <
> <mailto:nickthomp...@earthlink.net> nickthomp...@earthlink.net> wrote:
> SG,
>
>
>
> There are now THREE issues lurking here between us.
>
>
>
> IS THE CRITERION FOR A SYSTEM ARBITRARY: You say yes; I say no. We’ve
> already covered that ground.
>
>
> In my post, I said it is not arbitrary. It's a function of what the
> researcher is trying to use it for or explain.
>
>
>
>
> IS A HURRICANE A SYSTEM: For me, that is the question of whether the
> collection of thunderstorms we call a hurricane interact with one another
> more than they interact with their collective surroundings. Another way to
> put this question is in terms of redundancy. If we were to go about
> describing the movements of the thunderstorms of a hurricane, would we get a
> simpler, less redundant description if we referred their movements to the
> center of the hurricane. I think the answer to this question is clearly YES.
>
>
> Yes you could model the movement in a simpler way by modeling the movement of
> the center point. And that was my second model of a hurricane as a random
> walker biased by a global wind vector and Coriolis curve term. And I said
> that was not a complex system.
>
>
>
>
> IS A HURRICANE COMPLEX? For me, complexity means “multi-layered” . So, a
> complex system is one composed of other systems. A hurricane is a system of
> thunderstorms which themselves are a system of thermals (handwaving, here).
> Thus a hurricane is at least a three-level system. So, yes. It is complex.
>
>
> I agree about complex systems as having multiple layers - a macro
> scale and a micro scale. I would say there's one system. If I was
> trying to model a hurricane in my first example of an emergent vortex
> dissipating temperature and pressure gradients, I would model the air
> with a combination of air particles and patches of air - at LANL they
> would describe these as particle in a box models or hybrid lagrangian
> and eulerian models. I would not introduce thunderstorms at the micro
> level. But there's many ways to skin a hurricane :-)
>
> Some would say the micro level air particles and air cell components which I
> would model as finite state machines (agents with a lower case "a") are
> systems in their own right and have boundaries. I don't see the benefit of
> calling them systems as their aren't multiple interacting components within
> them. But don't feel like arguing too hard here.
>
>
> Eric Smith?
>
>
>
>
> Yes, where are you Eric Smith?
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