Philip Forbes Henshaw...   on natural systems
(those special machines of nature and how they record their accumulative learning)
You might start by asking  Why?    (why think about the life cycle of change?) or What to do?? (to steer our unmanageable world.)

eds. 3/9/04,05,06,07,08,09, 1/21/10 1/23 2/6 (note ed. dates indicate how current paragraphs are)2/12 This is about how anyone can learn to better observe and understand the changing systems of their own environment.  Why people don't understand these uncontrolled systems seems quite largely because science carefully avoids studying them, concentrating only on things that seem to follow rules.   Appreciating how uncontrolled systems make up their own rules as they go is about closely watching them, identifying large and small cells of climate and economic processes and personal or ecological relationships as they develop and change form, like storms, technologies and our friendship circles and the balances of nature around us.    There are their tipping points, approaching dead ends and emerging new forms to identify.    What usually marks their irreversible change, as opposed to incidental change, are the patterns of successively bigger or smaller steps of change.  Those are what indicate developing or dissipating environmental systems, the enduring structures of nature.

One develops mental models of them, but mostly as questions about what's changing on its own.   It would help scientists to see what complex systems in an environment might be modeled, too, and when the real system has or is about to change form and models of it will need to be changed.    It's about raising better questions, considering natural systems as changing by accumulating new features as information in their physical designs, as organizational learning processes themselves, made possible by watching their conserved change accumulate .   How to tell the ones that are persistent and for which organizational change is strictly accumulative and permanent is one of the important steps. 

Considering natural systems as processes of accumulating organization engaged in learning about their environments allows you to view them as controlled by how they explore their environments and what they discover, instead of as controlled an observer's rules of prediction.   A mouse explores its environment its way, to find food.   A business explores its environment its way, to discover markets.  A teenager does to find who there is to hang out with.   Each is forms a network regular connections, the environmental relationship itself, that serves as a platform for finding new ones, establishing a presence in the environment and a way of growing and responding to growth limits.    Sometimes an observer can see what they are about to discover, letting them anticipate what to do then.   The same stages of development and variety of outcomes for new personal relationships can be seen in the life story of more complex environmental systems like businesses or cultures.

Such new networks of environmental relationships are "special machines", things that change form as they find room to take off, and change form again when they run out of room.  That's their growth phase and maturation phase for systems that will persist beyond their own initial growth.    Normal models and theories fail to suggest how such natural systems continually change as they interact with their changing environments.   Natural systems have distributed parts, and tend to change everywhere at once, often in seemingly coordinated ways and without controls.   Sometimes they just "go zoom" in some fantastically orchestrated way, for no apparent outside cause at all.   They're individually "eventful".  Their biggest changes in form come when they discover something and take off, and then when their limits trigger them to either stabilize or run down.   "Simple machines" don't do those sorts of things.    "Simple machines" is all people and theory can define, though.   So this is about getting "simple machines" to point at nature's "special machines", as better questions about them, helping an observer to see their features and learn to tell when they're changing.

One thing that points to them is their succession of progressive development trends, and reading them as narratives of their organizational processes.   Identifying a local development trend lets you associate it with everything working together as a whole to produce it, to recognize what's happening in total, and as changes progress from one direction of development to another.  It's whole system learning from beginning to end.   So there's the art of observation and the general approach and other topics.    The rigorous scientific "hook" making it a new scientific method is building the narrative around the sequence of developments required  by the conservation of energy for the physical continuity of energy flows.   The form of the narrative is derived from the Law of Continuity, which opens up a useful new approach to general physics of change, consistent with thermodynamics but not with some of its more common interpretations.    Other physicists are still generally hesitant.   The problem is how to treat scientific information, whether as well defined representations of nature or also for referring to physical things we can't define.    It's a mysterious philosophical conundrum, with a long history.   Learning to separately discuss physical realities we can only point to, not confusing them with the information we point with...  looks like the trick.   

Please do ask if things are not clear.   If I say things that seem to conflict with your beliefs, ask why I might suggest it, or if I was just misspeaking for your way or reading it.   Sometimes I'm trying to suggest a range of possibilities, sometimes I'm omitting something that should have been mentioned.   Let me know.   We definitely have a lot to sort out in many ways.

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Some quite simple answers for complex problems... (by finding  the right question)
The problem with wealth	Businesses need to use finance, but finance is habitually used to put money into businesses to take more out, in an endless cycle the multiplies.   That requires businesses to continually multiply their products and innovations.   It works logically OK, but just not physically.   Multiplying products can only be temporary, but finance requires it to be permanent.   That, and why we've failed to notice it, are our root problem, finding how business can remain profitable and not need to continually multiply.
Why people don't respond	People back away from understanding how their own cultural beliefs are modeled on physical impossibilities... like ever multiplying money, for example, or that science can describe everything as a machine.   Our cultures seem to be built around dreams, generally, and as nature shifts the playing field we may miss the signals and get confused as to what the reality is.   The reality has been changing.    Learning to be curious about the difference, between images and realities, offers a great deal more than just helping you stay out of trouble, of course.
The problem with impacts I = P • A • T • S	It's actually a 150 year old discovery repeatedly confirmed that using improved efficiency to reduce our impacts on the earth overlooks the growth stimulus, and causes the reverse.  The ratio is 2.5.   Economic efficiency saving 1 gal. of gas stimulates new uses consuming 2.5 gal, on average worldwide!   Efficiency makes it easier to use energy... taking less for one thing, AND letting us do more things...   Which is the safer bet for saving the earth, what the economy does or what our theory says it should do but doesn't?? -- more below    "The math joke" Impacts on the earth = Population • Affluence • Technology costs • Stimulus (of new uses)
• • • • better questions don't end the task of finding what to do, but give you a more solid place to begin • • • •

.

		(This graph shows 5 choices for when to respond to an approaching natural limit, asking when to respond to reach growth limits at a peak of vitality rather than at a peak of exhaustion.   ... and the need to study your path, not your past.) (click to enlarge)
...current cartoon... .....more.....
© 1995-2010 reproduction, review and quotation encouraged with attribution.

Delayed responses to approaching limits risk exhausting yourself and loosing control.  

So the #1 sustainability issue today is our delay in asking why growth would change from making everything cheaper and easier to making everything more costly and complicated.   That's the time when our way of solving problem begins to multiply them, creating more conflicts instead of freedoms as it once did.   
Finding and solving the true causes may be more challenging but  that at least addresses the right problem, correcting our Type III error, using the wrong model and accepting the wrong questions it gives us.

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General Essays
What's so different here? - The problem with systems  -  Reading Hints... -  The top sustainability issue in the world today? 
What are Natural Complex Systems? - A question, does all change evolve?

General Scientific Theory & Method:
Current work  Physics for Open Systems

Lists etc.

Some things to fix? - Concept & Comment essays - Publications - Odd Facts - Philosophy in a Phrase - Bio - Life Tools Arts 
                                  

Science is all about observation, of course, but almost exclusively focused on observations about how things of the physical world are externally controlled, using controlled experiments, for example.

The problem with that, of course, is that it makes learning how to observe the things of our world that choose their own paths, and are significantly self-controlled, into a lost art. 

I say "lost art" because our common languages are filled with terms for how people, our cultures and communities, and other kinds of organisms of all sorts of nature actively explore and steer their own paths in their worlds.   After you learn to look for it you find it's a fairly common property of natural systems.  For centuries it has been represented as something that happens nowhere in nature except in the minds of the one self-conscious species.  That's just a bit of an exaggeration.    It takes effort and a playful approach to demystify it, but it's just a wonderful lost art in the end. 1/8/10

Information actually controls nothing but our predictions, but it's become popular to redefine nature as being what we can predict.
What leads you to understanding something
about the worlds of nature we completely rely on taking care of themselves,
is not prediction however, but using the same information to help you ask better questions
about what must remain unexplained. ~3/28/09

The problem with systems

....4/10/09 05/20 6/17 7/9 is that people don't recognize the vastly complex natural machines by which the world works.   Natural systems don't operate by our explanations, and how they do operate is as yet quite inexplicable to us.    Natural systems arise from their environments by local development, which is one inexplicable thing about them, and operate without instructions or controls, using processes occurring differently everywhere at once.    "Seeing" things is to make sense of them, so No Wonder we don't see them!   We can begin to though.   It takes learning some strategic ways of reading beyond your information, and discover the implied processes of sweeping change we are caught up in.   The key to foresight with them is recognizing the kinds of progressions that end by upsetting the regularities they display (growth | integration | disintegration | decay), so you can learn to watch them to learn about change in natural system relationships has or is about to happen.    It's another way to read the fingerprints of nature's transformations.     Traditional scientific theory is mainly used to build predictable models that interpret nature's stable behaviors of the past, not to read nature's instabilities for clues to her changing complex organized forms.   

The problem with our concept of I = P • A • T is that it's missing the hidden 'S' for growth Stimulus 

Impacts on the earth = Population • Affluence • Technology efficiency • Stimulus of increasing productivity

It's 150 year old established science, actually.   Why we use efficiencies is to simplify our tasks and become more affluent.   Our main purpose in improving organization and being more efficient with our tasks, often with improved technology, is to increase our productivity.   That's a growth stimulus.    That makes using it as a strategy for reducing impacts completely self-defeating.   Over a century ago Stanley Jevons noticed the effect in England when improving steam engines to use less coal accelerated the consumption of coal, not the reverse.   The added utility and growth stimulus of improved technology, and so the productivity of the people using it, increased the use of the resources it was intended to conserve.   

It was called "Jevons' paradox" because it is counter intuitive.   It's been widely discussed too.  People have simply not applied it to correcting our wishful thinking when it comes to saving the planet from our overconsumption...    Though long recognized by many scientists, even other scientist don't take it to heart, so it's been completely ignored in the public advocacy for sustainability by educators, activists, media and government in organizing, planning and research.    That's trouble!   It happened partly because people normally think by snap judgments, and "go with their intuition".   Here our intuition is dead wrong.    Somehow even modern economists have just never seemed to mention that as a strategy for impact reduction it fails entirely.   Someone needs to research the full story of the confusion.   It's both important intellectual history and critical for getting to the bottom of why we let our main solution for relieving our impacts on the earth be a direct multiplier of the very problem it was intended to address.

 
Sustainability does need efficiency, just not for stimulating even more growth.  It sadly does mean that the central tenet of sustainability that people around the world are now  relying on has the opposite of the intended effect on our environmental.   Look at the language of the proposals.   Even the strategies for climate change to reduce CO2 and other GHG emissions are entirely phrased as plans to improve the efficiency of growth.  Then look at the curve.   It only means money growing faster than impacts.  Ot assures that all our kinds of impacts will keep increasing ever faster too, even if marginally slower than the money someone is making off them.   The only way to stop adding to our impacts is to stop adding to the economy, really.   That means investors accepting their natural fiduciary responsibility for choosing what systems the economy will develop.  They'd need to actually use their profits from investments to no longer undermine the value of our common investment in the earth, and invest in long term sustainability instead.    That's possible, but means that a fundamental change in the design in the economic system is needed to make sustainability physically feasible.   

Those able to see these errors need to be employed in helping guide the change.  We need to fix this, and other fatal errors still part of our thinking.  I need help  
 

Everyone seemed pleased with my presentation on "Why Efficiency Multiplies Consumption" at the BioPhysical Economics 09 meeting in Syracuse on 10/17.   The slides and lecture notes are at EffMultiplies.htm.   Some related research notes, links and good short essays like the one below are at Errors in efficiency (10/19/09)    Going to the root, why our work ethic becomes an endless steeper climb  11/15/09 What in the world is really going on here? and what we need to understand to change it Peak Zucchini !

and then going a bit deeper in two short articles Inside Efficiency and How We get out of here?

Other top  systems theory issues ? and  sustainability issues ?

What are Natural Complex Systems? 

__________

 Particle, Atom, Molecule, Organelle, Cell, Organ, Body,

Community, Economy,  Population,

Ecology, Life, Planet, Solar System, Galaxy, Universe

The Continuities of nature arise with the local development of

Multi-scale Networks of physical relationships 

Acting as a Cell with an internal Medium of Exchange

And local Marketplace to internally Link its Hubs,

Which are themselves smaller scale networks containing their own Hives of activity

Surrounding their own Mediums of Exchange,

Cells on their own scale. that develop regularities as "Local Laws" of "Their Nature",

Small Universes with original design and behavior,

Linked together by sharing mediums of exchange with others, as part of larger scale networks,

Whole Physical Economies composed of independently behaving parts,

That we may refer to as features of our information. 

Complex systems work by themselves, sometimes predictable, but determined by how their processes develop locally.  There are two realities, the physical world and our mental world of human ideas, to be taken as dance partners rather than as enemies, denying neither their freedom, and avoiding the denial that is major trouble for both.  At the scale of growth systems, at least, natural systems  require diversity in their constituent parts and reserves of resources in their environments.   Those that grow also come to require stability.  Their creative hearts are the hives of network activity that form their cells, like the village that creates the reason for a train stop and the reason for the roads leading there.  Those hives of activity on any scale are where creative events develop to propagate like seed on the larger network scales, the process of emerging features that for a whole system "punctuates the equilibrium".     

Bob Ulanowicz has  recently published a theorem on the need for diversity in natural systems (1) concluding "all complex systems, including our monetary and financial one, become structurally instable whenever efficiency is overemphasized at the expense of diversity and interconnectivity".   What drives systems to overspecialize, though, and develop their strengths until they become weaknesses, is a broader issue.    An example of this I’ve been studying is why people advocating sustainability are attracted to using efficiency as a growth resource, though that ultimately creates instability as its end.  It appears that it used to have the opposite effect, and we got used to that.   When we were small and the earth was big, growth stimulated by efficiency used to make resources more plentiful and cheaper.   The economic theory of the last two centuries, then, built up around that assumption.   Now the opposite is true, growth makes resources more scarce and expensive.    If you look at the ‘green’ literature, these days, you find that fatal solution for sustainability (sadly...) is really all people talk about…

There are perhaps many misconceptions that lead our society to reduce diversity, for profit, till systems become unstable.  I once devised a general solution to the monetary part of the problem I called “general allocation theory”.   I found it hard to discuss with people.   The barrier seemed to be the need to discuss economic systems as individual organisms of a sort, "creatura" as Gregory Bateson would have called them, like self-organizing social or business networks as well weather systems and organisms, each with their own individual behaviors.   The still dominant "paradigm" of nature for science is that there are no independent systems, and everything that happens is determined by it's environment and error, so writing other better versions of that and other papers also received the same total lack of interest.   The preference is for representing systems with a set of rules of control.   

The natural systems approach is radically different in that systems are considered as individual self-organizations that originate by growth and development, and are full of different scales of independent internal activity, like what we observe.    Links on a network, for example, exist to connect these ‘hives’ of complex system activity, like the road and rail networks that connect homes, towns and cities, or the blood stream branches that connect cells and organs.   In economies there are the supply and product chains feeding into goods and service markets that link the individual hives of activity that individual businesses are.   It's a really good "telescope", something you can reliably find your way with, providing a great way to begin making sense of natural systems by looking for their mediums of exchange of different scale, through which their hives of organization connect.

1) Quantifying sustainability: Resilience, efficiency and the return of information theory 
Ulanowicz, R.E. / Goerner, S.J. / Lietaer, B. / Gomez, R. , Ecological Complexity, 6 (1), p.27-36, Mar 2009 
 

   2/7/09 2/12 pfh   

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Physics for Open Systems

What I mean by 'physics' here combines my use of physics to do it, and the intent to create a firm new common foundation for all branches of complex systems theory and practice with it, what the work is about.

             Intro Essays & quick links

• Complex Systems Science - 1/18/10 my Encyclopedia of the Earth review of complex systems theories and practices
• A Natural Systems Science Process 9/17/08  Using the conservation of change to
     discover the divergent & convergent workings of change!
• A Natural Systems Science Theory 5/16/07..09/08/07 02/19/08 a General Behavioral
     Economics, a Unified Physics of Open Systems  
• Bump on a Curve ¸¸.·´ ¯ `·.¸¸  Notepad For Dummies
     for  non-scientists who happen to watch what goes on 4/07
• Observing Systems
     a new reaching summary, in 22 short subjects -from the view of  6/06

• a Physics of Happening...  ¸¸¸¸.·´ ¯ `·.¸¸¸¸ physics research & applications
    analytical technique, theory & tools for research on natural systems as events
   

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                               Introductions

• The Art of Observation
• Emergence of Natural Systems Complex Learning for Distributed Processes
• Network Science, General Systems, Natural Economics & Growth
• Microclimates
• Publication "an unhidden pattern of events" & other writings
• Other people & Influences

                                Current work

• A paper on using a simplified Total Environmental Analysis method (TEA) for business System Energy Analysis (SEA), and standardize whole system analysis method for  EROI , for ASME-ES 2010 Pheonix - no draft to post yet.
• Writing and talks on why efficiency stimulates the economy to accelerate resource depletion rather than restrain it as most assume

The Art of Observation

12/28/08 1/24/09 1/27 1/20/10 There are two things required for learning how things in nature work on their own.   One is observing them without thinking, so your mind records some marks of the original behavior in a highly faithful way.  The second is exploratory.   Exploration is a matter of finding threads of connection and following them, and for natural systems, then letting the connections "grow on you" giving you "new ways of thinking" to check out.    What you're looking for is ways nature thinks differently from the way you do, paradoxically, so you can "be of two minds" about them.    It's becomes a way of connecting the dots that raises useful questions you never thought of before prompting further observation. 

That, in a nut shell, is what "science" is, with one key difference.   This is about discovering how individual systems discover their own rules rather that all compelled to follow preexisting universal rules.   One way to tell if it's working is whether you find paths of discovery that lead you on, little "yellow brick roads" in nature, taking you beyond your prior imagining.   That also helps you tell if you're just making things up or really discovering the nature of what you are looking at.   That's an endless hazard because of the human tendency to interpret consciousness as reality, instead of our own personalized cultural image.    Observation is pure research.    Then, you hope your way of asking better questions gives you a way to talk to others who have done the same thing, in their own different way, so you can constructively trade notes.  

Figure:  The diagram is of 1) how seeing a tree leaves a direct imprint on the retina of an observer's eye, 2) in who invents in their mind an image of a whole system through which energy and materials flow like a tree, along with an image of how it is connected in the cycles of nature.   Is the diagram to be found anywhere in nature?    No, of course not.   It's imaginary..   Is it may also be useful for helping the observer ask better questions about the real tree and it's environment, that others may understand as well.   Possibly...  --

Why people seem to know so very little about how the intricately organized things of nature take care of themselves gives the appearance that humans have not learned much from our time watching to see how things around us work.   Our normal rule for explanations is self-consistency, that every piece of information is determined by some other piece of information, and nothing in it has any independent behavior.  The better question would be, if some things in the world seem controlled like that, why isn't everything?   Asked another way, it might be, why do people almost never ask that question?    That there do indeed seem to be at least some things that take care of themselves, but we hardly ever ask how, seems to be a possible reason why we have such mixed success in taking care of ourselves...   It comes down to our habit of treating the *things* we see as the *information* we have about them.   Things may actually talk back, and information never will.   Seeing them as information we then interpret the things of the natural world in terms of our explanations.  The inadequacy of that is not only how explanations are never going to talk back, and the things being explained very well could.   All the connections in an explanation are also things we added ourselves, not things that came from what we're explaining.    What we use to connect the pieces of information to make explanations stick together are the cultural and emotional values we attach to the information.   In our minds we don't see physical things as connected by the physical systems they are composed of, but by the value laden constructs we attach to the information we have in our minds.   We tend to equate the real world with a kind of "dream world", our own artificial representation of it.   How we see things as being organized is as we organize our own thoughts and values.  We don't see them as organized by the natural processes that produced what we see.   What a true observer needs to overcome is this naturally artificial naive viewpoint, that the things of the world are the images we have of them.  It's often not easy, but there are lots of little flaws in the 'magic' of how we disguise the world as information you can learn to trust, leaving openings to the real world where you discover connections rather than fill in explanations.    

Observing is a process of letting the intricate beauties and designs of nature seep into one's awareness without imposing your own cultural values or explanations on them, to remain free to discovering their own connections.  When later attaching ones own values to them, then it is to something of substance rather than to nothing of substance.   Otherwise observation tends to be just a fascination with your own values.  Often where you make your first discoveries of nature's connections is noticing how things act as a "whole".  It's the best indication of the existence and design of uncontrolled systems, that they have complex scattered connections that act as one.   The easiest place to see it is in any organism, or culture, or burst of chemical energy, locating the system by how its set of scattered parts erupts in growth as one.   What you soon find is that what makes them whole, and gives them their ability to act as one, is what I call "ESP" (equal stress principle).  Things that act as a whole tend to evenly distribute their own stresses internally.   Seeing this can be easy for some things, but quite hard particularly for things we only know from other people's explanations.   Explanations don't do well with uncontrolled parts.   It can be a lot easier with things that need no explanation or come naturally and are beyond explanation, that we know intimately and so can closely observe without bias.    Truthful observation is not a "one shot deal" but an accumulation of them.   It's like building compost in the soil of an organic garden.   It's a matter of letting one's own mind accumulate a rich compost of the unaltered features imported directly from the "value free" physical systems of nature, letting your mind become imprinted by them as the first step.  

A painter needs paint, and a good observer needs to let their 'paints' accumulate in nature's own colors.   Not taking that approach, but seeing things as the information about them we connect in our own subjective way, our observations then tend to represent the world as lifeless and formless.   Things become "just explanations", given meaning only by the values we attach to them.   We miss all the natural meanings they have that way.   What we then "see" is our own poor awareness of how other things work on their own.   Then in everything we see we find mainly reflections of ourselves and little of the natural world's own connections.   It's an 'inadequate' view of our extraordinary rich intertwined and living world with its many kinds and scales of organized and complex individual parts.   Whether it's the health and prosperity of a tree, of a storm the size of a planet, or of a personal friendship or community of relationships getting into trouble and painfully hard to understand, the beginning of becoming truly a part of it's future is truthful observation.

I have lots of accumulated notes on observation technique scattered all over these pages.  I've been learning how to express it better, which of course means nearly everything here is also a little "out of date" and in need of "fixing" a little.   So, poke around...and see what you'd use and what you'd fix.

The Emergence of Natural Learning Systems, 
Complex Learning of, by, and for Distributed Processes

...Using physics tools a naturalist, for studying individual systems, their internal networks, life histories and their current and future learning processes.  05? 07/04/06 5/26/07 2/2/08 3/3/08 

1/29/09 11/28 Note: My first successful expression of this idea was an old unpublished early paper called "An Unhidden Pattern of Events", also described by Stan Salthe as the "canonical development trajectory" in thermodynamic and informational change, in his 2005 Energy and Semiotics.    The common pattern is an outline, or a 'crib sheet' if you will, on the "Chapters - In the whole story of individual lives and events" that individual evolutions and events themselves fill out with all their details.    Below is one introduction to my approach to expanding the scientific method to make many new kinds of scientific discoveries possible, more deeply grounding our understanding in the realities around us and with in us.   So much has gone on this year.   The following two short discussions are still useful, but "in a nut shell" might work too.

11/08/08 1/6/09  The general subjects of dissipative systems and complexity is are not really new, and really vast.   What's new here is the recognition that individual systems that begin and end do not need to be approximated by deterministic models in order to explore their changing local organization and developmental behaviors.   Determinism is a restrictive assumption of the physical sciences, based apparently on the guess that because some things can be determined from other things, therefore nothing has independent learning or behavior.   This is about learning how to study systems with clearly independent learning and behavior as a naturalist would, but using the tools of physics to identify the learning processes of the complex systems they contain and are the environments they interact with.

The starting point is that the conservation laws seem to imply that processes need to have multiple scales of developmental organization for energy flows to begin or end.    That conclusion comes from the old problem that when theory implies infinite field density, rates of energy flow or accelerations, the real implication is of another scale of organization.  A theorem expands the conservation laws into a general law of continuity and divergence that identifies natural necessities and limits of developmental processes, and opens a new way to explore causation.

To apply the continuity & divergence principle to complex systems research one uses the principle backwards from the normal procedures of physics.   It becomes a diagnostic tool for exploratory learning, that helps locate and identify the 'little bangs' and 'big booms' of locally emergent developmental processes.  Development in a process, say an ionization cascade in a spark or other growth phenomenon is called 'learning' because it is not guided by rules or a map, but takes place by local exploratory interaction with an environment.  That successes in that tend to be exposed by how they multiply provides a guide to where successful strategies within the system are developing.    It leads to a diagnostic approach to physical systems and change rather than a representational approach.   Work on the method was begun in the late 1970's and now is collected here, with methods and applications discussed in "a physics of happening" section.

From an information theory view, a diagnostic approach to physics treats the physical system as a unique individual "in-physico" model of itself...   The empirical signs of organizational change point to the physical phenomena within and around it, which are together considered to be the full complete and true representation of the system, in the physical thing itself.   Then one explores it's features and shapes to inform one's questions about it.   A 'theory' that may develop for it is considered to fit the physical thing's shapes like 'a glove' fits (or does not fit) to 'a hand'.    It's an approach of trying to understand individual things that nature has already built, by developing better questions about the process by which they developed.  It then leads to questions about what new conditions it will confront and need to respond to as it develops further.  The conserved property of derivative continuity allows one to do that by connecting inflection points in its learning curves with the internal network of its system of relationships, their learning processes, and the environment they are responding to.  

Typically there is a switch in the kind of development between a starting period of discovering expanding opportunity for self-referencing change in relation to the conditions the emerging system is coming from, without limits, to responding to and integrating with the limits of a larger environment it is emerging into.   The system development alters its original conditions of development and other independent things in  the environment often independently respond.

see also:

Henshaw 2008 Life’s hidden resources for learning in Cosmos & History special 10/08 issue on "What is Life"

Henshaw 1999-1 Features of derivative continuity in shape International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), special issue on invariants in pattern recognition, V13 No 8 1999 1181-1199 - mathematical methods for identifying and reconstructing continuity in natural flows

 "How can you see there's a process when your information about it is 'between the dots' ?"  

It's in the continuity of the dots.   Unfortunately, partly because of the many years of representing learning systems as following other kinds of abstract deterministic rules, there are a lot of 'tricks' of reasoning to unlearn.  One of the key ones is about reading beyond one's data.  The rule of the physical sciences has been that science must only consider the information it has as representing reality.   Physical systems, though, still exist in-between the times when you have information about them.   Here the gaps in your data are treated as questions, not exclusions, and a continuity of change is what your probing of the environment is seeking to uncover.  It's proof by discovery, not prediction.   That's very different.

3/3/08   Every 4 year old child knows that frogs jump because you poke them.  It would be nice if the philosophy of science did not still rely on that idea of causal determinism.   The idea that careful description of how actions of one kind produce effects of another is sufficient 'natural cause' for how we determine our own effects is perfectly sound.   That we say our models of deterministic prediction are also invisibly 'embedded' in the universe as the direct causes of nature is not.   The truth of course, is it's the frog that jumps, not your finger.    Looking at the time lags between stimuli and response, you can actually prove that the jumping of a frog is a local complex system learning process.   

A natural systems approach has to do with watching very closely as the 'frog jumps' to observe  how that learning process develops, and identify the emerging organizational networks that are instrumental in the frog's behavior.  It's not about designing an 'artificial frog' as normal control oriented science would be.  It's about discovering how to read the internal processes of the real frog.    There are a number of important discoveries about the true sources of eventfulness and organization in nature to be made, including how a lot of it is 'hidden in sight', disguised by our own unthinking categories.    I have a collection of basic principles:

Lists of Key Principles for understanding Natural Systems
Common Sense - Basic Theory - Systems Thinking - Research Methods  12/07

My main collection of analytical work on studying the continuity of change to raise key questions about the evolving systems of change is  a Physics of Happening.   I built the collection of studies in the late 80's and in the 90's, and have been trying to find the right words to explain it ever since.   To me, looking at historical records for when, where and how developmental processes changed direction is an obvious short-cut for finding the physical systems involved.   I closely observe time traces to see what's happening, focusing particularly on where events begin and end.  Where continuities begin and end the growth & decay of the internal networks of relationships that do it is very exposed.     Physics has looked at nature and asked what universal rules are being followed.   This approach looks to see what local rules are being developed.    Certainly it may look a little strange to study individual things rather than large classes of similar ones, but it's a key to understanding the physical world.   This intro has been rewritten many of times, the following are some short topics that didn't get erased....

Notable achievements?  There's a list of what I consider important results, but the most valuable for our steering the earth are various methods of measuring whole system strain and impacts.   In  well connected economies money does actually quantitatively measure physical energy use for example.  Money is a 'marker', yes, of potential energy, because spending an average dollar consumes an average amount of the total energy in global competitive markets with energy price liquidity.   This has a gigantic implication for economics in that most of our long range economic planning assumes the opposite, failing to count the 'fat tail' of the impact distribution of spending.   Using the $shadow principle to compare the measurable and unmeasurable portions of the impacts of commerce shows a typical undercount of a factor of 10.  

The property of infinitely smooth progression in mathematics is called 'derivative continuity'. It is one of the most fundamental and useful properties of mathematical functions.   Physical systems often display a similar but less well defined property, call it 'flow', or 'natural continuity'.   It characterizes the physical processes in which change takes a process of change, and so is 'conserved' in the same way energy can not be created or destroyed, only transferred by a process.   It's the main property of nature that formulas attempt to emulate, and the main reason equations are useful.   Energy is among the few properties of nature that is universal and conserved.    Most properties of systems of organization are not, except... the continuity of their changing.   That's very useful.    The natural continuity of flows is more complex than equations, continually changing as the underlying complex systems continually change.  For example one section of a curve might have all derivatives positive and a following section of the curve having all derivatives negative.   That suggests looking for underlying systems and how they switch from growth to decay. 

The intent is not aimed at writing a formula. You might use a formula as a way to see how the natural system diverges from it, though.  The intent is to understand how the instrumental systems develop and interact.    Reading shifts in the continuity in natural flows is a big help.   It's an approach that works with any field of science, astrophysics or political science, ecology or economics.   Each would use it to study the continuity of change of the properties they are interested in for the systems they are interested in.   Making it possible to have a common empirical reference to the qualitative subjects of interest  greatly helps in 'getting the problem right', whatever analytical method you then use.    One promising method is to us network science , starting with mapping networks of internal sets of  working parts of whole complex natural systems, and then reading their learning curves for their whole system environmental experience.. 

My sample studies  use various mathematical tools in a diagnostic fashion, to expose otherwise hidden details of  physical system flows and the implied system developments they reflect.   One of these is called "derivative reconstruction" (DR) that uses the mathematical definition of derivatives in reverse,  to "reconnect the dots" and sensitively reconstruct the probable dynamics of underlying system by filtering the spurious higher derivative fluctuation.  Another constructs a "dynamic mean" (DM) by stripping fluctuations and reconstructing the simplest curve shape representing their norm.  They produce differentiable natural functions by interpolation.   It doesn't always, but often exposes otherwise invisible developmental changes and forces excellent new questions.  To assume that a series of dots represents a single continuous process is tricky, of course, and there are some statistical tests like the step variance test (SV) to rule out random walk and a noise suppression sensitivity test (NSS) to gage the scale of non-random fluctuation.   Another of the methods used is called "curvature scale space" (CSS) which originated in the field of computer vision.   It uses repeated smoothing of shapes to distinguish and define those features of shape which are the most robust (slowest to disappear with suppression).  Basically you look for where processes begin and end and try to figure out what is beginning and ending.

There is no practical barrier to these new methods having wide and immediately useful application in numerous fields.   There is a conceptual barrier though.   It's not the Western cultural habit to think of time as a process.  We tend to think of it as a location, and so equations with time as a variable as describing a system that itself does not change over time.   The evidence is that all natural systems continually change over time, and that the main events causing change in systems are 'tipping points' at which systems 'out of balance' end up disrupting themselves in some fashion.  Ordinary thinking hides that from us.

Network Science     
....what happens when things connect!  05/24/07.. 09/09/07

Watch this space....   The NetSci conference in NY in May 07.  The ability to convey highly complex system information and understand the evolution of systems from it is advancing to a useful tool very rapidly.   Great Displays from Manuel Lima's Visual Complexity.   My most recent technical notes on linking Net Sci and Natural Systems theory with Complex Systems engineering.. PICS.htm

• One of the things that causes the 'power law' distribution of organization in emergent systems appears to be the elaboration and refinement that occurs in how they grow and develop.  

• One of the ways of understanding how networks are embedded into the complex systems which produce them is hat all the nodes are actually 'hives' of activity in the larger system when looked at at a different scale.  

• To understand what it means that people are connected by 5 degrees of separation and web pages by 19 is helps to consider how close connection of this kind has a simultaneous reverse property of great isolation and independence.   What the difference between 5 and 19 means is that information is divided into many many more separate worlds, the flip side of the astonishment we all feel when finding out that all our very separate worlds are also quite closely connected.

The tools for displaying these structures and relationships are so good, and the complex system decisions people need to make so pressing, that there clearly should be an office of complex information display in every branch of government.   You can't ask the question till you can see the problem.   Think of the difference if we could look at comprehendible maps of the real evolving complex relations between communities in Iraq or your own city!    It's clearly possible now.  Think of the difference if we could map ecologies in depth and display their connections in a visually compelling and analytically rigorous way.  It's clearly possible now.

General Systems Theory
....a grand event in systems thinking that didn't survive, 05?  07/04/06

General Systems Theory, was one of several great attempts to make a science of the study of natural systems.  The more popular but still unproven one today goes by the name 'Complexity'.   GST originated as a major interdisciplinary effort in the 1940's, Von Bertalanffy, Boulding, Ashby, Miller, Forrester and others, and seemed to loose direction and turn into other things in the late 1980's & 90's.  The language of general systems theory as it developed, is problematic as science and quite short on generally useful results.    Still, it is full of insights into the nature of the problem. 

The successor organization which retains little of the original form keeps a web site with a genealogy diagram of systems thinking (http://www.iigss.net/gPICT.pdf).  Basically, 'holism' became 'cybernetics' and with several layers of complexity became 'general systems theory'.   I've had recent long and productive correspondence with Don McNeil about the origins and 'death' of pure systems thinking, and what might be salvageable.  I thought it might be of some research interest sometime, and asked if I put it up on the web that I show it as copy righted. My two 1985 papers for SGSR and some other things are now online too.

All natural systems are an interplay between active and passive components, for example. There's the plant and the soil, the cell and the blood stream, the speaker and listener, the industry and the pools of resources from which it draws and to which it contributes. Nature is also structured as a unity of opposites, things and the mediums through which they communicate with each other, for one example. These and many other insights into nature are mystical in their power, but also overwhelming in their grandeur while failing the test of having practical use.  It left those who studied it relatively less to say than it first appeared they would have.