NETZWERKE VERNETZEN -
NETWORKING NETWORKS



NETZWERKEN - VERBINDEN VON IDEEN - ASSOZIATION - UNTERSCHEIDEN - VERGLEICHEN - METAPHER - NETZWERKE VERNETZEN - NETZE KNÜPFEN - GEWEBE WEBEN - TEXTIL

INTERACTION

Komplexität:

Selbstorganisation:

Ebenen des Seins:

Erkenntnistheorie:

The pattern of life, is a network pattern capable of self-organisation. Capra79


NETZWERKE VERNETZEN - NETWORKING NETWORKS

OUR UNIVERSE IS A NETWORK OF INTERACTIONS, A NETWORK OF PROCESSES. TO UNDERSTAND OUR WORLD WE NEED TO STUDY THE EVOLUTION, THE HISTORY, THE FUNCTIONING AND THE STRUCTURES OF THIS CENTRAL PHENOMENON:


INTERACTION

" The purpose of science is to find meaningful simplicity in the midst of disorderly complexity".
Herbert Simon

TO SIMPLIFY MEANINGFULLY WE MUST FIND THE MOST BASIC PROCESS OF THIS - OUR - WORLD. THE PROCESS THAT "MAKES" COMPLEXITY: INTERACTION

At critical points and phase transitions the properties of the parts of the system stop mattering. Instead it is the interactions and organisation that matter.Ward97

THE RESULTS, THE EFFECTS OF THIS PROCESS OF INTERACTION ARE: MATTER, ENERGY, MIND, INTELLIGENCE, LANGUAGE, CULTURE


MIND

Mind is a phenomenon on that occurs when human beings coexist in societies. Kennedy/Eberhardt3

In Mind and Nature, Bateson detailed what he considered to be criteria of mind, qualities that were necessary and sufficient for something to recall the mind:
1 A mind is an aggregate of interacting parts or components.
2 The interaction between parts of mind is triggered by difference. For instance, perception depends on changes in stimuli.
3 Mental process requires collateral energy.
4 Mental process requires circular (or more complex) chains of determination. The idea of reciprocal causation, or feedback, is very important one and is fundamental to mental processes.
5 In mental process, the effects of difference are to be regarded as transforms (i.e. coded versions) of the difference which preceded them. Effects are not the same as their causes; the map is not the same as the territory.

EVERYTHING - EVERY THING - IN OUR WORLD IS AN AGGREGATE OF INTERACTING COMPONENTS. ALL "THINGS" ARE MENTAL. THEY ARE THE RESULT OF EMERGING LEVELS OF BEING.

EXISTENCE - PERSISTENCE
LEVELS OF BEING

STEPS 2: THE LEVELS OF BEING


Grand 12:
a hierarchy of "persistent phenomena"
Grand65:
adaptive behaviour can emerge from essentially the same kinds of regulatory mechanism already employed by autocatalytic networks. So this rudimentary form of intelligence can be seen as the next rung of the ladder of mechanisms for persistence - another level of being. Any phenomenon that can modify its own behaviour as a consequence of the environmental stresses imposed by other phenomena has a greater chance of persisting than one that just stands there and takes it on the chin, and this is what we mean by adaptation. This ability to react to events after they have happened can get an organism a long way, but not nearly as far as pre-adaptation can. In other words, reacting to an existing opportunity or problem is not as effective as predicting it and changing one's behaviour appropriately before the opportunity has time to go away or before the damage is inflicted. Intelligence is perhaps a term that should be reserved for systems that can predict the future.

Intelligence is perhaps a term that should be reserved for systems that can predict the future.

EMERGENCE

Ohne Sprache keine Zeit - Wie der sprechende Mensch mit der Zeit umgehen lernte

Von Urs Boeschenstein
Die Zukunft wählen...
Mehrzellige Lebewesen haben im Verlaufe einer langen Entwicklungsgeschichte ein Organ entwickelt, das ihnen gestattet, die Zukunft zu wählen - das Gehirn. Sie können entscheiden, sie können wollen, sie können während ihres Lebens Erfahrungen speichern, sie können lernen. Bei einfacheren Lebewesen sind die Entscheidungen noch fest programmiert. Das Wollen und das Entscheiden lernten Säugetiere und Vögel. Sie können Erfahrungen sammeln und ihre gelernten Erfahrungen für überlebensfördende Entscheidungen einsetzen.


ORGANISATION

FORM and STRUCTURE: ....the study of substance (structure) and the study of form (pattern).  In the study of structure we measure and weigh things.  Patterns, however, cannot be measured or weighed; they must be mapped.  To understand the pattern, we must map the configuration of relationships.  In other words, structure involves quantities, while pattern involves qualities. Capra79

EMERGING LEVELS OF BEING

COMPLEXITY:

COMPLEXITY : " The purpose of science is to find meaningful simplicity in the midst of disorderly complexity". Herbert Simon - complexity - complexity theory - laws of form - organisation - small worlds - Plato - Kant - architecture of networks - patterns - intelligence - SMALL WORLDS - SYNCHRONY - general organising tendency in nature - geometrical character of the social world - the strength of weak ties - mathematical networks - order and randomness in one network - small world networks -synchronisation puzzle - global organisation - computation - signals, counter-signals and counter-countersignals - computational design, small world architecture - small world geometry. COMPUTATION : Steve Grand - persistent phenomena - matter, life, mind and society are simply different levels or aspects of the same thing - organised machines, unorganised machines (neural networks) and self-organising machines (life) - mind - mental processes - digital computer - serial, procedural, top-down computer: a tool to create new machines that are parallel, relational and bottom-up

PATTERN:..relationships characteristic of a particular system -
MATHEMATICS OF COMPLEXITY -
SELF-ORGANISATION -
CYBERNETICS

NONLINEARITY: ...the relationships in a network pattern are nonlinear relationships -
FEEDBACK-


The Importance of Pattern
Living Systems
The recent advances in our understanding of living systems are based on twodevelopments that originated in the late 1970s. 
One was the discovery of the new mathematics of complexity
The other was the emergence of a powerful novel concept, that of self-organisation.
 Pattern: To understand the phenomenon of self-organisation, we first need to understand the importance of pattern.  The idea of pattern of organisation - the configuration of relationships characteristic of a particular system - become the explicit focus of systems thinking in cybernetics and has been a crucial concept ever since.  From the systems point of view, the understanding of life begins with the understanding of pattern.
 
 Networks
The Patterns of Life
Having appreciated the importance of pattern for the understanding of life, we can now ask: Is there a common pattern of organisation that can be identified in all living systems?  We shall see that this is indeed the case.  This pattern of organisation, common to all living systems, will be discussed below.  Its most important property is that it is a network pattern.  Whenever we encounter living systems - organisms, parts of organisms, or communities of organisms - we can observe that their components are arranged in network fashion.  Whenever we look at life, we look at networks.

Cybernetics tried to understand the brain as a neural network and developed special mathematical techniques to analyse its pattern.  The structure of the human brain is enormously complex.  It contains about 10 billion nervous cells (neurons), which are interlinked in a vast network through 1000 billion junctions (synapses).  The whole brain can be divided into subsections or subnetworks, which communicate each other in network fashion.  All this results in intricate patterns of interwined webs, networks nesting within larger networks.
Nonlinearity: The first and most obvious property of any network is its nonlinearity - it goes in all directions.  Thus the relationships in a network pattern are nonlinear relationships.  In particular, an influence, or message, may travel along a cyclical path, which may become the feedback loop.  The concept of feedback is intimately connected with a network pattern. Because networks of communication may generate feedback loops, they may acquire the ability to regulate themselves.  For example, the community that maintains an active network of communications will learn from its mistakes, because the consequences of a mistake will spread through the network and returned to the source along feedback loops.  Thus the community can correct its mistakes, regulate itself, and organise itself. Indeed, self organisation has emerged as perhaps the central concept in the systems view of life, and like the concept of feedback and self-regulation it is closely linked to networks. The pattern of life, is a network pattern capable of self organisation.


 The pattern of life, is a network pattern capable of self- organisation. Capra79


QUALITY - QUANTITY:....the study of substance (structure) and the study of form (pattern).  In the study of structure we measure and weigh things.  Patterns, however, cannot be measured or weighed; they must be mapped.  To understand the pattern, we must map the configuration of relationships.  In other words, structure involves quantities, while pattern involves qualities.

NON-LINEARITY: ....The first and most obvious property of any network is its nonlinearity - it goes in all directions.  Thus the relationships in a network pattern are nonlinear relationships.  In particular, an influence, or message, may travel along a cyclical path, which may become the feedback loop.  The concept of feedback is intimately connected with a network pattern.



FEEDBACK: ...In particular, an influence, or message, may travel along a cyclical path, which may become the feedback loop.  The concept of feedback is intimately connected with a network pattern.


CHAOS

Mark Ward
BEYOND CHAOS
The Underlying Theory Behind Life, the Universe, and Everything
Thomas Dunne Books 2001
pg 97
Keywords: Cellular Automata - Universality - at critical points and phase transitions the properties of the parts of the system stop mattering. Instead it is the interactions and organisation that matter -

John Horton Conway - Game of Life - one-dimensional cellular automata (1-D CA) - Stephan Wolfram - Chris Langton - Alife - creating synthetic organisms - cellular automata as toy universes into which they unleash a variety of software creatures to relive and retrace evolution - Fractal patterns - phase transition - critical point - Universality - "edge of chaos" - at the critical junctures complex structures emerge and persist. Persistence, staying alive, demands the ability to process information about your surroundings and use it - dynamics of information - order and structure - organisational principle of all living things

UNIVERSALITY: Universality is built into living organisms as their, and our, defining dynamic. At critical points and phase transitions the properties of the parts of the system stop mattering. Instead it is the interactions and organisation that matter. Since the 1970s scientists have been using simplified models of the world called cellular automata to tackle a huge variety of research problems.


Mark Buchanan
Ubiquity
The Science of History Why the World is Simpler than we Think
Weidenfels&Nicolson 2000

pg 9

Keywords: the organisation of networks (system) - a small shock to trigger a response out of all proportion to itself. It is as if these systems had been poised on some knife‑edge of instability, merely waiting to be set off - instability – disaster – upheaval – The global ecosystem is occasionally visited by abrupt episodes of collapse - a profound similarity not between moving objects, but between the upheavals that affect our lives, and the ways in which the complicated networks in which they occur - economies, political systems, ecosystems and so on - are naturally organised - these events, and the workings of the systems in which they occur, may reflect the tenor of just a few simple and ubiquitous underlying processes.

Sand-pile game - Per Bak, Chao Tang, Kurt Weisenfeld - what is the typical size of an avalanche? How big, that is, should you expect the very next avalanche to be? The result? Well …there was no result, for there simply was no 'typical' avalanche - The hypersensitive state to which the computer sand pile organises itself is known as the critical state -

critical state - Could the special organisation of the critical state explain why the world at large seems so susceptible to unpredictable upheavals? - the peculiar and exceptionally unstable organisation of the critical state does indeed seem to be ubiquitous in our world – At the heart of our story, then, lies the discovery that networks of things of all kinds ‑ atoms, molecules, species, people, and even ideas ‑ have a marked tendency to organise themselves along similar lines. On the basis of this insight, scientists are finally beginning to fathom what lies behind tumultuous events of all sorts, and to see patterns at work where they have never seen them before.

Catastrophe theory - catastrophe theory, despite its provocative name, has very little to say about the workings of anything like the earth's crust, an economy, or an ecosystem. In these things, where thousands or millions of elements interact, what is important is the overall collective organisation and behaviour. To understand things of this sort, one needs a theory that applies generally to networks of interacting things.

Chaos theory - chaos by itself cannot explain why a butterfly can cause a thunderstorm. Chaos may indeed explain why a tiny cause can quickly make the future different in its details (the positions of many molecules) from what it might have been. But to explain why tiny causes can ultimately lead to great upheavals, we need something else. We may say that although chaos can explain simple unpredictability, it cannot explain upheavability.

complexity: networks of interacting things: For centuries, physicists have sought the fundamental laws of the universe in timeless and unchanging equations – equilibrium - the air in the atmosphere is very much out of equilibrium, since it is continually being stirred and agitated and energised by the influx of light from the sun, and here we have a clue to the origin of upheavals: it lies in the distinction between what happens in equilibrium, and what happens away from it. If things in equilibrium are fairly simple, things out of equilibrium can be decidedly complex

non­-equilibrium physics, or, to use the currently fashionable language, the physics of complex systems - the relationship between the critical state and complexity is really quite simple: the ubiquity of the critical state may well be considered the first really solid discovery of complexity theory

history: In coming to consider complex systems, physicists seem to have gained a new appreciation of a simple fact: in the immediate world around us, history is important - out of equilibrium, history does matter. One can only make sense of the infinitely detailed shape of a snowflake by following the history of its growth by slow freezing from the thin air. These are all problems in non‑equilibrium physics, the physics of complex systems, or, to coin a new term, historical physics. If the laws of physics are ultimately simple, why is the world so complex? Why don't ecosystems and economies reveal the same simplicity as Newton's laws? The answer, in a word, is history.

dynamics of history - For things out of equilibrium, one cannot proceed by solving timeless equations, and so physicists have turned to another approach ‑ replacing equations with games -

explore the basics of crystal growth – frozen accidents - If the laws of physics did not allow frozen accidents, the world would be in equilibrium, and everything would be like the gas in a balloon, resting forever in the same uniform and unchanging condition. But the laws of physics do allow events to have consequences that can become locked in place, and so alter the playing field on which the future unfolds. The laws of physics allow history to exist. The discovery of the ubiquity of the critical state, then, is not only the first solid discovery of complexity theory, but also the first deep discovery concerning the typical character of things historic.


INFORMATION: Persistence, staying alive, demands the ability to process information about your surroundings and use it - dynamics of information (Ward97)


CELLULAR AUTOMATA: cellular automata


Communication


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