Emergence
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The whole is more than the sum of the parts

Summary
This page discusses the mechanisms and effects of emergence underpinning any complex adaptive system (
This page introduces the complex adaptive system (CAS) theory frame.  The theory provides an organizing framework that is used by 'life.'  It can be used to evaluate and rank models that claim to describe our perceived reality.  It catalogs the laws and strategies which underpin the operation of systems that are based on the interaction of emergent agents.  It highlights the constraints that shape CAS and so predicts their form.  A proposal that does not conform is wrong. 

John Holland's framework for representing complexity is outlined.  Links to other key aspects of CAS theory discussed at the site are presented. 
CAS
).  Physical forces and constraints follow the rules of complexity.  They generate phenomena and support the indirect emergence of epiphenomena.  Flows of epiphenomena interact in events which support the emergence of equilibrium and autonomous entities.  Autonomous entities enable evolution to operate broadening the adjacent possible.  Key research is reviewed. 
Introduction
John Holland eloquently explains how new phenomena can emerge from certain types of systems. 

"A
This page discusses the physical foundations of complex adaptive systems (CAS).  A small set of rules is obeyed.  New [epi]phenomena then emerge.  Examples are discussed. 
small number of rules
or laws can generate systems of surprising complexity, M. Mitchell Waldrop describes a vision of complexity via:
  • Rich interactions that allow a system to undergo spontaneous self-organization
  • Systems that are adaptive
  • More predictability than chaotic systems by bringing order and chaos into
  • Balance at the edge of chaos
. "

He argues that the complexity contains recognizable features, which recur.  They are also dynamic.  He goes on "that
Plans are interpreted and implemented by agents.  This page discusses the properties of agents in a complex adaptive system (CAS). 
It then presents examples of agents in different CAS.  The examples include a computer program where modeling and actions are performed by software agents.  These software agents are aggregates. 
The participation of agents in flows is introduced and some implications of this are outlined. 
agents
create the emergent behavior of rule based systems. " ... "The simple laws of the agents generate an emergent behavior far beyond their individual capabilities.  It is noteworthy that this emergent behavior occurs without direction by a central executive.  "

What makes the agents emerge?  A little self-assembly is required.  A structure which can
Plans emerge in complex adaptive systems (CAS) to provide the instructions that agents use to perform actions.  The component architecture and structure of the plans is reviewed. 
support a plan
and self-assemble into an
This page reviews the catalytic impact of infrastructure on the expression of phenotypic effects by an agent.  The infrastructure reduces the cost the agent must pay to perform the selected action.  The catalysis is enhanced by positive returns. 
infrastructure amplifier
can do this.  Hence Ribose Nucleic Acids (RNA (RNA), a polymer composed of a chain of ribose sugars.  It does not naturally form into a paired double helix and so is far less stable than DNA.  Chains of DNA are converted by transcription into equivalently sequenced messenger m-RNA.  RNA also provides the associations that encode the genetic code.  Transfer t-RNAs have a site that maps to the codon and match the associated amino-acid.  Stuart Kauffman argues that RNA polymers may be the precursor to our current DNA based genome and protein based enzymes.  In the adaptive web framework's (AWF) Smiley we use a similar paradigm with no proteins.  ), which can self-assemble, support schematic plans as in m-RNA (RNA), a polymer composed of a chain of ribose sugars.  It does not naturally form into a paired double helix and so is far less stable than DNA.  Chains of DNA are converted by transcription into equivalently sequenced messenger m-RNA.  RNA also provides the associations that encode the genetic code.  Transfer t-RNAs have a site that maps to the codon and match the associated amino-acid.  Stuart Kauffman argues that RNA polymers may be the precursor to our current DNA based genome and protein based enzymes.  In the adaptive web framework's (AWF) Smiley we use a similar paradigm with no proteins.   and catalytic, an infrastructure amplifier. 
actions such as transfer (t-RNA (RNA), a polymer composed of a chain of ribose sugars.  It does not naturally form into a paired double helix and so is far less stable than DNA.  Chains of DNA are converted by transcription into equivalently sequenced messenger m-RNA.  RNA also provides the associations that encode the genetic code.  Transfer t-RNAs have a site that maps to the codon and match the associated amino-acid.  Stuart Kauffman argues that RNA polymers may be the precursor to our current DNA based genome and protein based enzymes.  In the adaptive web framework's (AWF) Smiley we use a similar paradigm with no proteins.  ) provides a high profile
The agents in complex adaptive systems (CAS) must model their environment to respond effectively to it.  Evolution's schematic operators and Samuel modeling together support the indirect recording of past successes and their strategic use by the current agent to learn how to succeed in the proximate environment. 
model
.  With
Carlo Rovelli resolves the paradox of time. 
Rovelli initially explains that low level physics does not include time:
  • A present that is common throughout the universe does not exist
  • Events are only partially ordered.  The present is localized
  • The difference between past and future is not foundational.  It occurs because of state that through our blurring appears particular to us
  • Time passes at different speeds dependent on where we are and how fast we travel
  • Time's rhythms are due to the gravitational field
  • Our quantized physics shows neither space nor time, just processes transforming physical variables. 
  • Fundamentally there is no time.  The basic equations evolve together with events, not things 
Then he explains how in a physical world without time its perception can emerge:
  • Our familiar time emerges
    • Our interaction with the world is partial, blurred, quantum indeterminate
    • The ignorance determines the existence of thermal time and entropy that quantifies our uncertainty
    • Directionality of time is real but perspectival.  The entropy of the world in relation to us increases with our thermal time.  The growth of entropy distinguishes past from future: resulting in traces and memories
    • Each human is a unified being because: we reflect the world, we formed an image of a unified entity by interacting with our kind, and because of the perspective of memory
    • The variable time: is one of the variables of the gravitational field.  With our scale we don't register quantum fluctuations, making space-time appear determined.  At our speed we don't perceive differences in time of different clocks, so we experience a single time: universal, uniform, ordered; which is helpful to our decisions

time
, emergent systems are likely to generate specialized agents better suited to particular tasks than the general purpose initiator.  These new agents will replace and obscure the earlier structures essential role. 

Agents are not required for emergence however.  Stuart Kauffman explains that very basic binary networks demonstrate emergent properties.  In particular the binary state of the elements can be transformed by the network into small numbers of emergent attractor regions which are stable unless the network is perturbed.  Terrence Deacon
Terrence Deacon explores how constraints on dynamic flows can induce emergent phenomena which can do real work.  He shows how these phenomena are sustained.  The mechanism enables the development of Darwinian competition. 
describes a framework of dynamic processes
that bridges from thermodynamic chemistry to ends-focused functional systems. 

Physical systems, such as rivers, can be observed to demonstrate the emergence of persistent state.  The state can remain as long as the resources that support the flows exist.  But, the physical forces acting on the system typically perturb the situation, for example disrupting a
Barriers are particular types of constraints on flows.  They can enforce separation of a network of agents allowing evolution to build diversity.  Examples of different types of barriers: physical barriers, chemical molecules can form membranes, probability based, cell membranes can include controllable channels, eukaryotes leverage membranes, symbiosis, human emotions, chess, business; and their effects are described. 
barrier
, allowing the resources to disperse. 

Francis Crick assumes that while the whole may not be the simple sum of the parts, its behavior can, at least in principle, be understood from the nature and behavior of its parts plus the knowledge of how all these parts interact.  Murray Gell-Mann notes that the history are a class of fine-grained histories of the universe, in quantum mechanics, which all agree on a particular account of what is followed (events of large inertial mass) but vary over all possible events of what is not followed, which are summed over. 
executed by an entity are, according to Abbott, a class including people, families, corporations, hurricanes.  They implement abstract designs and are demarcatable by their reduced entropy relative to their components.  Rovelli notes entities are a collection of relations and events, but memory and our continuous process of anticipation, organizes the series of quantized interactions we perceive into an illusion of permanent objects flowing from past to future.  Abbott identifies two types of entity:
  1. At equilibrium entities,
  2. Autonomous entities, which can control how they are affected by outside forces;
likely includes
This page discusses the impact of random events which once they occur encourage a particular direction forward for a complex adaptive system (CAS). 
frozen accidents
which
Russ Abbott explores the impact on science of epiphenomena and the emergence of agents. 
block reductionist recreation
of the entity purely from functionally lower level laws. 
Epiphenomena are emergent
Abbott explains that a
This page discusses the physical foundations of complex adaptive systems (CAS).  A small set of rules is obeyed.  New [epi]phenomena then emerge.  Examples are discussed. 
phenomena
is emergent if it is conceptualized independently of the platform is agent generated infrastructure that supports emergence of an entity through: leverage of an abundant energy source, reusable resources; attracting a phenotypically aligned network of agents. 
that implements it.  I.E. it is used and modeled without a direct dependence on the underlying phenomena and physical mechanisms.  Abbott demonstrates how emergent epiphenomena can encapsulate conceptual rules which can be associated with predictive theories, and these will hold while the underlying physics is in a matching phase. 

Abbott identifies two classes of emergent entities:
Autonomous entities are entities which:
  • Are far from equilibrium
  • Consume and save low entropy
  • Can use accessible low entropy to maintain themselves
are implementations of epiphenomena's abstract designs, which can use
Flows of different kinds are essential to the operation of complex adaptive systems (CAS). 
Example flows are outlined.  Constraints on flows support the emergence of the systems.  Examples of constraints are discussed. 
control of flows of energy
to sustain themselves. 

Chemical structures, emergent epiphenomena, focusing
This page discusses the physical foundations of complex adaptive systems (CAS).  A small set of rules is obeyed.  New [epi]phenomena then emerge.  Examples are discussed. 
physical phenomena
, can provide a
Plans change in complex adaptive systems (CAS) due to the action of genetic operations such as mutation, splitting and recombination.  The nature of the operations is described. 
re-combinable
active matrix from which
Plans are interpreted and implemented by agents.  This page discusses the properties of agents in a complex adaptive system (CAS). 
It then presents examples of agents in different CAS.  The examples include a computer program where modeling and actions are performed by software agents.  These software agents are aggregates. 
The participation of agents in flows is introduced and some implications of this are outlined. 
agents
and
Plans emerge in complex adaptive systems (CAS) to provide the instructions that agents use to perform actions.  The component architecture and structure of the plans is reviewed. 
schematic plans
can be derived.  Similarly the adaptive web framework (AWF)'s
This page describes the Copycat Coderack. 
The details of the codelet architecture are described. 
The specialized use of the Coderack by the adaptive web framework's (AWF) Smiley is discussed. 
The codelet scheduling mechanism is discussed. 
A variety of Smiley extensions to the Coderack are reviewed. 
The Coderack infrastructure functions are included. 
Coderack
associates re-combinable
This page describes the Copycat Workspace. 
The specialized use of the Workspace by the adaptive web framework's (AWF) Smiley is discussed. 
How text and XML are imported into the Smiley Workspace is described. 
Telomeric aging of schematic structures is introduced. 
The internal data structure used to represent the state of each workspace object is included. 
The Workspace infrastructure functions are included. 
Workspace
objects is a collection of: happenings, occurrences and processes; including emergent entities, as required by relativity, explains Rovelli.  But natural selection has improved our fitness by representing this perception, in our minds, as an unchanging thing, as explained by Pinker.  Dehaene explains the object modeling and construction process within the unconscious and conscious brain.  Mathematicians view anything that can be defined and used in deductive reasoning and mathematical proofs as an object.  These mathematical objects can be values of variables, allowing them to be used in formulas.  
, and strings, with
This page describes the Smiley infrastructure and codelets that instantiate the epiphenomena defined in the Meta file and Slipnet. 
Infrastructure sensors are introduced. 
The role of phenomena in shaping the environment is discussed. 
The focusing of forces by phenomena in Smiley is discussed. 
The Meta file association of case keywords with phenomena is included. 
The codelets and supporting functions are included. 
epiphenomena
reflecting properties defined in the
This page describes the Copycat Slipnet. 
The goal of the Slipnet is reviewed. 
Smiley's specialized use of the Slipnet is introduced. 
The initial Slipnet network used by the 'Merge Streams' and 'Virtual Robot' agent-based applications is setup in initchemistry and is included. 
The Slipnet infrastructure and initialization functions are included. 
Slipnet
or its basic 'physical' constants. 

Complex systems emerge from the presence of feedback during the competition of a collection of simpler autonomous entities for scarce resources. 

If the competing 'entities' include an
Plans emerge in complex adaptive systems (CAS) to provide the instructions that agents use to perform actions.  The component architecture and structure of the plans is reviewed. 
action inducing plan
the feedback can include
Plans change in complex adaptive systems (CAS) due to the action of genetic operations such as mutation, splitting and recombination.  The nature of the operations is described. 
genetic operations
on the plans. 
This page introduces the complex adaptive system (CAS) theory frame.  The theory provides an organizing framework that is used by 'life.'  It can be used to evaluate and rank models that claim to describe our perceived reality.  It catalogs the laws and strategies which underpin the operation of systems that are based on the interaction of emergent agents.  It highlights the constraints that shape CAS and so predicts their form.  A proposal that does not conform is wrong. 

John Holland's framework for representing complexity is outlined.  Links to other key aspects of CAS theory discussed at the site are presented. 
Complex adaptive systems
(CAS)
Plans are interpreted and implemented by agents.  This page discusses the properties of agents in a complex adaptive system (CAS). 
It then presents examples of agents in different CAS.  The examples include a computer program where modeling and actions are performed by software agents.  These software agents are aggregates. 
The participation of agents in flows is introduced and some implications of this are outlined. 
agents
can emerge.  These genetically framed agents can support the emergence of additional predictive mental
The agents in complex adaptive systems (CAS) must model their environment to respond effectively to it.  Evolution's schematic operators and Samuel modeling together support the indirect recording of past successes and their strategic use by the current agent to learn how to succeed in the proximate environment. 
models
that improve the genes' chance of reproduction and survival:
Antonio Damasio argues that ancient & fundamental homeostatic processes, built into behaviors and updated by evolution have resulted in the emergence of  nervous systems and feelings.  These feelings, representing the state of the viscera, and represented with general systems supporting enteric operation, are later ubiquitously integrated into the 'images' built by the minds of higher animals including humans. 

Damasio highlights the separate development of the body frame in the building of minds. 

Damasio explains that this integration of feelings by minds supports the development of subjectivity and consciousness.  His chain of emergence suggests the 'order of things.'  He stresses the end-to-end integration of the organism which undermines dualism.  And he reviews Chalmers hard problem of consciousness. 

Damasio reviews the emergence of cultures and sees feelings, integrated with reason, as the judges of the cultural creative process, linking culture to homeostasis.  He sees cultures as supporting the development of tools to improve our lives.  But the results of the creative process have added stresses to our lives. 

Following our summary of his arguments RSS frames his arguments from the perspective of complex adaptive system (CAS) theory.  Each of the [super]organisms discussed is a CAS reflecting the theory of such systems:
  • Damasio's proposals about homeostasis routed signalling, aligns well with CAS theory. 
  • Damasio's ideas on cultural stresses are elaborated by CAS examples. 

feelings
,
Consciousness is no longer mysterious.  In this page we use complex adaptive system (CAS) theory to describe the high-level architecture of consciousness, linking sensory networks, low level feelings and genetically conserved and deployed neural structures into a high level scheduler.  Consciousness is evolution's solution to the complex problems of effective, emergent, multi-cellular perception based strategy.  Constrained by emergence and needing to avoid the epistemological problem of starting with a blank slate with every birth, evolution was limited in its options. 

We explain how survival value allows evolution to leverage available tools: sensors, agent relative position, models, perception & representation; to solve the problem of mobile agents responding effectively to their own state and proximate environment.  Evolution did this by providing a genetically constructed framework that can develop into a conscious CAS. 

And we discuss the implications with regard to artificial intelligence, sentient robots, augmented intelligence, and aspects of philosophy. 
consciousness
,
Carlo Rovelli resolves the paradox of time. 
Rovelli initially explains that low level physics does not include time:
  • A present that is common throughout the universe does not exist
  • Events are only partially ordered.  The present is localized
  • The difference between past and future is not foundational.  It occurs because of state that through our blurring appears particular to us
  • Time passes at different speeds dependent on where we are and how fast we travel
  • Time's rhythms are due to the gravitational field
  • Our quantized physics shows neither space nor time, just processes transforming physical variables. 
  • Fundamentally there is no time.  The basic equations evolve together with events, not things 
Then he explains how in a physical world without time its perception can emerge:
  • Our familiar time emerges
    • Our interaction with the world is partial, blurred, quantum indeterminate
    • The ignorance determines the existence of thermal time and entropy that quantifies our uncertainty
    • Directionality of time is real but perspectival.  The entropy of the world in relation to us increases with our thermal time.  The growth of entropy distinguishes past from future: resulting in traces and memories
    • Each human is a unified being because: we reflect the world, we formed an image of a unified entity by interacting with our kind, and because of the perspective of memory
    • The variable time: is one of the variables of the gravitational field.  With our scale we don't register quantum fluctuations, making space-time appear determined.  At our speed we don't perceive differences in time of different clocks, so we experience a single time: universal, uniform, ordered; which is helpful to our decisions

time
, vision,
E O. Wilson argues that campfire gatherings on the savanna supported the emergence of human creativity.  This resulted in man building cultures and later exploring them, and their creator, through the humanities.  Wilson identifies the transformative events, but he notes many of these are presently ignored by the humanities.  So he calls for a change of approach. 

He:
  • Explores creativity: how it emerged from the benefits of becoming an omnivore hunter gatherer, enabled by language & its catalysis of invention, through stories told in the evening around the campfire. He notes the power of fine art, but suggests music provides the most revealing signature of aesthetic surprise. 
  • Looks at the current limitations of the humanities, as they have suffered through years of neglect.  
  • Reviews the evolutionary processes of heredity and culture:
    • Ultimate causes viewed through art, & music
    • The bedrock of:
      • Ape senses and emotions,
      • Creative arts, language, dance, song typically studied by humanities, & 
      • Exponential change in science and technology.  
    • How the breakthrough from our primate past occurred, powered by eating meat, supporting: a bigger brain, expanded memory & language. 
    • Accelerating changes now driven by genetic cultural coevolution.  
    • The impact on human nature.  
  • Considers our emotional attachment to the natural world: hunting, gardens; we are destroying. 
  • Reviews our love of metaphor, archetypes, exploration, irony, and considers the potential for a third enlightenment, supported by cooperative action of humanities and science

Following our summary of his arguments RSS frames these from the perspective of complex adaptive system (CAS) theory:
  • The humanities are seen to be a functionalist framework for representing the cultural CAS while 
  • Wilson's desire to integrate the humanities and science gains support from viewing the endeavor as a network of layered CAS. 

story-telling
& culture is how we do and think about things, transmitted by non-genetic means as defined by Frans de Waal.  CAS theory views cultures as operating via memetic schemata evolved by memetic operators to support a cultural superorganism.  Evolutionary psychology asserts that human culture reflects adaptations generated while hunting and gathering.  Dehaene views culture as essentially human, shaped by exaptations and reading, transmitted with support of the neuronal workspace and stabilized by neuronal recycling.  Damasio notes prokaryotes and social insects have developed cultural social behaviors.  Sapolsky argues that parents must show children how to transform their genetically derived capabilities into a culturally effective toolset.  He is interested in the broad differences across cultures of: Life expectancy, GDP, Death in childbirth, Violence, Chronic bullying, Gender equality, Happiness, Response to cheating, Individualist or collectivist, Enforcing honor, Approach to hierarchy; illustrating how different a person's life will be depending on the culture where they are raised.  Culture:
  • Is deployed during pregnancy & childhood, with parental mediation.  Nutrients, immune messages and hormones all affect the prenatal brain.  Hormones: Testosterone with anti-Mullerian hormone masculinizes the brain by entering target cells and after conversion to estrogen binding to intracellular estrogen receptors; have organizational effects producing lifelong changes.  Parenting style typically produces adults who adopt the same approach.  And mothering style can alter gene regulation in the fetus in ways that transfer epigenetically to future generations!  PMS symptoms vary by culture. 
  • Is also significantly transmitted to children by their peers during play.  So parents try to control their children's peer group.  
  • Is transmitted to children by their neighborhoods, tribes, nations etc. 
  • Influences the parenting style that is considered appropriate. 
  • Can transform dominance into honor.  There are ecological correlates of adopting honor cultures.  Parents in honor cultures are typically authoritarian. 
  • Is strongly adapted across a meta-ethnic frontier according to Turchin.  
  • Across Europe was shaped by the Carolingian empire. 
  • Can provide varying levels of support for innovation.  Damasio suggests culture is influenced by feelings: 
    • As motives for intellectual creation: prompting detection and diagnosis of homeostatic deficiencies, identifying desirable states worthy of creative effort.
    • As monitors of the success and failure of cultural instruments and practices
    • As participants in the negotiation of adjustments required by the cultural process over time 
  • Produces consciousness according to Dennet. 
,
Reading and writing present a conundrum.  The reader's brain contains neural networks tuned to reading.  With imaging a written word can be followed as it progresses from the retina through a functional chain that asks: Are these letters? What do they look like? Are they a word? What does it sound like? How is it pronounced? What does it mean?  Dehaene explains the importance of education in tuning the brain's networks for reading as well as good strategies for teaching reading and countering dyslexia.  But he notes the reading networks developed far too recently to have directly evolved.  And Dehaene asks why humans are unique in developing reading and culture. 

He explains the cultural engineering that shaped writing to human vision and the exaptations and neuronal structures that enable and constrain reading and culture. 

Dehaene's arguments show how cellular, whole animal and cultural complex adaptive system (CAS) are related.  We review his explanations in CAS terms and use his insights to link cultural CAS that emerged based on reading and writing with other levels of CAS from which they emerge. 

reading
;
Kauffman's adjacent possible
Kauffman explains how natural selection expands the 'adjacent possible', by exposing
Desmond & Moore paint a picture of Charles Darwin's life, expanded from his own highlights:
  • His naughty childhood, 
  • Wasted schooldays,
  • Apprenticeship with Grant,
  • His extramural activities at Cambridge, walks with Henslow, life with FitzRoy on the Beagle,
  • His growing love for science,
  • London: geology, journal and Lyell. 
  • Moving from Gower Street to Down and writing Origin and other books. 
  • He reviewed his position on religion: the long dispute with Emma, his slow collapse of belief - damnation for unbelievers like his father and brother, inward conviction being evolved and unreliable, regretting he had ignored his father's advice; while describing Emma's side of the argument.  He felt happy with his decision to dedicate his life to science.  He closed by asserting after Self & Cross-fertilization his strength will be exhausted.  
Following our summary of their main points, RSS frames the details from the perspective of complex adaptive system (CAS) theory.  Darwin placed evolution within a CAS framework, and built a network of supporters whose complementary skills helped drive the innovation. 
 
Darwinian
pre-adaptations, initially termed pre-adaptation refers to the coopting of some function for a new use.   to new competitive situations where they provide a selective advantage.  As an example he describes how the swim bladder emerged from a pre-adaptation of a fish lung.  "Paleontologists have traced the
This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
evolution
of swim bladders from early fish with lungs.  Some of these lived in oxygen-poor water.  The lungs grow as outpouchings from the gut.  The fish swallowed the oxygen-poor water, some of which entered the lungs, where air bubbles were absorbed, making it easier for the fish to survive.  But now water and air were both in a single lung and the lung was pre-adapted to evolve into a new function--a swim bladder that adjusted neutral buoyancy in the water column.  "

The emergence of multi-cellular
This page reviews the implications of reproduction initially generating a single initialized child cell.  For multi-cellular organisms this 'cell' must contain all the germ-line schematic structures including for organelles and multi-generational epi-genetic state.  Any microbiome is subsequently integrated during the innovative deployment of this creative event.  Organisms with skeletal infrastructure cannot complete the process of creation of an associated adult mind, until the proximate environment has been sampled during development.  The mechanism and resulting strategic options are discussed. 
organisms
depends on the previous development of:
Agents use sensors to detect events in their environment.  This page reviews how these events become signals associated with beneficial responses in a complex adaptive system (CAS).  CAS signals emerge from the Darwinian information model.  Signals can indicate decision summaries and level of uncertainty. 
signalling infrastructure
, differential responses to signal strength, movement, structural binding; and a
Plans emerge in complex adaptive systems (CAS) to provide the instructions that agents use to perform actions.  The component architecture and structure of the plans is reviewed. 
schematic plan
that allows the cellular
Plans are interpreted and implemented by agents.  This page discusses the properties of agents in a complex adaptive system (CAS). 
It then presents examples of agents in different CAS.  The examples include a computer program where modeling and actions are performed by software agents.  These software agents are aggregates. 
The participation of agents in flows is introduced and some implications of this are outlined. 
agent
to
This page discusses the interdependence of perception and representation in a complex adaptive system (CAS).  Hofstadter and Mitchell's research with Copycat is reviewed.  The bridging of a node from a network of 'well known' percepts to a new representational instance is discussed as it occurs in biochemistry, in consciousness and abstractly. 
respond to external position relative signals by transposing them to, and then maintaining the, cell local coordinate signals for its cell to produce synchronized actions
across the locally dividing population.  Techniques include segmentation, identity coordinate signalling, and presence of an ordered schematic response to the local coordinate identity of any segment. 

The emergence of order from chaos provides an explanation for the apparently random period between water droplets falling from a tap.  Typically the model of the system is poor and so the data captured about the system looks unpredictable - chaotic.  With a better model the system's operation can be explained with standard physical principles.  Hence chaos as defined here is different from complexity.   in CAS represents a powerful adaptive in evolutionary biology is a trait that increased the number of surviving offspring in an organism's ancestral lineage.  Holland argues: complex adaptive systems (CAS) adapt due to the influence of schematic strings on agents.  Evolution indicates fitness when an organism survives and reproduces.  For his genetic algorithm, Holland separated the adaptive process into credit assignment and rule discovery.  He assigned a strength to each of the rules (alternate hypothesis) used by his artificial agents, by credit assignment - each accepted message being paid for by the recipient, increasing the sender agent's rule's strength (implicit modeling) and reducing the recipient's.  When an agent achieved an explicit goal they obtained a final reward.  Rule discovery used the genetic algorithm to select strong rule schemas from a pair of agents to be included in the next generation, with crossing over and mutation applied, and the resulting schematic strategies used to replace weaker schemas.  The crossing over genetic operator is unlikely to break up a short schematic sequence that provides a building block retained because of its 'fitness';  In Deacon's conception of evolution, an adaptation is the realization of a set of constraints on candidate mechanisms, and so long as these constraints are maintained, other features are arbitrary. 
mechanism. 



























































































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This page looks at schematic structures and their uses.  It discusses a number of examples:
  • Schematic ideas are recombined in creativity. 
  • Similarly designers take ideas and rules about materials and components and combine them. 
  • Schematic Recipes help to standardize operations. 
  • Modular components are combined into strategies for use in business plans and business models. 

As a working example it presents part of the contents and schematic details from the Adaptive Web Framework (AWF)'s operational plan. 

Finally it includes a section presenting our formal representation of schematic goals. 
Each goal has a series of associated complex adaptive system (CAS) strategy strings. 
These goals plus strings are detailed for various chess and business examples. 
Strategy
| Design |
This page uses an example to illustrate how:
  • A business can gain focus from targeting key customers,
  • Business planning activities performed by the whole organization can build awareness, empowerment and coherence. 
  • A program approach can ensure strategic alignment. 
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