Fitness landscapes
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Representation of fitness landscapes

Summary
This web page reviews opportunities to find and capture new niches, based on studying fitness landscapes using 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
) theory.  CAS SuperOrganisms are able to capture rich niches.  A variety of CAS are included: chess, prokaryotes, nation states, businesses, economies; along with change mechanisms: evolution and artificial intelligence; agency effects and environmental impacts. 

Genetic algorithms supported by fitness functions are compared to genetic operators. 

Early evolution of life and its inbuilt constraints are discussed. 

Strategic clustering, goals, flexibility and representation of state are considered
Introduction
The geneticist Sewall Wright suggested that each point in a genetic combinatorial set be assigned a measure of its adaptiveness 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. 
.  As a three dimensional representation this has been described as a fitness landscape. 
While its an attractive metaphor and it has inspired key work on
This web page reviews opportunities to enhance computing theory and practice by using biological mechanisms and complex adaptive system (CAS) theory. 
evolutionary computation
the vision of a landscape can be misinterpreted.  Stuart Kauffman's 'adjacent possible' seems to better illustrate the way
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
explore niches to enhance
This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
survival and reproduction
.  That fitness is, according to Dawkins, a suitcase word with at least five meanings in biology:
  1. Darwin and Wallace thought in terms of the capacity to survive and reproduce, but they were considering discrete aspects such as chewing grass - where hard enamel would improve the relative fitness. 
  2. Population geneticists: Ronald Fisher, Sewall Wright, J.B.S. Haldane; consider selection at a locus where for a genotype: green eyes vs blue eyes; one with higher fitness can be identified from genotypic frequencies and gene frequencies, with all other variations averaged out. 
  3. Whole organism 'integrated' fitness.  Dawkins notes there is only ever one instance of a specific organism.  Being unique, comparing the relative success of its offspring makes little sense.  Over a huge number of generations the individual is likely to have provided a contribution to everyone in the pool or no one. 
  4. Inclusive fitness, where according to Hamilton, fitness depends on an organism's actions or effects on its children or its relative's children, a model where natural selection favors organs and behaviors that cause the individual's genes to be passed on.  It is easy to mistakenly count an offspring in multiple relative's fitness assessments. 
  5. Personal fitness represents the effects a person's relatives have on the individual's fitness [3].  When interpreted correctly fitness [4] and fitness [5] are the same. 
changes as the agents and
The complex adaptive system (CAS) nature of a value delivery system is first introduced.  It's a network of agents acting as relays. 

The critical nature of hub agents and the difficulty of altering an aligned network is reviewed. 

The nature of and exceptional opportunities created by platforms are discussed. 

Finally an example of aligning a VDS is presented. 
environment
alter adds further complications. 
The early adjacent possible is going to be limited.  Entities 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;
were highly constrained.  The operation of autonomous entities are entities which:
  • Are far from equilibrium
  • Consume and save low entropy
  • Can use accessible low entropy to maintain themselves
must be constrained to preserve the low entropy, far from equilibrium dependency.  So
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. 
constraint
is expected to be present in all complex adaptive systems (
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
).  Capture of additional niches can undermine the control scheme with rapid shifts in wealth is schematically useful information and its equivalent, schematically useful energy, to paraphrase Beinhocker.  It is useful because an agent has schematic strategies that can utilize the information or energy to extend or leverage control of the cognitive niche.    and power: British merchant expansion during the reign of Queen Anne was untaxed, empowering the merchants and undermining the landed aristocrats and monarchy; until additional constraints are built.  Eventually,
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. 
constraint based phenomena enable Darwinian competition
.  Such
This page discusses the mechanisms and effects of emergence underpinning any complex adaptive system (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. 
emergent
agents are Turing machines, a machine specified by mathematician Alan Turing which is the blueprint for the electronic programmable computer.  It consists of an infinite tape on which symbols can be written.  A movable read/write tape head which can move about the tape and write on or read symbols from the tape.  A set of rules that tell the head what to do next. 
enabled by enzymatic, a protein with a structure which allows it to operate as a chemical catalyst and a control switch. 
control.  One can imagine that early
This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
evolved
agents had access to a very small set of
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
, types 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. 
sensor
or
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
of the environment.  Indeed the agents may well have been identical and placing each other under heavy threat in using the same strategies to compete directly for the few niches they could utilize. 

Prokaryotic, a single cell system with two main types: (1) Archaea, and (2) Eubacteria.  Prokaryotes have their own DNA and infrastructure within a single enclosure.  They are biochemically very versatile: Photosynthesis -> Electron transport & phosphorylation, Enzymatic regulation and catalysis of chemical reactions, Catabolize -> phosphate bond energy, ATP cycle, glycolysis, TCA cycle, Electron transports, oxidative phosphorylation, oxidation of fatty acids, oxidative degradation of amino acids; Biosynthesis & utilization of phosphate bond energy -> carbohydrates, lipids, amino acids, nucleotides, muscle & motile structures; membrane barriers & active transports, hormones; Replication, Transcription, Translation, Regulation of gene expression; self-assembly; They utilize cell membrane receptors and signalling to support symbiotic cooperation with other cellular entities, including: in the microbiome, and as chloroplasts and mitochondria within eukaryotic cells. 
populations can use
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. 
mutation
to explore the adjacent possible.  And due to prokaryotes focus on [bio]chemistry, mutation indirectly gains access to the chemical and physical forces that enable: action, energy capture and leverage, low level and computationally intrinsic
Representing state in emergent entities is essential but difficult.  Various structures are used to enhance the rate and scope of state transitions.  Examples are discussed. 
structurally enhanced state
, and reversible creation of chemical building blocks.  These capabilities support
This page introduces the many ways a complex modeling and coordination activity can be implemented using agent-based programming (see presentation). 

It describes how salient schematic alternative strings can be used to model a situation and make a decision under evolved control. 

It also introduces bottom up model codelets and complex techniques that are covered more fully on other pages. 

Constraints on the modeling process including requirements for timeliness, parallelism, synchronization and emergence of new models are discussed. 

Once a schematic sequence is selected by a group codelet or any additional type of modeling codelet the codelet will initiate an iterative cycle of detect, signal, match, deploy.  This allows the actions of a schematically selected sequence of model codelets to aggregate into a focused agent. 

A series of example signals sent by complex modeling codelets along with their associated operons and subgroup schematic sequences are included.  The signals are sent by the:
  • merge streams spdca builder - The initiator of merge streams's pdca cycle (see schematic pdca).
  • merge streams dcycip builder - The initiator of the planning phase of the merge streams's pdca cycle. 
  • merge streams cassert builder - The initiator of the mergestreams's case resolved assert true conditional cascade.  It is a structurally enhanced codelet which activates at the end of the 'do' phase and signals the nucleus. 
  • merge streams indsloc builder - The start locator codelet finds the application schemata's start operon
  • merge streams shsloc builder - A start locator codelet that finds an alternative start operon in the application schematic operon
  • merge streams rchpair builder - A receptor that detects and relays an application signal
  • pdca ecycdop builder - A cyclin simulation codelet which signals entry to the 'do' phase of the pdca. 
  • pdca acycchp builder - A cyclin simulation codelet which signals entry to the 'check' phase of the pdca. 
  • pdca bcycacp builder - A cyclin simulation codelet which signals entry to the 'act' phase of the pdca. 
And the Slipnet configuration which activates the schematic subgroup sequence <mergestreams> <for> <case> <resolved> <assert> <true> is included. 
schematic modeling
This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
Evolution
by
Richard Dawkin's explores how nature has created implementations of designs, without any need for planning or design, through the accumulation of small advantageous changes. 
natural selection
will support beneficial phenotypes is the system that results from the controlled expression of the genes.  It is typically represented by a prokaryotic cell or the body of a multi-cell animal or plant.  The point is that the genes provide the control surface and the abstract recipe that has been used to generate the cell.  , through survival and reproduction.  But without a way to share these enhancements, clones with different beneficial mutations will interfere competitively is a model that explains the relatively slow stabilization, and potential disappearance (fixation of the competing variant), of a beneficial mutation in asexually reproducing populations.  Herman Muller developed the model in 1932.  Muller noted that beneficial mutations are distributed within the population by sexual reproduction's recombination operator, which does not exist in the basic asexual mechanism.  Different beneficial mutations occurring in different organisms in the population will compete, and so through this interference some may be lost.  Muller suggested clonal interference would impact the asexual organism's ability to adapt and proposed it as a justification for sexual reproduction.  Experimental data showed asexual and sexual organisms with similar adaptation rates, because of DNA sharing through plasmids. 
, and beneficial mutations will spread slowly and through genetic drift is the random change in the population of specific gene alleles from one generation to the next. 
may be lost from the population.  Prokaryotes overcome this problem to a significant extent by sharing plasmids provide bacteria with a way to transfer parts of their DNA complement with one another.  The effect is to ensure that useful mutations can become rapidly distributed within a population of bacteria.  Because the plasmid reproduces asexually beneficial mutations will result in competition between hosts containing different plasmid variants through clonal interference. 


SuperOrganism is a wealthy autonomous entity needing and controlling the richest niches in the proximate environment, that emerges from the bundled cooperation of schematically aligned agents.   The term is based on the social insect model, used by: ants, termites, and bees; and identified by Holldobler & E.O. Wilson.  These genetically identical insect superorganisms cooperatively limit their reproduction to align with the resources available in the niche.  For humans it is an evolved cultural strategy used when the environment is supportive, but it is dependent on our imperfect cognitive assessment of kinship.  It depends on inter-agent signalling.  In both insects and humans it allows specialization, and encourages operations and flows that are tightly controlled, limiting waste, leveraging parallel activity, supporting coherence.  Superorganisms reflect cliodynamic flows.  A superorganism has a development and operational phase.  As additional agents are coopted into the superorganism they align, participate in supply and demand activities and so contribute to the evolutionary amplification.  Damasio notes that prokaryotes, in rich environments, can similarly operate in a symbiotic fashion expressing cultural behaviors. 
configurations, exemplified by social insects, can extend the actions they use to forage, to
The squeaky wheel gets attention in a complex adaptive system (CAS). 
additionally describe to their siblings
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
of where food and water sources are.  Other members of the colony use the models they develop in response to initiate their own participation in the cooperative capture of resources. 
The bundling of various strategies allows insect 'superorganisms' to evolutionarily out compete specialist insects that cannot bear the cost required for each individual to be competitive.  The 'superorganism' is far more
To benefit from shifts in the environment agents must be flexible.  Being sensitive to environmental signals agents who adjust strategic priorities can constrain their competitors. 
flexible
.  It can coordinate lines of attack to
This page discusses the benefits of bringing agents and resources to the dynamically best connected region of a complex adaptive system (CAS). 
the central area of action
, be the master of communications, focus colony members on the
This page discusses the strategy of going around the competitor's flank to reach and assault its rear. 
envelopment
of large prey insects and leverage the resulting evolutionary amplifier. 

In less beneficial
This page discusses the potential of the vast state space which supports the emergence of complex adaptive systems (CAS).  Kauffman describes the mechanism by which the system expands across the space. 
environments
the solitary strategies of beetles, spiders and other competitors of 'superorganisms' win out.  The pre-conditions for 'superorganism' success include access to enough resources to sustain an active colony.  Evolution ensures that focused strategies can be efficiently aligned with specific constrained niches. 

Also the cooperative communication infrastructure leveraged by 'superorganisms' leaves them open to
Rather than oppose the direct thrust of some environmental flow agents can improve their effectiveness with indirect responses.  This page explains how agents are architected to do this and discusses some examples of how it can be done. 
indirect attack
by competitors who are able to manipulate the signalling, is an emergent capability which is used by cooperating agents to support coordination & rival agents to support control and dominance.  In eukaryotic cells signalling is used extensively.  A signal interacts with the exposed region of a receptor molecule inducing it to change shape to an activated form.  Chains of enzymes interact with the activated receptor relaying, amplifying and responding to the signal to change the state of the cell.  Many of the signalling pathways pass through the nuclear membrane and interact with the DNA to change its state.  Enzymes sensitive to the changes induced in the DNA then start to operate generating actions including sending further signals.  Cell signalling is reviewed by Helmreich.  Signalling is a fundamental aspect of CAS theory and is discussed from the abstract CAS perspective in signals and sensors.  In AWF the eukaryotic signalling architecture has been abstracted in a codelet based implementation.  To be credible signals must be hard to fake.  To be effective they must be easily detected by the target recipient.  To be efficient they are low cost to produce and destroy. 
infrastructure and
This page discusses the strategy of confusing the control system of a complex adaptive system (CAS). 
unbalance
the emergent responses of the colony.  

Prokaryotes, a single cell system with two main types: (1) Archaea, and (2) Eubacteria.  Prokaryotes have their own DNA and infrastructure within a single enclosure.  They are biochemically very versatile: Photosynthesis -> Electron transport & phosphorylation, Enzymatic regulation and catalysis of chemical reactions, Catabolize -> phosphate bond energy, ATP cycle, glycolysis, TCA cycle, Electron transports, oxidative phosphorylation, oxidation of fatty acids, oxidative degradation of amino acids; Biosynthesis & utilization of phosphate bond energy -> carbohydrates, lipids, amino acids, nucleotides, muscle & motile structures; membrane barriers & active transports, hormones; Replication, Transcription, Translation, Regulation of gene expression; self-assembly; They utilize cell membrane receptors and signalling to support symbiotic cooperation with other cellular entities, including: in the microbiome, and as chloroplasts and mitochondria within eukaryotic cells. 
form SuperOrganisms and symbiotic is a long term situation between two, or more, different agents where the resources of both are shared for mutual benefit.  Some of the relationships have built remarkable dependencies: Tremblaya's partnership with citrus mealybugs and bacterial DNA residing in the mealybug's genome, Aphids with species of secondary symbiont bacteria deployed sexually from a male aphid sperm reservoir and propagated asexually by female aphids only while their local diet induces a dependency.  If the power relations and opportunities change for the participants then they will adapt and the situation may transform into separation, predation or parasitism. 
partnerships, demonstrating the
To benefit from shifts in the environment agents must be flexible.  Being sensitive to environmental signals agents who adjust strategic priorities can constrain their competitors. 
flexibility
of the
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 strategies
that
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 operators
can find and deposit in the phenotypic is the system that results from the controlled expression of the genes.  It is typically represented by a prokaryotic cell or the body of a multi-cell animal or plant.  The point is that the genes provide the control surface and the abstract recipe that has been used to generate the cell.   tool bag to maintain homeostasis is, according to Damasio, the fundamental set of operations at the core of life, from the earliest and long-vanished point of its beginning in early biochemistry to the present.  It is the powerful, unthought, unspoken imperative, whose discharge implies, for every living organism, small or large, nothing less than enduring and prevailing.  Damasio stresses that the operations that ensure prevailing ensure life is regulated within a range that is not just compatible with survival but also conducive to flourishing, to protection of life into the future of an organism or a species.  Prevailing implies mechanisms for monitoring and modeling the state of the organism, controlling and constraining the flows of energy and resources through schematic agency, and to facilitate exploring the environment and acting on signals of modeled opportunities and threats.  Global homeostasis of multi-organ animals requires endocrine, immune, circulatory and nervous 'systems' and results in the emergence of minds, feelings, consciousness, machinery of affect and complex movements.  The emergence of feelings allowed the homeostatic process to become enhanced by a subjective representation of the organism's state and proximate environment within the mind.  Feelings operating in minds allowed conscious decisions to extend homeostasis to the sociocultural domain. 
.  Tools associated by transcription is the process where DNA is converted into messenger m-RNA.  A complex of enzymes cooperates to bind to the DNA and generate the m-RNA copy.  There are a number of such transcription complexes which are based on RNA polymerase I, II or III. 
and translation is the process where messenger m-RNA is cross coded by Ribosomal agents and t-RNA into an amino-acid polymer.   with the schematic DNA (DNA), a polymer composed of a chain of deoxy ribose sugars with purine or pyrimidine side chains.  DNA naturally forms into helical pairs with the side chains stacked in the center of the helix.  It is a natural form of schematic string.  The purines and pyrimidines couple so that AT and GC pairs make up the stackable items.  A code of triplets of base pairs (enabling 64 separate items to be named) has evolved which now redundantly represents each of the 20 amino-acids that are deployed into proteins, along with triplets representing the termination sequence.  Chemical modifications and histone binding (chromatin) allow cells to represent state directly on the DNA schema.  To cope with inconsistencies in the cell wide state second messenger and evolved amplification strategies are used.   building blocks. 

The most unlikely SuperOrganism, because of the heterogeneous DNA of the
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
,
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. 

is the human
cultural 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. 
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
, which is enabled by cognitive identification of relatives
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. 
.  This CAS has allowed humanity to leverage language to innovate is the economic realization of invention and combinatorial exaptation.  Keynes noted it provided the unquantifiable beneficial possibility that limits fear of uncertainty.  Innovation operates across all CAS, being supported by genetic and cultural means.  Creativity provides the mutation and recombination genetic operators for the cultural process.  While highly innovative, monopolies: AT&T, IBM; usually have limited economic reach, constraining productivity.  This explains the use of regulation, or even its threat, that can check their power and drive the creations across the economy. 
and
Sven Beckert describes the historic transformation of the growing, spinning, weaving, manufacture of cotton goods and their trade over time.  He describes the rise of a first global commodity, its dependence on increasing: military power, returns for the control points in the value delivery system(VDS), availability of land and labor to work it including slaves. 

He explains how cotton offered the opportunity for industrialization further amplifying the productive capacity of the VDS and the power of the control points.  This VDS was quickly copied.  The increased capacity of the industrialized cotton complex adaptive system (CAS) required more labor to operate the machines.  Beckert describes the innovative introduction of wages and the ways found to mobilize industrial labor. 

Beckert describes the characteristics of the industrial cotton CAS which made it flexible enough to become globally interconnected.  Slavery made the production system so cost effective that all prior structures collapsed as they interconnected.  So when the US civil war blocked access to the major production nodes in the American Deep South the CAS began adapting. 

Beckert describes the global reconstruction that occurred and the resulting destruction of the traditional ways of life in the global countryside.  This colonial expansion further enriched and empowered the 'western' nation states.  Beckert explains how other countries responded by copying the colonial strategies and creating the opportunities for future armed conflict among the original colonialists and the new upstarts. 

Completing the adaptive shifts, Beckert describes the advocates for industrialization in the colonized global south and how over time they joined the global cotton CAS disrupting the early western manufacturing nodes and creating the current global CAS dominated by merchants like Wal-Mart pulling goods through a network of clothing manufacturers, spinning and weaving factories, and growers competing with each other on cost. 

Following our summary of Beckert's book, RSS comments from the perspective of CAS theory.  The transformation of disconnected peasant farmers, pastoral warriors and their lands into a supply chain for a highly profitable industrial CAS required the development over time: of military force, global transportation and communication networks, perception and representation control networks, capital stores and flows, models, rules, standards and markets; along with the support at key points of: barriers, disruption, and infrastructure and evolved amplifiers.  The emergent system demonstrates the powerful constraining influence of extended phenotypic alignment. 

initiate a global CAS


Chess has supported the exploration of a large number of proximate niches by 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. 
schematically
driven
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
.  It does not explore
This page discusses the mechanisms and effects of emergence underpinning any complex adaptive system (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. 
emergence
or the appearance of new physical technologies are defined by Beinhocker as methods and designs for transforming matter, energy, and information from one state into another in pursuit of a goal or goals.  The effects of nuclear and genetic physical technologies are already challenging.  Beinhocker adds artificial intelligence and nanotechnology as emerging physical technologies that support access to huge new niches and introduce additional challenges. 
.  But it clearly associates schematic strings of
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. 
flows
of move pairs with development is a phase during the operation of a CAS agent.  It allows for schematic strategies to be iteratively blended with environmental signals to solve the logistical issues of migrating newly built and transformed sub-agents.  That is needed to achieve the adult configuration of the agent and optimize it for the proximate environment.  Smiley includes examples of the developmental phase agents required in an emergent CAS.  In situations where parents invest in the growth and memetic learning of their offspring the schematic grab bag can support optimizations to develop models, structures and actions to construct an adept adult.  In humans, adolescence leverages neural plasticity, elder sibling advice and adult coaching to help prepare the deploying neuronal network and body to successfully compete. 
and deployment of two SuperOrganism is a wealthy autonomous entity needing and controlling the richest niches in the proximate environment, that emerges from the bundled cooperation of schematically aligned agents.   The term is based on the social insect model, used by: ants, termites, and bees; and identified by Holldobler & E.O. Wilson.  These genetically identical insect superorganisms cooperatively limit their reproduction to align with the resources available in the niche.  For humans it is an evolved cultural strategy used when the environment is supportive, but it is dependent on our imperfect cognitive assessment of kinship.  It depends on inter-agent signalling.  In both insects and humans it allows specialization, and encourages operations and flows that are tightly controlled, limiting waste, leveraging parallel activity, supporting coherence.  Superorganisms reflect cliodynamic flows.  A superorganism has a development and operational phase.  As additional agents are coopted into the superorganism they align, participate in supply and demand activities and so contribute to the evolutionary amplification.  Damasio notes that prokaryotes, in rich environments, can similarly operate in a symbiotic fashion expressing cultural behaviors. 
armies (social technologies are defined by Beinhocker as methods and designs for organizing people in pursuit of a goal or goals. He views the three most significant social technologies as: markets, science, and democracy.  A war example is Fuller & Liddell Hart's theory of high-speed tank warfare, subsequently instantiated by Guderian as Blitzkrieg. 
) using occupation of different squares to project and capture power.  It does this through transformation of the
The complex adaptive system (CAS) nature of a value delivery system is first introduced.  It's a network of agents acting as relays. 

The critical nature of hub agents and the difficulty of altering an aligned network is reviewed. 

The nature of and exceptional opportunities created by platforms are discussed. 

Finally an example of aligning a VDS is presented. 
environment
by leverage of: schematic wealth is schematically useful information and its equivalent, schematically useful energy, to paraphrase Beinhocker.  It is useful because an agent has schematic strategies that can utilize the information or energy to extend or leverage control of the cognitive niche.   , direct and
Rather than oppose the direct thrust of some environmental flow agents can improve their effectiveness with indirect responses.  This page explains how agents are architected to do this and discusses some examples of how it can be done. 
indirect
projection of
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. 
constraints
over the 64 squares on the board enabled by the rule based capabilities of the pieces.  The necessary
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. 
agency
depends on the schemata having been
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. 
modeled
in the
Computational theory of the mind and evolutionary psychology provide Steven Pinker with a framework on which to develop his psychological arguments about the mind and its relationship to the brain.  Humans captured a cognitive niche by natural selection 'building out' specialized aspects of their bodies and brains resulting in a system of mental organs we call the mind. 

He garnishes and defends the framework with findings from psychology regarding: The visual system - an example of natural selections solutions to the sensory challenges of inverse modeling of our environment; Intensions - where he highlights the challenges of hunter gatherers - making sense of the objects they perceive and predicting what they imply and natural selections powerful solutions; Emotions - which Pinker argues are essential to human prioritizing and decision making; Relationships - natural selection's strategies for coping with the most dangerous competitors, other people.  He helps us understand marriage, friendships and war. 

These conclusions allow him to understand the development and maintenance of higher callings: Art, Music, Literature, Humor, Religion, & Philosophy; and develop a position on the meaning of life. 

Complex adaptive system (CAS) modeling allows RSS to frame Pinker's arguments within humanity's current situation, induced by powerful evolved amplifiers: Globalization, Cliodynamics, The green revolution and resource bottlenecks; melding his powerful predictions of the drivers of human behavior with system wide constraints.  The implications are discussed. 

mind
of the players: 
The great variety of chess players displays how SuperOrganisms can be developed and operated in different ways:

Nation states are typically
This page discusses the mechanisms and effects of emergence underpinning any complex adaptive system (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. 
emergent
autonomous entities are entities which:
  • Are far from equilibrium
  • Consume and save low entropy
  • Can use accessible low entropy to maintain themselves
.  The US is the United States of America.  , by adopting a written constitution and legislation developed iteratively by congress to be operated by the executive, demonstrates a notably
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
approach to the emergence of a national SuperOrganism is a wealthy autonomous entity needing and controlling the richest niches in the proximate environment, that emerges from the bundled cooperation of schematically aligned agents.   The term is based on the social insect model, used by: ants, termites, and bees; and identified by Holldobler & E.O. Wilson.  These genetically identical insect superorganisms cooperatively limit their reproduction to align with the resources available in the niche.  For humans it is an evolved cultural strategy used when the environment is supportive, but it is dependent on our imperfect cognitive assessment of kinship.  It depends on inter-agent signalling.  In both insects and humans it allows specialization, and encourages operations and flows that are tightly controlled, limiting waste, leveraging parallel activity, supporting coherence.  Superorganisms reflect cliodynamic flows.  A superorganism has a development and operational phase.  As additional agents are coopted into the superorganism they align, participate in supply and demand activities and so contribute to the evolutionary amplification.  Damasio notes that prokaryotes, in rich environments, can similarly operate in a symbiotic fashion expressing cultural behaviors. 
.  The approach seems analogous to chess master play, displaying both the opening and middle-game aspects.  Most other states, do not have written constitutional foundations and so, depend on cultural 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. 
overlays to the mixed genetic base of humanity, to support the behavioral operation of the SuperOrganism. 

Businesses are also autonomous entities are entities which:
  • Are far from equilibrium
  • Consume and save low entropy
  • Can use accessible low entropy to maintain themselves
.  They can be supported by the
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. 
memetic
wealth is schematically useful information and its equivalent, schematically useful energy, to paraphrase Beinhocker.  It is useful because an agent has schematic strategies that can utilize the information or energy to extend or leverage control of the cognitive niche.    the educational institutions present to business students.  The niches that businesses compete for are also defined by their competitors:
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
, strategies and innovations is the economic realization of invention and combinatorial exaptation.  Keynes noted it provided the unquantifiable beneficial possibility that limits fear of uncertainty.  Innovation operates across all CAS, being supported by genetic and cultural means.  Creativity provides the mutation and recombination genetic operators for the cultural process.  While highly innovative, monopolies: AT&T, IBM; usually have limited economic reach, constraining productivity.  This explains the use of regulation, or even its threat, that can check their power and drive the creations across the economy. 
; and while the memetic plans have not been optimized over millions of years by
This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
evolution
, the strategies developed for the 'cognitive niche,' which have, provide a good starting point.  And the influence of
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
properties:
Peter Turchin describes how major pre-industrial empires developed due to effects of geographic boundaries constraining the empires and their neighbors' interactions.  Turchin shows how the asymmetries of breeding rates and resource growth rates results in dynamic cycles within cycles.  After the summary of Turchin's book complex adaptive system (CAS) theory is used to augment Turchins findings. 
cliodynamic cycles
,
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. 
constraints
,
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
and
This page reviews the strategy of setting up an arms race.  At its core this strategy depends on being able to alter, or take advantage of an alteration in, the genome or equivalent.  The situation is illustrated with examples from biology, high tech and politics. 
evolved amplifiers
- including
This page discusses the effect of the network on the agents participating in a complex adaptive system (CAS).  Small world and scale free networks are considered. 
network effects
,
This page discusses the benefits of geographic clusters of agents and resources at the center of a complex adaptive system (CAS). 
geographic clustering
,
This page reviews the inhibiting effect of the value delivery system on the expression of new phenotypic effects within an agent. 
extended phenotypic alignment
,
This page reviews Christensen's disruption of a complex adaptive system (CAS).  The mechanism is discussed with examples from biology and business. 
disruption
, presence or absence of
Representing state in emergent entities is essential but difficult.  Various structures are used to enhance the rate and scope of state transitions.  Examples are discussed. 
structurally enhanced state
, doomsday machine integrates a:
  • Signal that advertises the presence of the doomsday machine
  • Machine that once started can't be stopped.  
  • Uncontrollable initiation of the machine based on some constraint. 
  • Catastrophic result for all parties once the machine is started.  There is the potential for both parties to participate in an arms race. 
This page reviews the implications of doomsday machines in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
implications
; shapes the niches in predictable ways. 

A few businesses have worked on using a schematic approach to their operations:
But most multi-national businesses shifted to focus on low cost globalization based strategies without schematic operations: GE, Wal-Mart

Economics is the study of trade between humans.  Traditional Economics is based on an equilibrium model of the economic system.  Traditional Economics includes: microeconomics, and macroeconomics.  Marx developed an alternative static approach.  Limitations of the equilibrium model have resulted in the development of: Keynes's dynamic General Theory of Employment Interest & Money, and Complexity Economics.  Since trading depends on human behavior, economics has developed behavioral models including: behavioral economics. 
currently prioritizes
Matt Ridley demonstrates the creative effect of man on the World. He highlights:
  • A list of preconditions resulting in
  • Additional niche capture & more free time 
  • Building a network to interconnect memes processes & tools which
  • Enabling inter-generational transfers
  • Innovations that help reduce environmental stress even as they leverage fossil fuels

trade
over
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. 
constraints
Sugerscape explores fitness is, according to Dawkins, a suitcase word with at least five meanings in biology:
  1. Darwin and Wallace thought in terms of the capacity to survive and reproduce, but they were considering discrete aspects such as chewing grass - where hard enamel would improve the relative fitness. 
  2. Population geneticists: Ronald Fisher, Sewall Wright, J.B.S. Haldane; consider selection at a locus where for a genotype: green eyes vs blue eyes; one with higher fitness can be identified from genotypic frequencies and gene frequencies, with all other variations averaged out. 
  3. Whole organism 'integrated' fitness.  Dawkins notes there is only ever one instance of a specific organism.  Being unique, comparing the relative success of its offspring makes little sense.  Over a huge number of generations the individual is likely to have provided a contribution to everyone in the pool or no one. 
  4. Inclusive fitness, where according to Hamilton, fitness depends on an organism's actions or effects on its children or its relative's children, a model where natural selection favors organs and behaviors that cause the individual's genes to be passed on.  It is easy to mistakenly count an offspring in multiple relative's fitness assessments. 
  5. Personal fitness represents the effects a person's relatives have on the individual's fitness [3].  When interpreted correctly fitness [4] and fitness [5] are the same. 
in a simple trading scenario including genetic algorithm-supported reproduction.  The prioritization of trade is supported by the fossil fuel driven exponential increase in food supply.  This situation is
Peter Turchin describes how major pre-industrial empires developed due to effects of geographic boundaries constraining the empires and their neighbors' interactions.  Turchin shows how the asymmetries of breeding rates and resource growth rates results in dynamic cycles within cycles.  After the summary of Turchin's book complex adaptive system (CAS) theory is used to augment Turchins findings. 
atypical historically
, minimizes the impact of
Sven Beckert describes the historic transformation of the growing, spinning, weaving, manufacture of cotton goods and their trade over time.  He describes the rise of a first global commodity, its dependence on increasing: military power, returns for the control points in the value delivery system(VDS), availability of land and labor to work it including slaves. 

He explains how cotton offered the opportunity for industrialization further amplifying the productive capacity of the VDS and the power of the control points.  This VDS was quickly copied.  The increased capacity of the industrialized cotton complex adaptive system (CAS) required more labor to operate the machines.  Beckert describes the innovative introduction of wages and the ways found to mobilize industrial labor. 

Beckert describes the characteristics of the industrial cotton CAS which made it flexible enough to become globally interconnected.  Slavery made the production system so cost effective that all prior structures collapsed as they interconnected.  So when the US civil war blocked access to the major production nodes in the American Deep South the CAS began adapting. 

Beckert describes the global reconstruction that occurred and the resulting destruction of the traditional ways of life in the global countryside.  This colonial expansion further enriched and empowered the 'western' nation states.  Beckert explains how other countries responded by copying the colonial strategies and creating the opportunities for future armed conflict among the original colonialists and the new upstarts. 

Completing the adaptive shifts, Beckert describes the advocates for industrialization in the colonized global south and how over time they joined the global cotton CAS disrupting the early western manufacturing nodes and creating the current global CAS dominated by merchants like Wal-Mart pulling goods through a network of clothing manufacturers, spinning and weaving factories, and growers competing with each other on cost. 

Following our summary of Beckert's book, RSS comments from the perspective of CAS theory.  The transformation of disconnected peasant farmers, pastoral warriors and their lands into a supply chain for a highly profitable industrial CAS required the development over time: of military force, global transportation and communication networks, perception and representation control networks, capital stores and flows, models, rules, standards and markets; along with the support at key points of: barriers, disruption, and infrastructure and evolved amplifiers.  The emergent system demonstrates the powerful constraining influence of extended phenotypic alignment. 

industrialization
's constraint based strategies and is
E. O. Wilson reviews the effect of man on the natural world to date and explains how the two systems can coexist most effectively. 
currently inducing stress on the planet


This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
Evolution
has the effect of
Richard Dawkin's explores how nature has created implementations of designs, without any need for planning or design, through the accumulation of small advantageous changes. 
gathering mechanisms
that create, or gain access to, additional niches into the
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
grab bag.  The pressure to specialize and the capability to do so ensure that any action that enhances a mechanism that creates, or improves access to, an additional niche will be captured.  Epistasis tends to help extend the portfolio of the schematic structure.  Significantly the niches that evolution gains access to are almost all of its creation.  The
Peter Medawar writes about key historic events in the evolution of medical science. 
scientific method
transfers
Richard Dawkin's explores how nature has created implementations of designs, without any need for planning or design, through the accumulation of small advantageous changes. 
evolved designs
into abstract processes that are
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. 

written down
, copied, applied and can be amplified through
Salman Khan argues that the evolved global education system is inefficient and organized around constraining and corralling students into accepting dubious ratings that lead to mundane roles.  He highlights a radical and already proven alternative which offers effective self-paced deep learning processes supported by technology and freed up attention of teams of teachers.  Building on his personal experience of helping overcome the unjustified failing grade of a relative, Khan:
  • Iteratively learns how to teach: Starting with Nadia, Leveraging short videos focused on content, Converging on mastery, With the help of neuroscience, and filling in dependent gaps; resulting in a different approach to the mainstream method. 
  • Assesses the broken US education system: Set in its ways, Designed for the 1800s, Inducing holes that are hidden by tests, Tests which ignore creativity.  The resulting teaching process is so inefficient it needs to be supplemented with homework.  Instead teachers were encouraging their pupils to use his tools at home so they could mentor them while they attended school, an inversion that significantly improves the economics. 
  • Enters the real world: Builds a scalable service, Working with a real classroom, Trying stealth learning, At Khan Academy full time,  In the curriculum at Los Altos, Supporting life-long learning. 
  • Develops The One World Schoolhouse: Back to the future with a one room school, a robust teaching team, and creativity enabled; so with some catalysis even the poorest can become educated and earn credentials for current jobs. 
  • Wishes he could also correct: Summer holidays, Transcript based assessments, College education;
  • Concludes it is now possible to provide the infrastructure for creativity to emerge and to support risk taking. 

Following our summary of his arguments RSS frames them from the perspective of complex adaptive system (CAS) theory.  Disruption is a powerful force for change but if its force is used to support the current teachers to adopt new processes can it overcome the extended phenotypic alignment and evolutionary amplifiers sustaining the current educational network? 

education
.  Both science and education leverage
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
to improve niche access.  But the Prussian design of education removes the integration with somatic, Schematic structures which are used to support the operation of the agent.  They are modified as the agent's state changes unlike the germ-line schemata.   schema development and constrains the full deployment of schematic plans to a limited subset of
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
.  This will limit the potential for creativity

Isaacson uses the historic development of the global cloud of web services to explore Ada Lovelace's ideas about thinking machines and poetic science.  He highlights the value of computer augmented human creativity and the need for liberal arts to fulfill the process. 
Complex adaptive system (CAS) models of agent networks and collaboration are discussed. 

Artificial intelligence
(AI) currently utilizes a different approach.  Instead of
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 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. 
operations
it leverages neural networks are representational models that achieve high performance on difficult pattern recognition problems in vision and speech.  But they need specialized training methods such as greedy layerwise pre-training or HF optimization.  Researchers are gaining access to the participation of the individual 'neurons' using: visualization, attribution, dimensionality reduction, interpretability; (Mar 2018)
with
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
using Samuel weightings to create classifiers from human structured information stores accessible in the cloud.  These data weighted classifiers provide associated
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
with access to additional niches and enable
This page introduces a series of asymmetries which encourage different strategic approaches.   
The differences found in business, sexual selection, gamete structure, as well as in chess encourage escalations in the interactions. 
And yet the systems including these asymmetries can be quite stable. 
asymmetric
competition with former approaches to niche ownership. 
This page discusses the benefits of bringing agents and resources to the dynamically best connected region of a complex adaptive system (CAS). 
Centralization
of the
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
and leverage of
This page reviews the strategy of setting up an arms race.  At its core this strategy depends on being able to alter, or take advantage of an alteration in, the genome or equivalent.  The situation is illustrated with examples from biology, high tech and politics. 
evolved amplification
has pulled wealth is schematically useful information and its equivalent, schematically useful energy, to paraphrase Beinhocker.  It is useful because an agent has schematic strategies that can utilize the information or energy to extend or leverage control of the cognitive niche.    towards the AI and cloud infrastructure niche owners.  But the collapse of competitive niches may undermine the economy is a human SuperOrganism complex adaptive system (CAS) which operates and controls trade flows within a rich niche.  Economics models economies.  Robert Gordon has described the evolution of the American economy.  Like other CAS, economic flows are maintained far from equilibrium by: demand, financial flows and constraints, supply infrastructure constraints, political and military constraints; ensuring wealth, legislative control, legal contracts and power have significant leverage through evolved amplifiers. 
supporting the new wealth leading to its shrinkage. 

Contrary to the pressure to change are mechanisms that drive superior phenotypic is the system that results from the controlled expression of the genes.  It is typically represented by a prokaryotic cell or the body of a multi-cell animal or plant.  The point is that the genes provide the control surface and the abstract recipe that has been used to generate the cell.   strategies into dominance and
This page reviews the inhibiting effect of the value delivery system on the expression of new phenotypic effects within an agent. 
extend phenotypic alignment
beyond the
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. 
organism
.  But when resources become scarce within a proximate niche, organisms must be ready to respond:

Hence the presence of disjoint,
The complex adaptive system (CAS) nature of a value delivery system is first introduced.  It's a network of agents acting as relays. 

The critical nature of hub agents and the difficulty of altering an aligned network is reviewed. 

The nature of and exceptional opportunities created by platforms are discussed. 

Finally an example of aligning a VDS is presented. 
environmentally
different, niches can have the effect of assisting in additional niche capture and support
This page reviews Christensen's disruption of a complex adaptive system (CAS).  The mechanism is discussed with examples from biology and business. 
disruption
of aligned
This page discusses the effect of the network on the agents participating in a complex adaptive system (CAS).  Small world and scale free networks are considered. 
networks
Operations, such as membrane, formed from a lipid (fat) bilayer which creates a barrier between aqueous (water soluble) media.  In AWF a key property of membranes - their providing a catalytic environment and supporting the suspension of enzymatically active proteins within the membrane; is simulated with a Workspace list where 'active' structures can be inserted and codelets can detect and act on the structure's active promise configured as an association in the Slipnet.   formation and tooth construction, that actively generate layered deployments of new niches, such as in coral reef formation, extend the adjacent possible by:
Environmental changes, such as the development or removal of
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. 
barriers
, transform the accessible niches.  Partitioning may induce
This page discusses the strategy of modularity in a complex adaptive system (CAS).  The benefits, mechanism and its emergence are discussed. 
modules
with separate sets of states.  In any sequence of 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. 
interactions,
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
will also ensure that the situation will evolve in a totally unique way. 

So
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
fitness is, according to Dawkins, a suitcase word with at least five meanings in biology:
  1. Darwin and Wallace thought in terms of the capacity to survive and reproduce, but they were considering discrete aspects such as chewing grass - where hard enamel would improve the relative fitness. 
  2. Population geneticists: Ronald Fisher, Sewall Wright, J.B.S. Haldane; consider selection at a locus where for a genotype: green eyes vs blue eyes; one with higher fitness can be identified from genotypic frequencies and gene frequencies, with all other variations averaged out. 
  3. Whole organism 'integrated' fitness.  Dawkins notes there is only ever one instance of a specific organism.  Being unique, comparing the relative success of its offspring makes little sense.  Over a huge number of generations the individual is likely to have provided a contribution to everyone in the pool or no one. 
  4. Inclusive fitness, where according to Hamilton, fitness depends on an organism's actions or effects on its children or its relative's children, a model where natural selection favors organs and behaviors that cause the individual's genes to be passed on.  It is easy to mistakenly count an offspring in multiple relative's fitness assessments. 
  5. Personal fitness represents the effects a person's relatives have on the individual's fitness [3].  When interpreted correctly fitness [4] and fitness [5] are the same. 
seems to depend both on the specific environmental opportunities and the specific ordered actions of the current set of adapting agents and a landscape metaphor should be used with caution.  The application of fitness functions by
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 algorithms
to
This page discusses the mechanisms and effects of emergence underpinning any complex adaptive system (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. 
emergent
The complex adaptive system (CAS) nature of a value delivery system is first introduced.  It's a network of agents acting as relays. 

The critical nature of hub agents and the difficulty of altering an aligned network is reviewed. 

The nature of and exceptional opportunities created by platforms are discussed. 

Finally an example of aligning a VDS is presented. 
environments
certainly requires careful scrutiny.  It utilizes desired target values of selected capabilities to represent fitness is, according to Dawkins, a suitcase word with at least five meanings in biology:
  1. Darwin and Wallace thought in terms of the capacity to survive and reproduce, but they were considering discrete aspects such as chewing grass - where hard enamel would improve the relative fitness. 
  2. Population geneticists: Ronald Fisher, Sewall Wright, J.B.S. Haldane; consider selection at a locus where for a genotype: green eyes vs blue eyes; one with higher fitness can be identified from genotypic frequencies and gene frequencies, with all other variations averaged out. 
  3. Whole organism 'integrated' fitness.  Dawkins notes there is only ever one instance of a specific organism.  Being unique, comparing the relative success of its offspring makes little sense.  Over a huge number of generations the individual is likely to have provided a contribution to everyone in the pool or no one. 
  4. Inclusive fitness, where according to Hamilton, fitness depends on an organism's actions or effects on its children or its relative's children, a model where natural selection favors organs and behaviors that cause the individual's genes to be passed on.  It is easy to mistakenly count an offspring in multiple relative's fitness assessments. 
  5. Personal fitness represents the effects a person's relatives have on the individual's fitness [3].  When interpreted correctly fitness [4] and fitness [5] are the same. 
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. 
Schemata
, controlling
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
which most closely meet those targets in any particular generation, are selected to develop subsequent generations based on the score of the associated agent.  Due to the testing of multiple offspring and the representation of many parts of the fitness landscape within each schematic string's component building blocks, selection will drive subsequent generations of agents to increasingly match the target capabilities, by iteratively including the most successful building blocks. 
The simple environment, provided for the
This page discusses a complex adaptive system (CAS) implementation of a genetic algorithm (GA), Melanie Mitchell's robot-janitor built as a set of Copycat codelets integrated using agent-based programming.  The improvement in the operation of the robots over succeeding generations of applying the GA is graphed. 

The CAS that generated, and operated the robot is reviewed, including the implementation details and codelet operational program flow, and the challenges and limitations of this implementation. 

The schematic strings which make up the robot's genotype, as well as the signals which are sent to the nucleus of the robot's agents so that the agents can deploy the appropriate response strings (which activate codelets) are listed.  The Slipnet configuration required by the system to associate the schematic strings with programmatic forces (codelets) is also listed.  The codelets and supporting perl are also listed. 

In the conclusion the limitations of the robot-janitor abstraction in studying emergence and creative evolution are discussed and alternative experimental frameworks are proposed.  One such, the schematic cell is the subject of a separate page in this web frame. 

virtual robot
, is changed by the agent's actions, and these changes become associated, through higher scores, with the schemata.  However, this agent does not have to cope with direct actions of competitors' in the environment. 
The
This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
evolutionary
process applied to generations of competing agents will select for optimum competitive use of accessible niches.  However, the genetic algorithm leverages the designer's choices of capabilities and target values to explore the fitness landscape.  Evolution, in contrast, must use the schematically associated collection of tools available to agents, and the evolved relationship between these and the environment that the agents exist in.  With these, evolution supports competition in indirectly forcing adjacent possibilities into becoming accessible opportunities.  Evolution's
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 operators
probe the nature of the tool set, the impact of proximate agents and the schematic representation of the environment, and are supported in the search by the
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. 
constraining
nature of the changes operators can make to the schematic strings. 

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. 
agents can successfully tie actions to schematic structures analogous to genetic algorithms when the environment is constrained and
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. 
rules
are known.  It is also important that the parallel search amplification of genetic algorithms be present. 
Evolving with an adapted environment
Early 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
)
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
would be formed from a limited
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
database.  The schematic building blocks of proteins, a relatively long chain (polymer) of peptides.  Shorter chains of peptides are termed polypeptides.   are 20 amino acids are the building blocks of proteins.  The 20 main variants differ by the nature of their side chain.  Some are positively charged, others negatively charged.  Some are water seeking while others are fat seeking.  The genetic code mapping of DNA base pair triplets thus specifies the primary sequence of amino-acids in any protein polymer. 
associated by translation is the process where messenger m-RNA is cross coded by Ribosomal agents and t-RNA into an amino-acid polymer.   with the 61 active triplets of the genetic code (DNA), a polymer composed of a chain of deoxy ribose sugars with purine or pyrimidine side chains.  DNA naturally forms into helical pairs with the side chains stacked in the center of the helix.  It is a natural form of schematic string.  The purines and pyrimidines couple so that AT and GC pairs make up the stackable items.  A code of triplets of base pairs (enabling 64 separate items to be named) has evolved which now redundantly represents each of the 20 amino-acids that are deployed into proteins, along with triplets representing the termination sequence.  Chemical modifications and histone binding (chromatin) allow cells to represent state directly on the DNA schema.  To cope with inconsistencies in the cell wide state second messenger and evolved amplification strategies are used.  
The limited set of triplets constrains mutational events to triplet deletions, triplet additions, codon, a DNA triplet that represents a specific amino-acid, or termination sequence of the genetic code.   replacements as well as missense replications.  So the mutational operator is well-defined and limited in scope. 

The 20 amino acids, deployed by the translation is the process where messenger m-RNA is cross coded by Ribosomal agents and t-RNA into an amino-acid polymer.   of the DNA (DNA), a polymer composed of a chain of deoxy ribose sugars with purine or pyrimidine side chains.  DNA naturally forms into helical pairs with the side chains stacked in the center of the helix.  It is a natural form of schematic string.  The purines and pyrimidines couple so that AT and GC pairs make up the stackable items.  A code of triplets of base pairs (enabling 64 separate items to be named) has evolved which now redundantly represents each of the 20 amino-acids that are deployed into proteins, along with triplets representing the termination sequence.  Chemical modifications and histone binding (chromatin) allow cells to represent state directly on the DNA schema.  To cope with inconsistencies in the cell wide state second messenger and evolved amplification strategies are used.   schematic string,
Rather than oppose the direct thrust of some environmental flow agents can improve their effectiveness with indirect responses.  This page explains how agents are architected to do this and discusses some examples of how it can be done. 
indirectly
associate the plan with chemical, molecules obtain chemical properties from the atoms from which they are composed and from the environment in which they exist.  Being relatively small they are subject to phenomena which move them about, inducing collisions and possibly reactions with other molecules.  AWF's Smiley simulates a chemical environment including associating the 'molecule' like strings  with codelet based forces that allow the strings to react based on their component parts, sequence etc. 
and physical
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
.   The translation process is limited to building blocks that can be directly, or indirectly specified by the schematic string, and yet it extends the forces associated with the schemata more broadly. 
The resulting polypeptide, an intermediate length amino-acid polymer.  Longer lengths are termed proteins.   chains can interact with themselves, and other instances of polypeptides, as well as other environmental structures expressing these polarity, charge, size and shape phenomena. 

The competitive development of schematically defined cooperative structures with phenotypic value such as
This page reviews the strategy of setting up an arms race.  At its core this strategy depends on being able to alter, or take advantage of an alteration in, the genome or equivalent.  The situation is illustrated with examples from biology, high tech and politics. 
substrate complementary enzyme active sites
results directly from the
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
.  Each addition of new structure potentially extended the environment and schematically reachable possibilities. 

The presence of phenomenologically active building blocks that can be built up, with incorporated free energy, and torn down, with release of energy, by agents constructed from the same building blocks supports the efficient development of platforms 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. 
, and
The complex adaptive system (CAS) nature of a value delivery system is first introduced.  It's a network of agents acting as relays. 

The critical nature of hub agents and the difficulty of altering an aligned network is reviewed. 

The nature of and exceptional opportunities created by platforms are discussed. 

Finally an example of aligning a VDS is presented. 
value chains
as described above.
Strategic clustering
Inspecting the grab bag of mechanisms and how these are deployed so creatively, in biology, to leverage specific niche opportunities gains some credence from the recurrence of
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. 
schematic goals
, such as:
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
,
This page discusses the effect of the network on the agents participating in a complex adaptive system (CAS).  Small world and scale free networks are considered. 
network effects
,
This page discusses the benefits of geographic clusters of agents and resources at the center of a complex adaptive system (CAS). 
geographic clustering
; at each level of
This page discusses the mechanisms and effects of emergence underpinning any complex adaptive system (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. 
emergent
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


While the structures,
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
and mechanisms change, the
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. 
goals
are often similar.  But the dynamics and partitioning used by real agents, challenges the scientist's techniques.  The use of computer
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 reflect
This page discusses how Smiley provides deployment guarantees to its agent-based applications. 
Smiley's transaction services are reviewed. 
The complex interactions of codelets participating in a deployment cascade are discussed including: 
  • The implementation of schematic switches. 
  • The cooperative use of goal suppression.  
  • Evaluator codelets promotion of other siblings. 
Challenges of initiation of a cascade are discussed. 
Tools to associate transaction protection to an operon deployed codelet are described. 
Special support for sub-program codelets is described.  Completion of transactional sub-programs presents special challenges.  Priority and synchronization support includes:
  • Delaying the operaton of the cascade sponsor. 
  • Delaying the notgcompleting cascade participant. 
  • Waiting for completion of parallel operations with the wait and relay service.  
The need to sustain resource pools is reviewed. 
The use of signals to coordinate siblings is described. 
The structural binding operon for the wait and relay service is included. 
The codelets and supporting functions are included.
schematic cascades
, partitioning and
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
can support the understanding of real agent's operating strategies. 
The state space of real agents is represented in the aggregate schematic structures, schematic controls and deployed infrastructure controls.  Computer programmed models demand accurate control of the state system to function at all so they can help reject impossible scenarios from the alternatives scientists are struggling to rationalize.  The performance of real agents is also typically critical so
Representing state in emergent entities is essential but difficult.  Various structures are used to enhance the rate and scope of state transitions.  Examples are discussed. 
the management of state is constrained by the requirement to respond in a timely manner
.  Additionally, real agents must
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. 
amplify significant signals
so that they ensure to transform the collective state representation of the agent. 
The presence of amplified second messengers, provide an amplified form of signals within a cell.  Since cells need to stabilize their overall state with many operations happening in parallel second messengers are useful in clarifying the signals effect.  The second messenger strategy is seen repeatedly in CAS including: neuro-transmitter guidance signals such as dopamine distribution in the brain, corporate positioning email messages in response to new situations, newspaper articles aligning the population;  provides this service.  However, it means that a specific agent must have its
Representing state in emergent entities is essential but difficult.  Various structures are used to enhance the rate and scope of state transitions.  Examples are discussed. 
deployed infrastructure pre allocated
to the required response of the initiating
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. 
signal
.  Hence multi-agent systems have a multitude of similar infrastructure, from the evolved grab bag, configured for the specific responses particular agents are responsible for.  Aggregate analysis, ignoring the distributed deployment, just ends up with a bewildering collection of similar infrastructure apparently responding to the same second messengers. 

The schematic structures operations are also likely to be far more
To benefit from shifts in the environment agents must be flexible.  Being sensitive to environmental signals agents who adjust strategic priorities can constrain their competitors. 
flexible
than initially conceived by geneticists.  Inspection of the operation of a computer program, such as the
This page describes the Adaptive Web framework (AWF) test system and the agent programming framework (Smiley) that supports its operation. 
Example test system statements are included.  To begin a test a test statement is loaded into Smiley while Smiley executes on the Perl interpreter. 
Part of Smiley's Perl code focused on setting up the infrastructure is included bellow. 
The setup includes:
  • Loading the 'Meta file' specification,
  • Initializing the Slipnet, and Workspaces and loading them
  • So that the Coderack can be called. 
The Coderack, which is the focus of a separate page of the Perl frame then schedules and runs the codelets that are invoked by the test statement structures. 
Adaptive web framework (AWF) test infrastructure
, which utilizes
This page discusses how Smiley provides deployment guarantees to its agent-based applications. 
Smiley's transaction services are reviewed. 
The complex interactions of codelets participating in a deployment cascade are discussed including: 
  • The implementation of schematic switches. 
  • The cooperative use of goal suppression.  
  • Evaluator codelets promotion of other siblings. 
Challenges of initiation of a cascade are discussed. 
Tools to associate transaction protection to an operon deployed codelet are described. 
Special support for sub-program codelets is described.  Completion of transactional sub-programs presents special challenges.  Priority and synchronization support includes:
  • Delaying the operaton of the cascade sponsor. 
  • Delaying the notgcompleting cascade participant. 
  • Waiting for completion of parallel operations with the wait and relay service.  
The need to sustain resource pools is reviewed. 
The use of signals to coordinate siblings is described. 
The structural binding operon for the wait and relay service is included. 
The codelets and supporting functions are included.
schematic cascades
, partitioning and control of flows indicates that there is little benefit to sticking with one process.  The evolutionary grab bag (epi-genetic structures represent state surfaces within cells and eggs which can be operationally modified so as to provide a heritable structure.  DNA, histones and other stable structures provide surfaces where these states may be setup.  Egg carriers are in a particularly powerful position to induce epi-genetic changes.  Sapolsky notes [childhood] events which persistently alter brain structure and behavior via epi-genetic mechanisms including: pair-bonding in prairie voles, as they first mate, is supported by changes in oxytocin & vasopressin receptor gene regulation in the nucleus accumbens. 
, proteins, a relatively long chain (polymer) of peptides.  Shorter chains of peptides are termed polypeptides.  , structural domains, evolution conserves many useful structures including DNA base sequence (content) addressable binding regions, protein active sites and signal structures which can then be reused through the mutation genetic operator. 
, 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 other active structures) will be used when there is advantage in doing so. 

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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. 
Program Management
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