Perception & representation
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New knowledge can emerge from representations of localized perceptions

Summary
This page discusses the interdependence of perception and representation in a 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
).  Hofstadter and Mitchell's research with Copycat is reviewed.  The bridging of a node from a network of 'well known' percepts to a new representational instance is discussed as it occurs in biochemistry, in consciousness and abstractly. 
Introduction
Competition in a
This page introduces the complex adaptive system (CAS) theory frame.  The theory provides an organizing framework that is used by 'life.'  It can be used to evaluate and rank models that claim to describe our perceived reality.  It catalogs the laws and strategies which underpin the operation of systems that are based on the interaction of emergent agents.  It highlights the constraints that shape CAS and so predicts their form.  A proposal that does not conform is wrong. 

John Holland's framework for representing complexity is outlined.  Links to other key aspects of CAS theory discussed at the site are presented. 
complex adaptive system
(CAS) can take many forms.  But each of the forms
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. 
emerges
from the actions of an
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
.  One major challenge is to be able to respond to a limited number 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. 
signals
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. 
flexibly
and effectively by correctly identifying the appropriate situation from a potentially wide variety. 

Agents are sensitive to particular signals.  The detection of a specific signal results from a sensitive agent interacting with the signal.  Some agents perform
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. 
modeling
of the signal.  The model could be as simple as checking a value of the signal and responding with one of two outputs. 

While some agents aggregate to better cope with the signals they must act on, others remain focused on some simple aspect of the overall situation, relying on prior selection pressure to improve the likelihood that the situation they depend on recurs frequently.  Aggregation is when a number of actions become coordinated and operate together.  In the adaptive web framework's Smiley, codelets become coordinated by their relative position in the deployment cascade.  The cascade's dynamics are dependent on the situation, the operating codelets responses to that situation and the grouping of schematic strings they are associated with.  The aggregate effect is a phenotype the adaptive agent. 
allows for parallel processing of complex, rapidly changing inputs exemplified by visual processing is the main part of the cerebral cortex in mammals.  It was originally thought to exist only in mammals but is also present in reptiles and birds buried behind other areas of the for-brain.  The for-brain develops based on a genetic plan consistent across all vertebrates.  The neocortex processes vision in the visual hierarchy V1, V2, V3 .. V5 ... V20; and language with areas including Wernicke's and Broca's with sensors in the inner ear.  Primate species with bigger social groups have larger cortices.  Human cortex size suggests traditional human cultures had an average size of 150 people. 
.  Aggregation enables the complex changing state of the environment to be represented within the
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
of components of the aggregate.  However, it requires organization - self-organization. 

Construction destruction regrouping and rearrangement
Douglas Hofstadter writes that the perceptual process 'is essentially one of constructing larger units out of smaller ones, with temporary structures at various levels and permanent mental categories trying to accommodate each other.  ' .... 'In any type of perception, much back-and-forth motion must occur -- that is, an intimate mixture of construction, destruction, regrouping, and rearrangement of tentative structures.  Any architecture for a system to carry out this type of process is the result of many subtle decisions integrates situational context, state and signals to prioritize among strategies and respond in a timely manner.  It occurs in all animals, including us and our organizations: 
  • Individual human decision making includes conscious and unconscious aspects.  Situational context is highly influential: supplying meaning to our general mechanisms, & for robots too.  Emotions are important in providing a balanced judgement.  The adaptive unconscious interprets percepts quickly supporting 'fast' decision making.  Conscious decision making, supported by the: DLPFC, vmPFC and limbic system; can use slower autonomy.  The amygdala, during unsettling or uncertain social situations, signals the decision making regions of the frontal lobe, including the orbitofrontal cortex.  The BLA supports rejecting unacceptable offers.  Moral decisions are influenced by a moral decision switch.  Sleeping before making an important decision is useful in obtaining the support of the unconscious in developing a preference.  Word framing demonstrates the limitations of our fast intuitive decision making processes.  And prior positive associations detected by the hippocampus, can be reactivated with the support of the striatum linking it to the memory of a reward, inducing a bias into our choices.  Prior to the development of the PFC, the ventral striatum supports adolescent decision making.  Neurons involved in decision making in the association areas of the cortex are active for much longer than neurons participating in the sensory areas of the cortex.  This allows them to link perceptions with a provisional action plan.  Association neurons can track probabilities connected to a choice.  As evidence is accumulated and a threshold is reached a choice is made, making fast thinking highly adaptive.  Diseases including: schizophrenia and anorexia; highlight aspects of human decision making. 
  • Organisations often struggle to balance top down and distributed decision making: parliamentry government must use a process, health care is attempting to improve the process: checklists, end-to-end care; and include more participants, but has systemic issues, business leaders struggle with strategy. 
about how independent processes should interact, how structures should be put together or broken apart, what kinds of things form stable structures, what easy ways are of making new possible structures when old ones are seen to be inadequate, and so on.'  Hofstadter outlined such an architecture which he called Copycat. 

Hofstadter and Mitchell's Copycat Architecture
Hofstadter and Mitchell review the Copycat Project and its architecture in chapter 5 of Fluid Concepts and Creative Analogies.  What follows is a brief overview of the major components extracted from their detailed discussion. 

They write 'there are three major components to the architecture: the Slipnet, the Workspace, and the Coderack.  In very quick strokes, they can be described as follows. (1) The Slipnet is the site of all permanent Platonic concepts.  It can be thought of, roughly, as Copycat's long-term memory.  As such, it contains only concept types, and no instances of them.  The distances between concepts in the Slipnet can change over the course of a run, and it is these distances that determine, at any given moment, what slippages are likely and unlikely.  (2) The Workspace is the locus of perceptual activity.  As such, it contains instances of various concepts from the Slipnet, combined into temporary perceptual structures (e.g., raw letters, descriptions, bonds, groups, and bridges).  It can be thought of, roughly, as Copycat's short-term memory or working memory, and resembles the global "blackboard" data-structure of Hearsay II.  (3) Finally, the Coderack can be thought of as a "stochastic waiting room", in which small agents that wish to carry out tasks in the Workspace wait to be called.  It has no close counterpart in other architectures, but one can liken it somewhat to an agenda (a queue containing tasks to be executed in a specific order).  The critical difference is that agents are selected stochastically from the Coderack, rather than in a determinate order'. 

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. 
Genetic and Memetic
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
must respond to signals, 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. 
from their environment. 

The
In this page we:
  • Introduce some current problems of complexity for humanity
  • Explain how to use the site. 
There are two main starting points:
  1. The example systems frame and
  2. The presentation frame. 
  3. And then there is how we use the site. 
The site uses lots of click through.  That's so that you can see the underlying principles that are contributing to the system being discussed.  We hope that as you internalize and reflect on the principles the system should appear in a new light.  At this site clicking is good!
opportunities frame
includes a
Consciousness is no longer mysterious.  In this page we use complex adaptive system (CAS) theory to describe the high-level architecture of consciousness, linking sensory networks, low level feelings and genetically conserved and deployed neural structures into a high level scheduler.  Consciousness is evolution's solution to the complex problems of effective, emergent, multi-cellular perception based strategy.  Constrained by emergence and needing to avoid the epistemological problem of starting with a blank slate with every birth, evolution was limited in its options. 

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

And we discuss the implications with regard to artificial intelligence, sentient robots, augmented intelligence, and aspects of philosophy. 
discussion
of how the brain includes a Slipnet of genetically specified structures: amygdala contains > 12 distinct areas: Central, Lateral.  It receives simple signals from the lower parts of the brain: pain from the PAG; and abstract complex information from the highest areas: Disgust, heart rate, and suffering from the insula cortex, allowing it to orchestrate emotion.  It connects strongly to attention focusing networks.  It sends signals to almost every other part of the brain, including to the decision making circuitry of the frontal lobes.  It has high levels of D(1) dopamine receptors.  During extreme fear the amygdala drives the hippocampus into fear learning.  It outputs directly to subcortical reflexive motor pathways when speed is required.  Its central nucleus projects to the BNST.  It signals the locus ceruleus.  It directly signals area 25.  The amygdala:
  • Promotes aggression.  Stimulating the amygdala promotes rage.  It converts anger into aggression and when impaired it impacts the ability to detect angry facial expressions.  
  • Participates in disgust
  • Perceives fear promoting stimuli, focusing our attention on these.  In PTSD sufferers the Amygdala overreacts to mildly fearful stimuli and is slow to calm down and the amygdala expands in size over a period of months.  Fear is processed by the lateral nucleus which serves as the input from various senses, and the central nucleus which outputs to the brain stem (central grey - freezing, lateral hypothalamus - blood pressure, activates paraventricular hypothalamus => crf -> hormone adjustments). 
  • Has lots of receptors for and is highly sensitive to glucocorticoids.  Stress inhibits the GABA interneurons in the basolateral amygdala (BLA) allowing the excitatory glutamate releasing neurons to excite more. 
  • Is sensitive to unsettling/uncertain social situations where it promotes anxiety and makes us distracted.  It is also interested in uncertain but potentially painful situations.  The amygdala contributes to social and emotional decision making where the BLA supports rejecting an unacceptable offer, as allowed in the Ultimatum Game, by injecting implicit mistrust and vigilance, generating an anger driven rejection that is used as punishment.  The amygdala is very rapidly excited by subliminal signals from the thalamus of outgroup skin color.  The amygdala subsequently tips social emotions against outgroups unless restrained by the frontal lobe or influenced by subliminal priming to prioritize inclusion.  The fast path from the thalamus rapidly but inaccurately signals its identified a weapon. 
  • Sees suffering of others as increasingly salient with loving-kindness meditation practice, Goleman & Davidson explain. 
  • Promotes male, but not female, sexual motivation when it is an uncertain potential pleasure. 
  • Responds to the longing for uncertain potential pleasures and fear that the reward will not be worth it if it happens.  The amygdala turns off during orgasm. 
  • Uses but is not directly involved in vision.  
, insula is part of the cerebral cortex folded deep within the lateral sulcus.  It includes: anterior, posterior insula; and is overlaid by the operculum.  Kandel notes the anterior insula is where feelings are calibrated by evaluating and integrating the importance of the stimuli.  It directly signals area 25.  LeDoux showed there are two routes for signals of feelings and emotions to the amygdala: a fast unconscious one and a slow one that involves the anterior insula.  So the insula is assumed to participate in consciousness where it has been linked to emotion, salience & body homeostasis functions:
  • Perception,
  • Motor control: Hand-&-eye motor movement, Swallowing, Gastric motility, Speech articulation;
  • Self-awareness,
  • Inter-personal experiences: Disgust at smells, contamination & mutilation which generate visceral responses, that are projected to the amygdala; binding physical and moral aspects of purity (Macbeth effect)
    • Suffering of others can be projected by the insula to the amygdala and made increasingly salient with loving-kindness meditation practice, Goleman & Davidson explain. 
  • Homeostatic regulation of the sympathetic network, parasympathetic network, and immune system.  Heart rate and sweat gland activity are monitored.   When the amygdala signals concern, the insula prepares the body for action, increasing blood flow to the muscles etc.
; and a Workspace where representations are built from new, but well known, cells of the hippocampus is a part of the medial temporal lobe of the brain involved in the temporary storage or coding of long-term episodic memory.  It includes the dentate gyrus.  Memory formation in the cells of the hippocampus uses the MAP kinase signalling network which is impacted by sleep deprivation.  The hippocampus dependent memory system is directly affected by cholinergic changes throughout the wake-sleep cycle.  Increased acetylcholine during REM sleep promotes information attained during wakefulness to be stored in the hippocampus by suppressing previous excitatory connections while facilitating encoding without interference from previously stored information.  During slow-wave sleep low levels of acetylcholine cause the release of the suppression and allow for spontaneous recovery of hippocampal neurons resulting in memory consolidation.  It was initially associated with memory formation by McGill University's Dr. Brenda Milner, via studies of 'HM' Henry Molaison, whose medial temporal lobes had been surgically destroyed leaving him unable to create new explicit memories.  The size of neurons' dendritic trees expands and contracts over a female rat's ovulatory cycle, with the peak in size and cognitive skills at the estrogen high point.  Adult neurogenesis occurs in the hippocampus (3% of neurons are replaced each month) where the new neurons integrate into preexisting circuits.  It is enhanced by learning, exercise, estrogen, antidepressants, environmental enrichment, and brain injury and inhibited by various stressors explains Sapolsky.  Prolonged stress makes the hippocampus atrophy.  He notes the new neurons are essential for integrating new information into preexisting schemas -- learning that two things you thought were the same are actually different.  Specific cells within the hippocampus and its gateway, the entorhinal cortex, are compromised by Alzheimer's disease.  It directly signals area 25. 
and olfactory bulb. 
Consciousness has confounded philosophers and scientists for centuries.  Now it is finally being characterized scientifically.  That required a transformation of approach. 
Realizing that consciousness was ill-defined neuroscientist Stanislas Dehaene and others characterized and focused on conscious access. 
In the book he outlines the limitations of previous psychological dogma.  Instead his use of subjective assessments opened the window to contrast totally unconscious brain activity with those including consciousness. 
He describes the research methods.  He explains the contribution of new sensors and probes that allowed the psychological findings to be correlated, and causally related to specific neural activity. 
He describes the theory of the brain he uses, the 'global neuronal workspace' to position all the experimental details into a whole. 
He reviews how both theory and practice support diagnosis and treatment of real world mental illnesses. 
The implications of Dehaene's findings for subsequent consciousness research are outlined. 
Complex adaptive system (CAS) models of the brain's development and operation introduce constraints which are discussed. 

Access to consciousness
initiates the bridging of the Workspace representation to the salient, Douglas Hofstadter controlled the amount of attention a Workspace object in Copycat would receive from codelets via its salience.  The more descriptions, analogous to geons, an object has and the more highly activated the nodes involved therein, the more important the object is.  Modulating this tendency is any relative lack of connections from the object to the rest of the objects in the Workspace.  Salience is a dynamic number that takes into account both these factors.  In Smiley the instantaneous salience of a Workspace's objects is calculated by itsalience.  In the brain salience is modeled by the salience networks. 
Slipnet node.  In the case of a fearful is an emotion which prepares the body for time sensitive action: Blood is sent to the muscles from the gut and skin, Adrenalin is released stimulating: Fuel to be released from the liver, Blood is encouraged to clot, and Face is wide-eyed and fearful.  The short-term high priority goal, experienced as a sense of urgency, is to flee, fight or deflect the danger.  There are both 'innate' - really high priority learning - which are mediated by the central amygdala and learned fears which are mediated by the BLA which learns to fear a stimulus and then signals the central amygdala.  Tara Brach notes we experience fear as a painfully constricted throat, chest and belly, and racing heart.  The mind can build stories of the future which include fearful situations making us anxious about current ideas and actions that we associate with the potential future scenario.  And it can associate traumatic events from early childhood with our being at fault.  Consequent assumptions of our being unworthy can result in shame and fear of losing friendships.  The mechanism for human fear was significantly evolved to protect us in the African savanna.  This does not align perfectly with our needs in current environments: U.S. Grant was unusually un-afraid of the noise or risk of guns and trusted his horses' judgment, which mostly benefited his agency as a modern soldier. 
percept the amygdala's axon's synaptic, a neuron structure which provides a junction with other neurons.  It generates signal molecules, either excitatory or inhibitory, which are kept in vesicles until the synapse is stimulated when the signal molecules are released across the synaptic cleft from the neuron.  The provisioning of synapses is under genetic control and is part of long term memory formation as identified by Eric Kandel.  Modulation signals (from slow receptors) initiate the synaptic strengthening which occurs in memory. 
connections to the new representation are strengthened. 
Consciousness is no longer mysterious.  In this page we use complex adaptive system (CAS) theory to describe the high-level architecture of consciousness, linking sensory networks, low level feelings and genetically conserved and deployed neural structures into a high level scheduler.  Consciousness is evolution's solution to the complex problems of effective, emergent, multi-cellular perception based strategy.  Constrained by emergence and needing to avoid the epistemological problem of starting with a blank slate with every birth, evolution was limited in its options. 

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

And we discuss the implications with regard to artificial intelligence, sentient robots, augmented intelligence, and aspects of philosophy. 
Consciousness
now has an appropriate viewer 'who' can subjectively perceive the scene and take action. 

The
This page introduces the programs that the Adaptive Web Framework (AWF) develops and uses to deploy Rob's Strategy Studio (RSS). 
The programs are structured to obey complex adaptive system (CAS) principles.  That allows AWF to experiment and examine the effects. 
A production program generates the web pages. 
A testing system tests the production program.  It uses a framework to support the test programs.  This is AWF's agent programming framework as described in the agent-based programming presentation. 
An example of the other AWF agent-based programs that are also described in the frame is the virtual robot. 
Finally a strength, weaknesses, opportunities and threats assessment is presented. 
Perl frame
includes a Copycat like framework (
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. 
Smiley
) for integrating perceptions and representations.  It includes implementations of the three inter-dependent aspects of Copycat: the
This page describes the Copycat Coderack. 
The details of the codelet architecture are described. 
The specialized use of the Coderack by the adaptive web framework's (AWF) Smiley is discussed. 
The codelet scheduling mechanism is discussed. 
A variety of Smiley extensions to the Coderack are reviewed. 
The Coderack infrastructure functions are included. 
Coderack
,
This page describes the Copycat Workspace. 
The specialized use of the Workspace by the adaptive web framework's (AWF) Smiley is discussed. 
How text and XML are imported into the Smiley Workspace is described. 
Telomeric aging of schematic structures is introduced. 
The internal data structure used to represent the state of each workspace object is included. 
The Workspace infrastructure functions are included. 
Workspace
and
This page describes the Copycat Slipnet. 
The goal of the Slipnet is reviewed. 
Smiley's specialized use of the Slipnet is introduced. 
The initial Slipnet network used by the 'Merge Streams' and 'Virtual Robot' agent-based applications is setup in initchemistry and is included. 
The Slipnet infrastructure and initialization functions are included. 
Slipnet
; which support the emergence of codelet based CAS agents. 

Copycat supports emergence of aggregate schematic agents
A concrete example of a
The agents in complex adaptive systems (CAS) must model their environment to respond effectively to it.  Evolution's schematic operators and Samuel modeling together support the indirect recording of past successes and their strategic use by the current agent to learn how to succeed in the proximate environment. 
model
, from the Perl frame, is the mgpart codelet which is an example of a modeling codelet which checks a specific part of a test statement has attributes that reach a threshold used to indicate the part is whole.  The general point is the model can be anything which can induce a differential output. 

The output of the modeling is reflected in other
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. 
signals
issued by the modeling codelet.  Other codelets may respond to the initial signals, or the output of the models or both, initiating some action.  Due to the modeling a variety of potential actions becomes associated with the original signal and current local environmental state.  The different actions correspond to differences in the benefit generated. 

The codelets can be
This page describes the adaptive web framework (AWF) Smiley agent progamming infrastructure's codelet based Copycat grouping operation. 
The requirements needed for a group to complete are described. 
The association of group completion with a Slipnet defined operon is described.  Either actions or signals result from the association. 
How a generated signal is transported to the nucleus of the cell and matched with an operon is described. 
A match with an operon can result in deployment of a schematic string to the original Workspace.  But eventually the deployed string will be destroyed. 
Smiley infrastructure amplification of the group completion operation is introduced.  This includes facilities to inhibit crowding out of offspring. 
A test file awfart04 is included. 
The group codelet and supporting functions are included. 
associated
with schematic structures in the
This page describes the Copycat Workspace. 
The specialized use of the Workspace by the adaptive web framework's (AWF) Smiley is discussed. 
How text and XML are imported into the Smiley Workspace is described. 
Telomeric aging of schematic structures is introduced. 
The internal data structure used to represent the state of each workspace object is included. 
The Workspace infrastructure functions are included. 
Workspace
.  Since codelet's actions vary depending on the state of the local Workspace particular associated representations become influences of the codelet's actions.  With
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. 
reproduction of the Workspace structures selecting for valued actions
, the Workspace structures become
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 plans
.  A higher level modeling system appears based on the interactions, and a true
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. 
agent
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. 
emerges
from the interplay of
This page describes the Copycat Slipnet. 
The goal of the Slipnet is reviewed. 
Smiley's specialized use of the Slipnet is introduced. 
The initial Slipnet network used by the 'Merge Streams' and 'Virtual Robot' agent-based applications is setup in initchemistry and is included. 
The Slipnet infrastructure and initialization functions are included. 
Slipnet
, Workspace structures and codelets. 

Agents select different actions due to differences in the local environment and the chance encountering of signals.  Certain of the agent's selections may be relatively advantageous. 

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 structures
are essentially sequences of signals which the agents detect and respond to.  The inclusion of these schemata both expands the local environment of the agents and shapes and constrains it. 

The alteration of schematic structures to record the results of the models and actions allows a direct integration of the agent's plan, its actions and its state.  The changes to the schemata can be targeted to particular labeled regions.  Such changes can affect the schematic signals the agent detects and responds too.  CAS agents naturally utilize
Walter Shewhart's iterative development process is found in many complex adaptive systems (CAS).  The mechanism is reviewed and its value in coping with random events is explained. 
Shewhart cycles


Schematic strings are also easy to copy, and can be subject to
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
.  Alternative strategies correspond to alternative sets of schematic strings.  The resulting
This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
evolutionary pressures
will alter the mix of replicators is Richard Dawkin's name for the genotype since it has the evolutionary goal of surviving long enough to reproduce its schematic plan effectively.  The action of genetic operators means that the results of successful reproduction may be different to the parental genotypes and phenotypes (Dawkin's vehicle). 
available for 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 implementation of the future plans specifying the models and actions that drive the agents. 

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 action plans
may then result in alternative structures corresponding to new knowledge. 

Schematic agents can aggregate into perception and representation structures
More complex signals, such as those captured by the primate visual system supports processing of visual data into what and how.  To do this it has two distinct paths: The ventral path and the dorsal path. 
, have highly parallel aspects which are initially captured by
This page describes a schematic system about abstracted neurons operating in a circuit. 
The neuronal system was designed to focus in on the cellular nature of a schematically defined neuron. 
The goals include:
  • Development of a system of cells, their differentiation and deployment into a neuron network. 
  • Abstract receptor operation must support interactions of a network of neurons and attached cells. 
THE IMPLEMENTATION IS INCOMPLETE AND ONGOING. 
The codelets and infrastructure are included. 
arrays of photo-receptors and then neuronal state
.  Having layers of interconnected neurons, specialized eukaryotic cells include channels which control flows of sodium and potassium ions across the massively extended cell membrane supporting an electro-chemical wave which is then converted into an outgoing chemical signal transmission from synapses which target nearby neuron or muscle cell receptors.  Neurons are supported by glial cells.  Neurons include a:
  • Receptive element - dendrites
  • Transmitting element - axon and synaptic terminals.  The axon may be myelinated, focusing the signals through synaptic transmission, or unmyelinated - where crosstalk is leveraged. 
  • Highly variable DNA schema using transposons. 
allows for the signals to be deconstructed and aggregated.  Neuronal networks, a network of interconnected neurons which perform signalling, modeling and control functions.  In Cajal's basic neural circuits the signalling is unidirectional.  He identified three classes of neurons in the circuits:
  • Sensory, Interneurons, Motor; which are biochemically distinct and suffer different disease states. 
and body cells become cooperating agents able to process signals,
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. 
represent shared state
, and issue signals.  As Hofstadter described above multiple structures, each represented by inter neuron, specialized eukaryotic cells include channels which control flows of sodium and potassium ions across the massively extended cell membrane supporting an electro-chemical wave which is then converted into an outgoing chemical signal transmission from synapses which target nearby neuron or muscle cell receptors.  Neurons are supported by glial cells.  Neurons include a:
  • Receptive element - dendrites
  • Transmitting element - axon and synaptic terminals.  The axon may be myelinated, focusing the signals through synaptic transmission, or unmyelinated - where crosstalk is leveraged. 
  • Highly variable DNA schema using transposons. 
synaptic, a neuron structure which provides a junction with other neurons.  It generates signal molecules, either excitatory or inhibitory, which are kept in vesicles until the synapse is stimulated when the signal molecules are released across the synaptic cleft from the neuron.  The provisioning of synapses is under genetic control and is part of long term memory formation as identified by Eric Kandel.  Modulation signals (from slow receptors) initiate the synaptic strengthening which occurs in memory. 
growth, are built in parallel by neuron agents adapting to the stream of signals from the sensors and each other.  Schematic plans specify the pre-deployment of valuable neuron network agents and associated body cells. 

Bodies, capable of executing actions for neuron network agents, demand significant supplies of resources.  Emergent infrastructure supports the deployment and operation of the neuron network and body cell agents.  Additional leverage from the emergent formation of
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
enhances the operational benefits of the system, but requires regulation to limit positive returns, W. Brian Arthur's conception of how high tech products have positive economic feedback as they deploy.  Classical products such as foods have negative returns to scale since they take increasing amounts of land, and distribution infrastructure to support getting them to market.  High tech products typically become easier to produce or gain from platform and network effects of being connected together overcoming the negative effects of scale. 
effects of the amplifiers. 

Competitive parasitic is a long term relationship between the parasite and its host where the resources of the host are utilized by the parasite without reciprocity.  Often parasites include schematic adaptations allowing the parasite to use the hosts modeling and control systems to divert resources to them or improve their chance of reproduction: Toxoplasma gondii.   strategies can subsequently target the model and regulatory environment to leverage the infrastructure and control systems while avoiding the costs involved in developing and operating a perception and representation infrastructure. 






























































Market Centric Workshops
The Physics - Politics, Economics & Evolutionary Psychology
Politics, Economics & Evolutionary Psychology

Business Physics
Nature and nurture drive the business eco-system
Human nature
Emerging structure and dynamic forces of adaptation


integrating quality appropriate for each market
 
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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