Meaning
This page describes the organizational forces that limit change.  It explains how to overcome them when necessary. 

Power& tradition holding back progress
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. 
Be responsive to market dynamics
This page uses the example of HP's printer organization freeing itself from its organizational constraints to sell a printer targeted at the IBM pc user. 
The constraints are described. 
The techniques to overcome them are implied. 
Overcome reactionaries
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Meaning and consciousness

Philosophers have struggled to explain the operation of the
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. 
conscious brain
for centuries.  Different proposals including: dualism is an assumed separation of the mind and body.  It has a long history.  Descartes's Cartesian dualism assumes the mind and body are two clocks in synchrony but otherwise unrelated.  John Locke commented 'It is impossible to conceive that matter, either with or without motion, could have, originally, in and from itself, sense, perception, and knowledge; as is evident from hence, that then sense, perception, and knowledge, must be a property eternally separable from matter and every particle of it.'  Chalmers describes this explanatory gap as the hard problem of consciousness.  Damasio explains that the construction of feelings requires there be no duality, and he shows how it then emerged due to the structure of affect in humans. 
where a
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
and brain operate separately, and epiphenomenalism where mental states are just effects of operating 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. 
and have no causal relevance; all have pitfalls as effective models. 

Psychologists asked 'how does a baby bootstrap its understanding of the world so that it can rapidly learn about its physical and social environment'? 

Mathematicians, scientists and philosophers focused efforts on artificial intelligence expecting it 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. 
emerge
from work on computer systems.  The apparent optimism that such emergence must occur as the computer systems become more complex seems far-fetched. 

This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
Evolution
provides an alternative framework for supporting the emergence of meaning and
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
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. 
Read Montague explores how brains make decisions.  In particular he explains how:
  • Evolution can create indirect abstract models, such as the dopamine system, that allow
  • Life changing real-time decisions to be made, and how
  • Schematic structures provide encodings of computable control structures which operate through and on incomputable, schematically encoded, physically active structures and operationally associated production functions. 
neuron networks
representing
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. 
sensory inputs
, assumed position, potential mediated
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. 
actions
and modulating associations have
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. 
emerged
under selection pressure from the action of
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
.  The association of actions with 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. 
, emergent
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
s of goals, and strategic values; allows models and physical states to become associated.  Further the reproduction 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
ensures that the models and associations are maintained over generations of 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.  
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


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. 
Constrained interacting dynamic flows
underpin the evolutionary framework, and enable end-directedness.  Businesses emerge from the constraints and creativity of the
The specialized environment and evolution of humans on the African savanna supports the development of a new type of superOrganism.  The emergence of culture allowed human superOrganism families to accelerate the evolutionary process and apply it to memes.  This cultural superOrganism can evolve significant capabilities and attributes that can be reflected in each emergent phenotype: hunter-gatherer band, tool chain, business, state. 

cultural superOrganism


This emergent architecture is not deterministic, argues that given specific conditions a specific outcome will occur.  , so free will is the subjective assessment of one's ability to make decisions and perform independent actions.  Philosophers note that causal chains linking physical phenomena with conscious decisions would undermine the idea of independent free will.  RSS views the architecture of CAS agency as requiring indirect associations between phenomena and agent's models.  Evolution captures these associations within the genetic structures of the emergent agents, removing any epistemological or complementarity constraints.  Sapolsky concludes that this evolved agency severely limits the potential contribution of free will.   is not constrained, and there is no problem of causal closure, argues that all physical effects can be ultimately reduced to physical causes.  If this is true it is argued dualistic mental events can have no effect. 
.  The pressure on mobile agents to decide effectively in the competition for resources ensures evolution's effects.   Pre-adaptations, initially termed pre-adaptation refers to the coopting of some function for a new use.  It provides an operational phenotype with schematic access to the adjacent possible through the action of regular genetic operators. 
and adaptations 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. 
captured schematically 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
and
This page describes the consequences of the asymmetries caused by genotypic traits creating a phenotypic signal in males and selection activity in the female - sexual selection.   
The impact of this asymmetry is to create a powerful alternative to natural selection with sexual selection's leverage of positive returns.  The mechanisms are described. 
sexual
selection are enough. 

This process is summarized in our vision 'I act, therefore I think'. 
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Nature and nurture drive the business eco-system
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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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