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In this page we:
- Introduce some current
problems of complexity for humanity
- Explain how to use
the site.
There are two main starting points:
- The example systems
frame and
- The presentation
frame.
- 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 |
This web page reviews persistent business challenges with
complex adaptive system (CAS)
theory.
Exploring opportunities |
Dark webs can enhance
individual creativity, local operational autonomy, enterprise
strategic alignment and organizational learning. In this
page we summarize the opportunity.
Dark webs |
The productivity of
complex adaptive system (CAS) is reviewed highlighting the most
significant variables: access to raw
materials, agency based leverage of additional wage
laborers/consumers to build a SuperOrganism during
cliodynamic up-cycles, wealth
amplifying infrastructure build-out,
trading
network time capture offset by instability of amplifier
driven bubbles requiring strategic management and extended
phenotypic alignment and disruption; when they expand markets
for goods & services. The CAS and classical economic
approaches are compared.
Important CAS aspects are highlighted:
- CAS reflect the history of
all the events of the network of agents and their environment
- The relevant economic
history is reviewed demonstrating the contribution of
power, politics, war...
- Chemical
structures capture and preserve important recipes that
allow agents to increase search/operational effectiveness
and wealth & the
system to be robust
- Environment matched
to system strategy: Superorganism
and beetle
- Cliodynamic models of historical agent networks allows a
realistic assessment
of productivity over a full network cycle
- The models must be matched
to the proximate environment
- Internal failures
of the agent network
- Existential
threats to the agent network
Human agents must dedicate: focus, time,
coherence and skills; to productively generate wealth. And they could
do much more - learning to develop
and use formal schematic plans
during their education, and using the skill when participating
in a superorganism.
CAS level
productivity improvements are due to:
- Collective solidarity ensures evolved amplifiers are fully
expressed
- Valuable schematically defined, emergent actions must be
accessible to resource controlling and allocating schemata
and their agents
- Meta ideas that can be reused and recombined
- Distribution of these ideas allow parallel searching
- Trading to gain time
- Isolated agents can be integrated into the current network
during each growth phase, but cliodynamic assessments show
agents are dropped again from the network during the decline
phase of the cycle
- Network
effects and leverage of power drive productivity
improvements.
Human agent level productivity
- Agent level productivity
improvements of significance
- More time: Increased light,
reduced moving & travelling, quicker & better
eating, reduced rework, motivated & effective
- Broader utilization with adoption of standards &
undermining of monopoly
constraints
- Weapons & armor
- Power available: Driving
flows &
actions in required direction
- Iterative theory & practice
- Infrastructure & tools: catalytic
reduction in cost of repeated operations
- Agent level productivity improvements of
limited effect
Productivity of CAS |
Representative democracy's robustness is dependent on emotional
and cultural
aspects of humanity. The impact of YouTube's
recommendation engine on the adolescent mind has
undermined the genetic
operators provided by culture. Typical parental constraints on
the associations allowed to adolescents are undermined and
emotional links are built to the most emotive ideas, based
simply on their capacity to sustain attention to YouTube.
An outline
mechanism is described that reintroduces 'parental'
constraints. Legislative enforcement of the capability is
required.
Details of the theoretical complex adaptive system (CAS)
requirements of genetic operations are introduced. The
minds implementation of the schematic operators is
explained. Traditional cultural constraints limiting large
changes in the schema base are outlined.
Aligning YouTube & democracy |
Organizations can benefit from understanding and leveraging
creativity. In this page we review what creativity is,
highlight the
opportunity - including when it is
appropriate to apply, how to do
that organizationally, and when it might
be avoided, and the challenges with
enabling it when it is desirable.
We introduce the aspects of the creative process.
Leveraging creativity |
Graziano's consciousness |
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.
On the nature of conscious things |
John Searle's influential thought experiment implied to him that
computers cannot understand. Complex adaptive system (CAS) theory indicates that this is
not the case.
Understanding the Chinese room |
In his talk 'The Science of Ending Aging' Aubrey de Grey argues
we should invest more in maintenance of our bodies. In
this page we summarize his video comments and then use complex
adaptive system (CAS) theory to
review his arguments. Focusing the lens of CAS theory and
mechanisms of emergence on the system we highlight the pros and
cons of ending aging.
Ending aging |
The essence of
a library complex adaptive system (CAS) is defined.
Implications
for the future development of contemporary libraries
are reviewed.
Libraries evolving |
This web page reviews opportunities to benefit from modeling
agent based flows using complex adaptive system (CAS) theory.
Agent based flows |
This web page reviews opportunities to find and capture new
niches, based on studying fitness landscapes using complex
adaptive system (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.
Fitness landscapes |
This web page reviews opportunities to enhance computing theory
and practice by using biological mechanisms and complex adaptive
system (CAS) theory.
Biologically inspired computing |
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Michael Graziano's consciousness
Summary
In Gray Matter Michael Graziano asks Are we Really
Conscious? He argues that we build inaccurate models of
reality and then develop intuitions based on these problematic
models. He concludes we can't use intuitions to understand
consciousness. Instead he promotes 'brain science' as more
accurate and argues it suggests we are not conscious. In
this page we summarize his article and then use 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 to review his
arguments. Constrained by CAS theory and mechanisms of
emergence we see a requirement for consciousness.
Introduction
The psychologist Michael Graziano argues in Are
We Really Conscious? that we must shift our view of
consciousness from credulous and egocentric to a skeptical and
slightly discriminating one with respect to intuition. He
is exploring the relationship between our minds and the physical
world. He asserts that we don't actually have inner feelings are subjective models: sad, glad, mad, scared, surprised, and compassionate; of the organism and its proximate environment, including ratings of situations signalled by broadly distributed chemicals and neural circuits. These feelings become highly salient inputs, evolutionarily associated, to higher level emotions encoded in neural circuits: amygdala, and insula. Deacon shows James' conception of feeling can build sentience. Damasio, similarly, asserts feelings reveal to the conscious mind the subjective status of life: good, bad, in between; within a higher organism. They especially indicate the affective situation within the old interior world of the viscera located in the abdomen, thorax and thick of the skin - so smiling makes one feel happy; but augmented with the reports from the situation of the new interior world of voluntary muscles. Repeated experiences build intermediate narratives, in the mind, which reduce the salience. Damasio concludes feelings relate closely and consistently with homeostasis, acting as its mental deputies once organisms developed 'nervous systems' about 600 million years ago, and building on the precursor regulatory devices supplied by evolution to social insects and prokaryotes and leveraging analogous dynamic constraints. Damasio suggests feelings contribute to the development of culture: - 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
in the way most
of us think we do.
He notes that the brain builds models about items in the world
and that the models are often not very accurate. This is a
significant facet of Patricia Churchland and Daniel Dennett's
philosophy of consciousness and with the conclusions of
Graziano's research suggests the brain doesn't become
subjectively aware of the real world information even though it
thinks it does!
Graziano proposes an attention schema theory of
consciousness. In this:
Graziano argues the brain is not subjectively aware of
information because:
- Historically we concluded there was high level
subjectivity based on introspection. But introspection
is accessing internal mental models and the models are
flawed.
- There is just a data processing device which leaves no
room for subjective impression.
- While it might seem unlikely a brain without the property
of subjective impression would waste energy computing models
of subjective awareness and attribute that property to
itself Graziano says that is so. Graziano's research
framed by the attention schema of consciousness identifies
an alternative explanation for the value of subjective
models.
- He asserts:
- The brain needs an approximate model of attention to be
able to control the item of attention efficiently.
- To predict the behavior of other creatures, the brain
needs to model their brain states including their
attention.
- Attention schema theory pulls together evidence from
social neuroscience, attention research, control theory and
elsewhere. Almost all other theories of consciousness
are rooted in our intuitions about awareness which depend on
the brain's models which are caricatures of
reality.
Graziano concludes attention really exists and awareness is just
a distorted accounting of it.
When using 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) theory to analyze Graziano's article it appears:
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 introduces a set of
constraints which apply to humans, their brains and all the
other organs, and the cells and chemicals from which they
are constructed. An emergent hierarchy 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. obeying This page discusses the physical foundations of complex adaptive
systems (CAS). A small set of
rules is obeyed. New [epi]phenomena then emerge. Examples are
discussed.
physical rules and constraints
support the development of emergent
phenomena encapsulating additional rules at each
higher emergent level. At each higher level the
apparent operation of lower level supporting phenomena is
typically an approximation at best. But the
approximations benefit to the maintenance of the emergent
phenomena is real. The key point is that an emergent
event always results in emergent approximate models of
reality that help sustain the emergence.
- 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.
agents must start out
with a very poor understanding of the physical world in
which they exist. This is true for both:
- Science follows emergence, and
This page reviews the implications of selection, variation and
heredity in a complex adaptive system (CAS).
The mechanism and its emergence are
discussed.
evolution
in testing
out hypothesis of what is happening in the real
world. Science and evolution record the strategies for
testing the hypothesis and hence build iteratively better
hypothetical models of reality based on prioritizing highly
the successful strategies. But evolution's competitive
mechanism is relative. The one-eyed are major sensors in primates, based on opsins deployed in the retina & especially fovea, signalling the visual system: Superior colliculi, Thalamus (LGN), Primary visual cortex; and indirectly the amygdala. They also signal [social] emotional state to other people. And they have implicit censorious power with pictures of eyes encouraging people within their view to act more honorably. Eyes are poor scanners and use a saccade to present detail slowly to the fovea. The eye's optical structures and retina are supported by RPE. Eyes do not connect to the brain through the brain stem and so still operate in locked-in syndrome. Evo-devo shows eyes have deep homology. High pressure within the eye can result in glaucoma. Genetic inheritance can result in retinoblastoma. Age is associated with AMD. man is king in the
land of the blind. Evolved models of reality only need
to be good enough to ensure reproductive success. And
in our Russ Abbott explores the impact on science of epiphenomena and
the emergence of agents.
emergent layered world it
is likely that the scientific models are also just useful
approximations of the underlying physical phenomena.
- When rapid response is important for survival evolution
can support the emergent 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.
of plan-ahead serial
buffers which support the representation 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.
- The architecture of emergent agents is recursive.
Grasiano notes that the high level human is just a data
processing device. The 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
architecture allows evolution to gather together useful
algorithms that encode how to construct and then
execute. It can provide a vast variety 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.
sensors, signals, 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.
channels and controls, structural
members, and Plans emerge in complex adaptive
systems (CAS) to provide the
instructions that agents use to
perform actions. The component architecture and structure
of the plans is reviewed.
planning fragments.
Its programs are developed emergently and are This web page reviews opportunities to enhance computing theory
and practice by using biological mechanisms and complex adaptive
system (CAS) theory.
highly robust unlike the Von Neumann, John was a brilliant Hungarian mathematician who published the earliest paper specifying architecture for digital computing. It ensured this computing architecture was not patentable. The architecture has a central processing unit (CPU), random access storage addressable by the CPU and a sequencer. The architecture encourages a serial software architecture that matches the logic of the sequencer and processing operations on program and data. Von Neumann, his history, computing architecture and some alternative architectures are reviewed by Melanie Mitchell. data
processing architecture.
- In each agent, at whatever layer of the CAS hierarchy,
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.
state must be represented.
This must be sophisticated enough to allow both
bootstrapping from a 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.
single cell,
and representation of the local environment that the agent
is operating in. That must mean that there are
mechanisms retained to both:
- Work bottom up based on the controlled state provided at
conception.
- Work top down evaluating sensed streams of data from the
detectable epiphenomena
modelled by the agent sensors and deciding on the priority
of building alternative infrastructure to effectively cope
with the local environment.
- One method of deploying cooperating sets of agents is to
separate into a
This page discusses the interdependence of perception and
representation in a complex adaptive system (CAS). Hofstadter
and Mitchell's research with Copycat is
reviewed. The bridging of a node from a network of 'well
known' percepts to a new representational instance is discussed
as it occurs in biochemistry, in consciousness and
abstractly.
perception and
representation architecture:
- To gain a more global awareness of the implications of the
assessments of managers and builders, higher level
viewpoints are also stored as evolved models that have
previously proved beneficial in the situation of this set of
assessments must be used. Some agent(s) must take on
that
Jonathan Powell describes how the government of, the former UK Prime Minister, Tony Blair,
actually operated. Powell was Blair's only chief of
staff.
chief executive role.
We conclude consciousness has this role.
- Consciousness, or at least conscious access is, argues Stanislas Dehaene, when some attended information eventually enters our awareness and becomes reportable to others.
as it is defined in '
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.
Consciousness
And The Brain', appears to be a necessary set of high
level agents, that provide:
- Feedback on the appropriateness of current environmental
model assessments allowing for lower level modelers to
perform recording of more situational signals so that the
brain can adapt to its proximate environment.
- Responding to the stream of internal models that reflect
awareness prioritization of incoming environmental
signals, and where possible resolution of lower level
assessment conflicts.
- Responses to the significance of the high level state,
with only internal models to support it. These
changes to the high level state must be broadcast out to
the rest of the high level agents and lower level agents
that model signals based on the current proximate
state.
- Provide long term integration of the multiple strategies
that make up the current very
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.
high
level plan of action.
- Adjust the priorities of strategies within the plan, or
adopt an alternative plan when the situation in the
proximate environment changes significantly.
We hope that our CAS based comments help support the continued
scientific evaluations of our body's architecture and
operation.
 Politics, Economics & Evolutionary Psychology |
Business Physics Nature and nurture drive the business eco-system Human nature Emerging structure and dynamic forces of adaptation |
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integrating quality appropriate for each market |
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