Building emergence
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Rob, emerges from triangles & ovals
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Utilizing emergence in software development strategy

Working towards a vision of emergent agent-based software solutions enhancing strategy and enabling change in uncertain is when a factor is hard to measure because it is dependent on many interconnected agents and may be affected by infrastructure and evolved amplifiers.  This is different from risk, although the two are deliberately conflated by ERISA.  Keynes argued that most aspects of the future are uncertain, at best represented by ordinal probabilities, and often only by capricious hope for future innovation, fear inducing expectations of limited confidence, which evolutionary psychology implies is based on the demands of our hunter gatherer past.  Deacon notes reduced uncertainty equates to information. 
, real world environments

BES overview
To improve the ability for developed software to
This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
evolve
and
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
adapt 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 environmental aspects change, ensuring the sustained or enhanced delivery of solutions to customer problems, using novel software algorithms (
This page describes the Smiley infrastructure that supports the associative binding of schematic strings to codelets defined in the Meta file and Slipnet. 
The infrastructure supporting the associations is introduced. 
The role of Jeff Hawkins neocortical attributes is discussed. 
Relevant Slipnet configurations are included. 
The codelets and supporting functions are included. 
1
,
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. 
2
,
This page discusses how Smiley provides signalling to its agent-based applications. 
Alternative strategies for initiating the signalling are reviewed. 
The codelets and supporting functions are included.
3
,
This page describes the 'merge streams' application's codelet implementation of a 'case' architecture based on the adaptive web framework's (AWF) Smiley histone infrastructure. 
The application scenario for processing case statements is described. 
It involves a schematic binder complex for resolving the case statements. 
A case tagged application schemata. 
The Smiley infrastructure that supports the case architecture is reviewed. 
The Workspace schematic strings that implement the operon supporting histone like case control are included. 
The Slipnet concept network for the 'merge streams' application's histone like case control is included. 
The codelets and supporting functions are included. 
4
) and architectures (
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. 
1
,
This page describes a schematic system about abstracted 'animal' and 'plant' cells competing in a small world. 
The schematic cell was designed to focus in on the nature of mutation and the adjacent possible. 
THE IMPLEMENTATION IS INCOMPLETE AND ONGOING. 
The codelets and infrastructure are included. 
2
,
This page discusses how Smiley can support the start of the development phase of an agent-based application. 
Startup is an artificial operation not found in living systems.  But Smiley must do it and so we discuss an example of starting the development phase. 
With the Smiley infrastructure and the application integrated the application's development phase is reviewed.
The association of structural Workspaces for state representation is discussed. 
The aggregation of schematic associations of codelets defines a development agent.  At the application level it processes the application's schematic strings. 
The schematic nature of the data processed by the test application suggests the use of an indirect integration framework.  This supports the binding of codelets to the schematic data and detecting and responding to the control operons. 
An application polymerase complex emerges. 
The codelets and supporting functions are included. 
3
,
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. 
4
,
This page describes the specialized codelets that provide life-cycle and checkpoint capabilities for Smiley applications. 
The codelets implement a Shewhart cycle. 
The structural schematic nature of the cycle is described. 
Transcription factor codelets operate the phase change controls. 
How inhibitory agents are integrated into the cycle is described. 
An application agent with management and operational roles emerges. 
The codelets and supporting functions are included. 
5
)
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
on real-world
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
This page introduces the complex adaptive system (CAS) theory frame.  The theory provides an organizing framework that is used by 'life.'  It can illuminate and clarify complex situations and be applied flexibly.  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. 
systems


BES results
The program has developed two operational
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-based
research applications:
  1. Testing application, managed by an agent-based iterative
    This page describes the specialized codelets that provide life-cycle and checkpoint capabilities for Smiley applications. 
    The codelets implement a Shewhart cycle. 
    The structural schematic nature of the cycle is described. 
    Transcription factor codelets operate the phase change controls. 
    How inhibitory agents are integrated into the cycle is described. 
    An application agent with management and operational roles emerges. 
    The codelets and supporting functions are included. 
    process cycle
    and a
  2. 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
    , optimized with a genetic algorithm
as well as fully operational infrastructure supporting the applications run time
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
.  The infrastructure supported parallel deployment, scheduling and operation of the agent aggregates forming the applications.  Further applications are in development, as described below. 

The testing application has a number of important and novel aspects:
Multiple generations of genetically discrete competing
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 robots
, are developed using a genetic algorithm.  The form of the robots is novel:
The supporting infrastructure has a number of important and novel aspects:

An
The page reviews how complex systems can be analyzed. 
The resulting analysis supports evaluation of system events. 
The analysis enables categorization of different events into classes. 
The analysis helps with recombination of the models to enable creativity. 
The page advocates an iterative approach including support from models. 

analysis
framework was developed and used to describe the
This page introduces the complex adaptive system (CAS) theory frame.  The theory provides an organizing framework that is used by 'life.'  It can illuminate and clarify complex situations and be applied flexibly.  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. 
theory
: creativity, fitness, productivity; and
We are products of complexity, but our evolution has focused our understanding on the situation of hunter gatherers on the African savanna.  As humanity has become more powerful we can significantly impact the systems we depend on.  But we struggle to comprehend them.  So this web frame explores significant real world complex adaptive systems (CAS):
  • Assumptions of randomness & equilibrium allowed the wealthy & powerful to expand the size and leverage of stock markets, by placing at risk the insurance and retirement savings of the working class.  The assumptions are wrong but remain entrenched. 
  • The US nation was built from two divergent political views of: Jefferson and Hamilton.  It also reflects the development of competing ancient ideas of Epicurus and Cyril.  But the collapse of Bretton Woods forced Wall Street into a position of power, while the middle and working class were abandoned by the elites.  Housing financed with cash from oil and derivative transactions helped hide the shift. 
  • Most US health care is still operating the way cars built in the 1940s did.  Geisinger is an example of better solution.  But transforming the whole network is a challenge.  And public health investment has proved far more beneficial.  
  • Helping our children learn to be effective adults is part of our humanity, but we have created a robust but deeply flawed education system.  Better alternatives have emerged.  
  • Spoken language, reading and writing emerged allowing our good ideas to become a second genetic material. 
  • The emergence of the global economy in the 1600s and its subsequent development; 
It explains how the examples relate to each other, why we all have trouble effectively comprehending these systems and explains how our inexperience with CAS can lead to catastrophe.  It outlines the items we see as key to the system and why. 

operation of real-world
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. 
systems, including the US is the United States of America.  
The structure and problems of the US health care network is described in terms of complex adaptive system (CAS) theory. 

The network:
  • Is deeply embedded in the US nation state. It reflects the conflict between two opposing visions for the US: high tax with safety net or low tax without.  The emergence of a parasitic elite supported by tax policy, further constrains the choices available to improve the efficiency and effectiveness of the network.  
    • The US is optimized to sell its citizens dangerous levels of: salt, sugar, cigarettes, guns, light, cell phones, opioids, costly education, global travel, antibacterials, formula, foods including endocrine disrupters;
    • Accepting the US controlled global supply chain's offered goods & services results in: debt, chronic stress, amplified consumption and toxic excess, leading to obesity, addiction, driving instead of walking, microbiome collapse;
    • Globalization connects disparate environments in a network.  At the edges, humans are drastically altering the biosphere.  That is reducing the proximate natural environment's connectedness, and leaving its end-nodes disconnected and far less diverse.  This disconnects predators from their prey, often resulting in local booms and busts that transform the local parasite network and their reservoir and amplifier hosts.  The situation is setup so that man is introduced to spillover from the local parasites' hosts.  Occasionally, but increasingly, the spillover results in humanity becoming broadly infected.  The evolved specialization of the immune system to the proximate environment during development becomes undermined as the environment transforms. 
  • Is incented to focus on localized competition generating massive & costly duplication of services within physician based health care operations instead of proven public health strategies.  This process drives increasing research & treatment complexity and promotes hope for each new technological breakthrough. 
  • Is amplified by the legislatively structured separation and indirection of service development, provision, reimbursement and payment. 
  • Is impacted by the different political strategies for managing the increasing cost of health care for the demographic bulge of retirees.  
  • Is presented with acute and chronic problems to respond to.  As currently setup the network is tuned to handle acute problems.  The interactions with patients tend to be transactional. 
  • Includes a legislated health insurance infrastructure which is:
    • Costly and inefficient
    • Structured around yearly contracts which undermine long-term health goals and strategies.  
  • Is supported by increasingly regulated HCIT which offers to improve data sharing and quality but has entrenched commercial EHR products deep within the hospital systems.  
  • Is maintained, and kept in alignment, by massive network effects across the:
    • Hospital platform based sub-networks connecting to
    • Physician networks
    • Health insurance networks - amplified by ACA narrow network legislation
    • Hospital clinical supply and food production networks
    • Medical school and academic research network and NIH
    • Global transportation network 
    • Public health networks 
    • Health care IT supply network
health care network
, US
A key agent in the 1990 - 2008 housing expansion Countrywide is linked into the residential mortgage value delivery system (VDS) by Paul Muolo and Mathew Padilla.  But they show the VDS was full of amplifiers and control points.  With no one incented to apply the brakes the bubble grew and burst.  Following the summary of Muolo and Padilla's key points the complex adaptive system (CAS) aspects are highlighted. 
sub-prime mortgage market
and
Tools and the businesses that produce them have evolved dramatically.  W Brian Arthur shows how this occurred.
technology market

The web frame structure, generator is a Perl script, typically launched as a child process within the configuration editor, by clicking 'generate web', which executes frame configuration file instructions merging the configuration variables with an HTML template file to generate target web pages.  The configuration instructions can be tailored by filters from the configuration file specified filter file. 
and
Plans emerge in complex adaptive systems (CAS) to provide the instructions that agents use to perform actions.  The component architecture and structure of the plans is reviewed. 
schematic string
oriented representation of the ideas and sources allowed the details to be treated as a common place, a format of note book where multiple areas of interest were recorded, described, cross referenced, and iteratively developed over a period of time.  John Locke's common place method's cross reference included an index 'hash chain' linking themes, such as 'money' to the pages where the themes were discussed.  Steven Johnson explains how the idea of a common place book inspired Tim Berners-Lee's design for the world-wide-web.  Walter Isaacson notes Leonardo da Vinci's use of a 'zibaldone' or common place book.  Charles Darwin also used the format in his note books. 
'book.'  This supported easy representation of associative linkages and creative slippage between one set of ideas and another. 
An
This web frame includes a set of presentations about complex adaptive systems (CAS)
HTML based presentation framework
was developed and used to describe details of the theory and practice. 
Additionally, a planning and control framework was developed and used to support the execution of action plans allowing operational strategies to be linked directly to source code deliverables aggregated in 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


BES introduction
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
systems typically generate variety, stimulating
This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
evolution


Additionally in such systems, when
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 aim is required, the operations are distributed and proceed in parallel, and input
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
are rich and arrive in parallel,
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
infrastructure is often deployed. 

Emergent system strategies can be leveraged
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 cultural 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
productively
in strengthening engineering solutions as illustrated by the success of the Internet, Linux and the world-wide-web. 
The general development process, however, continues to follow design rules formulated by the initial scientists and engineers studying and using early computing systems.  The process created a set of disconnects between the end product and its environment: 
  • The development process results in the generation of object code.  The object code flow is completely pre-specified.  When the flow diverges from the reality of its environment it will continue on regardless, or fail. 
  • Standard practices result in discrete designs, programs, test suites and deployments.  The result is a huge constraint on understanding and change.
The goal of standard practice is to build a unique focused program instance of sufficient 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. 
to be released to customers.  The designers work to develop a discrete perception of the customer's goals and needs and represent that perception in the designs, programs etc.  Only with the adoption of iterative development was adaptation 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. 
introduced into the design and programming activities. This improved designer's perceptions of the environment and the representations of the specification as development proceeds. 

When customers require variants of the release instance that improve the fitness of their activities the aim is typically in conflict with the processes that support the creation, and maintenance of a released product version.  Customization becomes dependent on additional processes typically disjoint from the core development of the product. 

The goal of the emergent software systems program is to enable the specification, to drive emergence 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. 
development, testing and integration processes.  A class of emergent systems - 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 illuminate and clarify complex situations and be applied flexibly.  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
) will be used to shape the architecture of a software development system.  The architecture that emerges must be able to respond effectively to changes in the state of large networks of adaptive buildings, vehicles, planes etc.  

The testing process was
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. 
used
to build experience of emergent infrastructure.  With a specification of the rules a program (the web frames generator) is coded to follow, and an assertion of an outcome a test can be performed.  By following the rules and comparing the assertion to the output of the program the 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. 
of the program can be assessed.    Instead of a purely descriptive specification, a set of formal schematic structures were developed including:
Rather than developing a source program structured as a set of objects, a set of codelets associated with the schematic plans were developed, which could deploy onto a
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. 
perception and representation architecture


An implementation of an agent-based application, a
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. 

robot-janitor
, specified by Melanie Mitchell, was used to gain experience 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 algorithms
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. 
bootstrap communication channels
to the CAS research community.  It was subsequently proposed to additionally explore the adaptive web framework (AWF)'s potential to broadly leverage mutation and then attempt to discuss the GA and mutation work with Professor Mitchell. 

An implementation of an agent-based
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. 
neuron network
was found to be needed to support the testing application.  The test application required parallel state processing and representation of its test streams. 

This page introduces the complex adaptive system (CAS) theory frame.  The theory provides an organizing framework that is used by 'life.'  It can illuminate and clarify complex situations and be applied flexibly.  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
identifies production functions, as generators of valuable resources that emergent systems can tailor into niche specific varieties. 
In a post disruption environment there is a race to capture network effects.  Once the network effects have been obtained the winner will ensure further advantage until the next round of disruption. 
Product development
is a typical production function. 

Strategies:
This page discusses the program strategy in a complex adaptive system (CAS).  Programs enable executive leadership to undermine counterproductive extended phenotypic alignment within functions.  Programs generate coherent end-to-end activity.  The mechanism is reviewed. 
Program 4 progress
,
Strategy gives way to tactics.  If you your company or other emergent system collapse there is no further possibility of strategic action.  This page discusses the importance of sustaining the base of operations to support subsequent strategic action. 
Security
,
This page reviews the potential to benefit from strategy in a complex adaptive system (CAS).  The challenges described by Dorner require a careful search of the proximate environment. 
Scipio awareness
,
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 thinking
,
This page reviews the catalytic impact of infrastructure on the expression of phenotypic effects by an agent.  The infrastructure reduces the cost the agent must pay to perform the selected action.  The catalysis is enhanced by positive returns. 
Infrastructure amplifier
, Maintain options, Influence of natural obstacles,
Agents can manage uncertainty by limiting their commitments of resources until the environment contains signals strongly correlated with the required scenario.  This page explains how agents can use Shewhart cycles and SWOT processes to do this. 
Commitments match pre-conditions
,
This page reviews the strategy of architecting an end-to-end solution in a complex adaptive system (CAS).  The mechanism and its costs and benefits are discussed. 
End-to-end architecture
,
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 developmental bottleneck
,
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. 
Reconnoitering expedition
, Don't make a flank attack with the center open,
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 & sensors
,
This page discusses the tagging of signals in a complex adaptive system (CAS).  Tagged signals can be used to control filtering of an event stream.  Examples of CAS filters are reviewed. 
filtering tags
,
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 ubiquity and control
,
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
,
This page discusses the benefits of bringing agents and resources to the dynamically best connected region of a complex adaptive system (CAS). 
Centralization
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. 
Restriction of Pawns ready to advance
,
This page reviews Christensen's disruption of a complex adaptive system (CAS).  The mechanism is discussed with examples from biology and business. 
Disruption
.
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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