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

Working towards a vision of
This page discusses the mechanisms and effects of emergence underpinning any complex adaptive system (CAS).  Key research is reviewed. 
emergent
Plans are interpreted and implemented by agents.  This page discusses the properties of agents in a complex adaptive system (CAS). 
It then presents examples of agents in different CAS.  The examples include a computer program where modeling and actions are performed by software agents.  These software agents are aggregates. 
The participation of agents in flows is introduced and some implications of this are outlined. 
agent-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.  , real world environments. 

BES overview
To improve the ability for developed software to evolve and flexibly adapt 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
) modeled on real-world emergent systems. 

BES results
The program has developed two operational 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. Virtual robot, optimized with a genetic algorithm
as well as fully operational infrastructure supporting the applications run time 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 virtual robots compete, using a genetic algorithm.  The form of the robots is novel:
The supporting infrastructure has a number of important and novel aspects:

An analysis framework was developed and used to describe the
This page introduces the complex adaptive system (CAS) theory frame.  The theory is positioned relative to the natural sciences.  It catalogs the laws and strategies which underpin the operation of systems that are based on the interaction of emergent agents. 
John Holland's framework for representing complexity is outlined.  Links to other key aspects of CAS theory discussed at the site are presented. 
theory
and
This web frame explores very significant example real world complex adaptive systems (CAS).  It explains how the examples relate to each other, why we all have trouble effectively comprehending these systems and outlines the items we see as key to the system and why.  By understanding these summaries you can better frame the interdependencies of important events such as war in Iraq, new iPhone releases or a cancer diagnosis and see how they are impacting you. 

operation of real-world
adaptive systems, including the US is the United States of America.  
The nature of the US Healthcare system is represented by a series of summaries of books describing different aspects of the whole.  Here we explain the rationale behind the books selected and our conclusions based on the application of complex adaptive system (CAS) theory to the various transactions identified. 
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

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).  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. 
perception and representation
infrastructure is often deployed. 

Emergent system strategies can be leveraged successfully 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 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 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 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 is positioned relative to the natural sciences.  It catalogs the laws and strategies which underpin the operation of systems that are based on the interaction of emergent agents. 
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 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 is positioned relative to the natural sciences.  It catalogs the laws and strategies which underpin the operation of systems that are based on the interaction of emergent agents. 
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 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 child cell.  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. 
Perception and representation
,
This page discusses the benefits of bringing agents and resources to the center 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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