Modularity
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Modularity, objects and CAS adaptation

Summary
This page discusses the strategy of modularity in a complex adaptive system (
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
).  The benefits, mechanism and its
This page discusses the mechanisms and effects of emergence underpinning any complex adaptive system (CAS).  Key research is reviewed. 
emergence
are discussed. 
Introduction
The separation of
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
, different functions and operations within different sub-components of a
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. 
system
sharing a coherent set of
Plans emerge in complex adaptive systems (CAS) to provide the instructions that agents use to perform actions.  The component architecture and structure of the plans is reviewed. 
schematic plans
provides a number of potential benefits: 

Some biological systems separate the schematic plans they use for sexual reproduction enforces the mixing of current germ-line DNA of a male and a female organism, with a recombination process, to ensure the generation of new schematic recipes and phenotypes in their shared offspring.  , the germ-line, a master copy of the schematic structures is maintained for reproduction of offspring.  There will also be somatic copies which are modified by the operational agents so that they can represent their current state.  , from the plans they use for day to day development is a phase during the operation of a CAS agent.  It allows for schematic strategies to be iteratively blended with environmental signals to solve the logistical issues of migrating newly built and transformed sub-agents.  That is needed to achieve the adult configuration of the agent and optimize it for the proximate environment.  Smiley includes examples of the developmental phase agents required in an emergent CAS.  In situations where parents invest in the growth and memetic learning of their offspring the schematic grab bag can support optimizations to develop models, structures and actions to construct an adept adult.  In humans, adolescence leverages neural plasticity, elder sibling advice and adult coaching to help prepare the deploying neuronal network and body to successfully compete. 
and operation - the somatic, Schematic structures which are used to support the operation of the agent.  They are modified as the agent's state changes unlike the germ-line schemata.   line.  This can allow for epi-genetic modifications represent state surfaces within cells and eggs which can be operationally modified so as to provide a heritable structure.  DNA, histones and other stable structures provide surfaces where these states may be setup.  Egg carriers are in a particularly powerful position to induce epi-genetic changes.  Sapolsky notes [childhood] events which persistently alter brain structure and behavior via epi-genetic mechanisms including: pair-bonding in prairie voles, as they first mate, is supported by changes in oxytocin & vasopressin receptor gene regulation in the nucleus accumbens. 
to be targeted at the appropriate line only.  Further, growth can change the state of the somatic agents to reflect specialization requirements of somatic cell lines, without impact to the germ-line schemata. 

Engineered systems separate designed modules to reduce complexity, M. Mitchell Waldrop describes a vision of complexity via:
  • Rich interactions that allow a system to undergo spontaneous self-organization
  • Systems that are adaptive
  • More predictability than chaotic systems by bringing order and chaos into
  • Balance at the edge of chaos 
, and separate work efforts.  Engineers obtain standardized training in best practice ideas and processes allowing basic coherence of understanding and communications signals. 

Still systems engineers have observed that the accumulation of simultaneous & interacting factors brings slower & slower motion. 

Engineered systems have tended to separate architecture, design, project plan and operational activities of the schemata.  Each engineer must understand how his responsibilities and actions affect each of these aspects and others sharing them.  When the sharing, or understanding is not perfect coordinated actions suffer, and each aspect may become misaligned. 

Methodologies that constrain complexity as the system grows are often chosen to limit the uncertainty 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.  .  For example simple regular interconnections are easy for architects and engineers to understand.  Data and control flows can be assembled into simple regular structures of modules, sub-systems and then systems.  The hierarchy is designed using a range of abstractions that focus on different levels of symbolic representation that help focus attention on specific aspects of the system.

However the engineer's choices of what to separate, how the resources are shared between the modules, how interdependencies are handled and the structure of the interfaces to the modules are all difficult to decide.  Indeed Hofstadter argues, in Fluid concepts and creative analogies, that
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
are interdependent. 

To consistently make effective choices an
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, and top-to-bottom understanding
(shared
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 plan
, actions and
The agents in complex adaptive systems (CAS) must model their environment to respond effectively to it.  Samuel modeling is described as an approach. 
models
) of the environment and Eco-system is required. 

Gaining such a broad understanding of a new area requires iterative processes and collective feedback on available models, options and challenges encountered, which allows for rating of the schemata.  Such activities seem at odds with information hiding strategies that are also advocated to support modularization. 

Walter Shewhart's iterative development process is found in many complex adaptive systems (CAS).  The mechanism is reviewed and its value in coping with random events is explained. 
Shewhart cycles
allow for iterative alignment of all aspects with the agent's understanding of the system and its environment. 

This page discusses the mechanisms and effects of emergence underpinning any complex adaptive system (CAS).  Key research is reviewed. 
Emergent
complex adaptive system (CAS) agents can have direct access to shared schematic plans, which integrate design, planning, and operations.  Through the
This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
evolutionary action
of
Plans change in complex adaptive systems (CAS) due to the action of genetic operations such as mutation, splitting and recombination.  The nature of the operations is described. 
genetic operators
they can improve the schemata's strategies for survival and replication and create effective modules. 

Alternatively a set of cooperating
This page reviews the implications of reproduction initially generating a single child cell.  The mechanism and resulting strategic options are discussed. 
organisms
can depend on synergies to create a system out of different free standing agents.  These production functions have aligned reproductive events, but do not have to operate from copies of identical schemata.  In effect the sum of the schematic plans becomes available with a specialized partitioning of components of the plans. 

Evolution can also be used to support engineering decisions about modularization. 
Flexibility can be ensured by integrating an adaptive process into the system design.  An evolutionary process uses market selection among competitive alternatives to the design of the modules defined by the constraints of the design rules.  By requiring a
Plans emerge in complex adaptive systems (CAS) to provide the instructions that agents use to perform actions.  The component architecture and structure of the plans is reviewed. 
memetic specification
for each module, selection pressures can be reflected in a set of specification
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. 
schemata
.  

Within the shared specification process
Plans change in complex adaptive systems (CAS) due to the action of genetic operations such as mutation, splitting and recombination.  The nature of the operations is described. 
genetic operators
will drive the system modularization.  Baldwin and Clark identify operations such as: splitting, substituting, augmenting, excluding, inverting and porting. 

Object orientation aims to facilitate the modularization process based on
Grady Booch advocates an object oriented approach to computer software design. 
"natural" hierarchies
within design domains.  However, end-to-end studies of Eco-systems suggest that the assumption of natural hierarchy can be unreasonable. 
Terrence Deacon explores how constraints on dynamic flows can induce emergent phenomena which can do real work.  He shows how these phenomena are sustained.  The mechanism enables the development of Darwinian competition. 
Theory of dynamic constraint based emergence
suggests emergent hierarchies are deeply entangled.  If the system description is characterized by change based on iteratively improving, or alternative
This page discusses the interdependence of perception and representation in a complex adaptive system (CAS).  Hofstadter and Mitchell's research with Copycat is reviewed. 
perceptions, and demands fluid representations
then object hierarchies must become deeply entangled and constraining. 

Instead a
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. 
Copycat
style architecture can integrate the schematic plans with perceptions about the system and environment to select agents best suited to the local situation. 
Market Centric Workshops
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Politics, Economics & Evolutionary Psychology

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


integrating quality appropriate for each market
 
This page looks at schematic structures and their uses.  It discusses a number of examples:
  • Schematic ideas are recombined in creativity. 
  • Similarly designers take ideas and rules about materials and components and combine them. 
  • Schematic Recipes help to standardize operations. 
  • Modular components are combined into strategies for use in business plans and business models. 

As a working example it presents part of the contents and schematic details from the Adaptive Web Framework (AWF)'s operational plan. 

Finally it includes a section presenting our formal representation of schematic goals. 
Each goal has a series of associated complex adaptive system (CAS) strategy strings. 
These goals plus strings are detailed for various chess and business examples. 
Strategy
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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. 
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