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

Power& tradition holding back progress
This page uses an example to illustrate how:
  • A business can gain focus from targeting key customers,
  • Business planning activities performed by the whole organization can build awareness, empowerment and coherence. 
  • A program approach can ensure strategic alignment. 
Be responsive to market dynamics
This page uses the example of HP's printer organization freeing itself from its organizational constraints to sell a printer targeted at the IBM pc user. 
The constraints are described. 
The techniques to overcome them are implied. 
Overcome reactionaries
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Structurally Enhanced State

Summary
Representing state in
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
entities are, according to Abbott, a class including people, families, corporations, hurricanes.  They implement abstract designs and are demarcatable by their reduced entropy relative to their components.  Rovelli notes entities are a collection of relations and events, but memory and our continuous process of anticipation, organizes the series of quantized interactions we perceive into an illusion of permanent objects flowing from past to future.  Abbott identifies two types of entity:
  1. At equilibrium entities,
  2. Autonomous entities, which can control how they are affected by outside forces;
is essential but difficult.  Various structures are used to enhance the rate and scope of state transitions.  Examples are discussed. 
Introduction
Single component
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 carefully control the flow 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. 
signals
they receive so that their
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
transitions effectively.  This makes it difficult to respond effectively to parallel arrays of signals.  Multi-component structures can divide the processing of parallel signals, and then integrate the results as long as they:
The division of state between multiple components allows the pre-deployment of sensors and action mechanisms improving the response
Carlo Rovelli resolves the paradox of time. 
Rovelli initially explains that low level physics does not include time:
  • A present that is common throughout the universe does not exist
  • Events are only partially ordered.  The present is localized
  • The difference between past and future is not foundational.  It occurs because of state that through our blurring appears particular to us
  • Time passes at different speeds dependent on where we are and how fast we travel
  • Time's rhythms are due to the gravitational field
  • Our quantized physics shows neither space nor time, just processes transforming physical variables. 
  • Fundamentally there is no time.  The basic equations evolve together with events, not things 
Then he explains how in a physical world without time its perception can emerge:
  • Our familiar time emerges
    • Our interaction with the world is partial, blurred, quantum indeterminate
    • The ignorance determines the existence of thermal time and entropy that quantifies our uncertainty
    • Directionality of time is real but perspectival.  The entropy of the world in relation to us increases with our thermal time.  The growth of entropy distinguishes past from future: resulting in traces and memories
    • Each human is a unified being because: we reflect the world, we formed an image of a unified entity by interacting with our kind, and because of the perspective of memory
    • The variable time: is one of the variables of the gravitational field.  With our scale we don't register quantum fluctuations, making space-time appear determined.  At our speed we don't perceive differences in time of different clocks, so we experience a single time: universal, uniform, ordered; which is helpful to our decisions

time
of multi-component agents relative to single component process of initiating a schematic cascade. 

A variety of
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. 
complex adaptive systems (CAS)
exploit structurally enhanced state:
The
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
of structural enhanced state requires that a variety of coordination problems be overcome:
  • Structural effects must be schematically defined and implemented by agents.  
  • Emergent physical structures must be flexibly associated with sensors and actuators, and support the interconnection of network components. 
  • Developing system must be supported until it can leverage the enhanced capabilities. 
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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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