Emergence
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The whole is more than the sum of the parts

Summary
This page discusses the mechanisms and effects of emergence underpinning any 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
).  Key research is reviewed. 
Introduction
John Holland eloquently explains how new phenomena can emerge from certain types of systems. 

"A
This page discusses the physical foundations of complex adaptive systems (CAS).  A small set of rules is obeyed.  New [epi]phenomena then emerge.  Examples are discussed. 
small number of rules
or laws can generate systems of surprising 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 
. "

He argues that the complexity contains recognizable features, which recur.  They are also dynamic.  He goes on "that
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
create the emergent behavior of rule based systems. " ... "The simple laws of the agents generate an emergent behavior far beyond their individual capabilities.  It is noteworthy that this emergent behavior occurs without direction by a central executive.  "

What makes the agents emerge?  A little self-assembly is required.  A structure which can
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. 
support a plan
and self-assemble into an
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
can do this.  Hence Ribose Nucleic Acids (RNA (RNA), a polymer composed of a chain of ribose sugars.  It does not naturally form into a paired double helix and so is far less stable than DNA.  Chains of DNA are converted by transcription into equivalently sequenced messenger m-RNA.  RNA also provides the associations that encode the genetic code.  Transfer t-RNAs have a site that maps to the codon and match the associated amino-acid.  Stuart Kauffman argues that RNA polymers may be the precursor to our current DNA based genome and protein based enzymes.  In the adaptive web framework's (AWF) Smiley we use a similar paradigm with no proteins. 
), which can self-assemble, support schematic plans as in m-RNA (RNA), a polymer composed of a chain of ribose sugars.  It does not naturally form into a paired double helix and so is far less stable than DNA.  Chains of DNA are converted by transcription into equivalently sequenced messenger m-RNA.  RNA also provides the associations that encode the genetic code.  Transfer t-RNAs have a site that maps to the codon and match the associated amino-acid.  Stuart Kauffman argues that RNA polymers may be the precursor to our current DNA based genome and protein based enzymes.  In the adaptive web framework's (AWF) Smiley we use a similar paradigm with no proteins. 
and catalytic, an infrastructure amplifier.   actions such as transfer (t-RNA (RNA), a polymer composed of a chain of ribose sugars.  It does not naturally form into a paired double helix and so is far less stable than DNA.  Chains of DNA are converted by transcription into equivalently sequenced messenger m-RNA.  RNA also provides the associations that encode the genetic code.  Transfer t-RNAs have a site that maps to the codon and match the associated amino-acid.  Stuart Kauffman argues that RNA polymers may be the precursor to our current DNA based genome and protein based enzymes.  In the adaptive web framework's (AWF) Smiley we use a similar paradigm with no proteins. 
) provides a high profile
The agents in complex adaptive systems (CAS) must model their environment to respond effectively to it.  Samuel modeling is described as an approach. 
model
.  With time, emergent systems are likely to generate specialized agents better suited to particular tasks than the general purpose initiator.  These new agents will replace and obscure the earlier structures essential role. 

Agents are not required for emergence however.  Stuart Kauffman explains that very basic binary networks demonstrate emergent properties.  In particular the binary state of the elements can be transformed by the network into small numbers of emergent attractor regions which are stable unless the network is perturbed.  Terrence Deacon
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. 
describes a framework of dynamic processes
that bridges from thermodynamic chemistry to ends-focused functional systems. 

Physical systems, such as rivers, can be observed to demonstrate the emergence of persistent state.  The state can remain as long as the resources that support the flows exist.  But, the physical forces acting on the system typically perturb the situation, for example disrupting a
Barriers are particular types of constraints on flows.  They can enforce separation of a network of agents allowing evolution to build diversity.  Examples of different types of barriers and their effects are described. 
barrier
, allowing the resources to disperse. 
Epiphenomena are emergent
Abbott explains that a
This page discusses the physical foundations of complex adaptive systems (CAS).  A small set of rules is obeyed.  New [epi]phenomena then emerge.  Examples are discussed. 
phenomena
is emergent if it is conceptualized independently of the platform that implements it.  I.E. it is used and modeled without a direct dependence on the underlying phenomena and physical mechanisms.  Abbott demonstrates how emergent epiphenomena can encapsulate conceptual rules which can be associated with predictive theories, and these will hold while the underlying physics is in a matching phase. 

Abbott identifies two classes of emergent entities:
  • Equilibrium entities,
  • Autonomous entities;
Autonomous entities are implementations of epiphenomena's abstract designs, which can thus use
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. 
control of flows of energy
to sustain themselves. 

Chemical structures, emergent epiphenomena, focusing
This page discusses the physical foundations of complex adaptive systems (CAS).  A small set of rules is obeyed.  New [epi]phenomena then emerge.  Examples are discussed. 
physical phenomena
, can provide a
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. 
re-combinable
active matrix from which agents and schematic plans can be derived.  Similarly the adaptive web framework (AWF)'s
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. 
Coderack
associates re-combinable
This page describes the Copycat Workspace. 
The specialized use of the Workspace by the adaptive web framework's (AWF) Smiley is discussed. 
How text and XML are imported into the Smiley Workspace is described. 
Telomeric aging of schematic structures is introduced. 
The internal data structure used to represent the state of each workspace object is included. 
The Workspace infrastructure functions are included. 
Workspace
objects, and strings, with
This page describes the Smiley infrastructure and codelets that instantiate the epiphenomena defined in the Meta file and Slipnet. 
Infrastructure sensors are introduced. 
The role of phenomena in shaping the environment is discussed. 
The focusing of forces by phenomena in Smiley is discussed. 
The Meta file association of case keywords with phenomena is included. 
The codelets and supporting functions are included. 
epiphenomena
reflecting properties defined in the
This page describes the Copycat Slipnet. 
The goal of the Slipnet is reviewed. 
Smiley's specialized use of the Slipnet is introduced. 
The initial Slipnet network used by the 'Merge Streams' and 'Virtual Robot' agent-based applications is setup in initchemistry and is included. 
The Slipnet infrastructure and initialization functions are included. 
Slipnet
or its basic 'physical' constants. 

Complex systems emerge from the presence of feedback during the competition of a collection of simpler autonomous entities for scarce resources. 

If the competing 'entities' include an action inducing plan the feedback can include
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 operations
on the plans. 
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) agents can emerge. 
Kauffman's adjacent possible
Kauffman explains how natural selection expands the 'adjacent possible', by exposing Darwinian pre-adaptations to new competitive situations where they provide a selective advantage.  As an example he describes how the swim bladder emerged from a pre-adaptation of a fish lung.  "Paleontologists have traced the
This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
evolution
of swim bladders from early fish with lungs.  Some of these lived in oxygen-poor water.  The lungs grow as outpouchings from the gut.  The fish swallowed the oxygen-poor water, some of which entered the lungs, where air bubbles were absorbed, making it easier for the fish to survive.  But now water and air were both in a single lung and the lung was pre-adapted to evolve into a new function--a swim bladder that adjusted neutral buoyancy in the water column.  "

The emergence of multi-cellular
This page reviews the implications of reproduction initially generating a single child cell.  The mechanism and resulting strategic options are discussed. 
organisms
depends on the previous development 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. 
signalling infrastructure
, differential responses to signal strength, movement, structural binding; and a schematic plan that allows the cellular agent to
This page discusses the interdependence of perception and representation in a complex adaptive system (CAS).  Hofstadter and Mitchell's research with Copycat is reviewed. 
respond to external position relative signals by transposing them to, and then maintaining the, cell local coordinate signals for its cell to produce synchronized actions
across the locally dividing population.  Techniques include segmentation, identity coordinate signalling, and presence of an ordered schematic response to the local coordinate identity of any segment. 

The emergence of order from chaos provides an explanation for the apparently random period between water droplets falling from a tap.  Typically the model of the system is poor and so the data captured about the system looks unpredictable - chaotic.  With a better model the system's operation can be explained with standard physical principles.  Hence chaos as defined here is different from complexity.   in CAS represents a powerful adaptive mechanism. 



























































































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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. 
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  • 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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