Signals & sensors
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Events, sensors and actions

Summary
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 (
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
).  CAS signals emerge from the Darwinian information model.  Signals can indicate decision summaries and level of uncertainty. 
Introduction
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)
interact with their environment when they detect some event via a sensor, or they
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. 
perform some action
that affects the environment. 

When the sensors are altered by the interaction with some
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
the sensor's state will change. 

Sensors provide
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
with an indication of some environmental state change.  However, the signals are typically general and the correct association will depend on the environmental context and agent's current state.  That encourages the development of
Rather than oppose the direct thrust of some environmental flow agents can improve their effectiveness with indirect responses.  This page explains how agents are architected to do this and discusses some examples of how it can be done. 
indirect
associations.  As long as the sensor's indication allows for differential choice of actions
This page reviews the implications of selection, variation and heredity in a complex adaptive system (CAS).  The mechanism and its emergence are discussed. 
evolution
can drive the emergence of advantageous associations. 

Consequently CAS signals do not just reflect Shannon, Claude Shannon was a key figure in information theory and computation.  He developed an electronic circuit using Boolean algebra which simplified the design and operation of a digital computer system enabling architectures such as Von Neumann's to become practical.  He also developed the mathematical models of information transfer which support information entropy. 
's entropy and information model but include Boltzmann and Darwinian information.  CAS agent's decisions are summarized in the signal. 

Signals can be multi-modal, real world effects include sound, light, touch etc. at the same time. 
and require very rapid processing.  Such challenges can act as selection pressures as agents evolve enhanced strategies, for example
Representing state in emergent entities is essential but difficult.  Various structures are used to enhance the rate and scope of state transitions.  Examples are discussed. 
structurally enhanced state
, for coping. 
Interacting with the environment
Autonomous agents can 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 their internal flows of energy
to interact with the broad environment, altering their state via responses to sensors, or changing the external environment by applying energy directly or indirectly. 
Associative infrastructure adds evolutionary control and flexibility
Associative mechanisms of binding goals, events, actions and signals enable
This page discusses the mechanisms and effects of emergence underpinning any complex adaptive system (CAS).  Key research is reviewed. 
emergence
.  The abstract nature of the primary signals, and the benefit of fast operation, encourages the formation of front-end processors which include abstract
The agents in complex adaptive systems (CAS) must model their environment to respond effectively to it.  Samuel modeling is described as an approach. 
modeling
allowing parallel distributed processing to rapidly form integrated signals that are subsequently processed by separate clusters of 'higher level' agents. 

Infrastructure exists in biochemical systems associating DNA (DNA), a polymer composed of a chain of deoxy ribose sugars with purine or pyrimidine side chains.  DNA naturally forms into helical pairs with the side chains stacked in the center of the helix.  It is a natural form of schematic string.  The purines and pyrimidines couple so that AT and GC pairs make up the stackable items.  A code of triplets of base pairs (enabling 64 separate items to be named) has evolved which now redundantly represents each of the 20 amino-acids that are deployed into proteins, along with triplets representing the termination sequence.  Chemical modifications and histone binding (chromatin) allow cells to represent state directly on the DNA schema.  To cope with inconsistencies in the cell wide state second messenger and evolved amplification strategies are used. 
sequences with amino acid are the building blocks of proteins.  The 20 main variants differ by the nature of their side chain.  Some are positively charged, others negatively charged.  Some are water seeking while others are fat seeking.  The genetic code mapping of DNA base pair triplets thus specifies the primary sequence of amino-acids in any protein polymer. 
sequences.  Significantly there are also DNA sequences which are associated with binding of the infrastructure to the DNA. 

The presence of DNA sequences which associate with conserved binding domains, evolution conserves many useful structures including DNA base sequence (content) addressable binding regions, protein active sites and signal structures which can then be reused through the mutation genetic operator. 
to support the replication, a key control mechanism in eukaryotic cells ensures that the cell can replicate when required.  The process is complicated but is logically equivalent to a Shewhart cycle with four phases: (1) general operation using the DNA as the plan, (2) generation of copies of genetic material, (3) checking that the copies were robust, (4) separation of the cell into two.  The details of the cell-cycle are described by Helmreich.  In AWF the eukaryotic cell-cycle has been abstracted in a codelet based implementation. 
and synthesis uses the product of the transcription of DNA into messenger m-RNA and is mostly the translation of the m-RNA into a folded protein by Ribosomes and t-RNA. 
infrastructure allows indirect associations to become responsive to
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


In general the association of environmental signals, sensors and actions is under the control of genetic operators in a CAS, but based on the
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 associative binding.  This allows for changes to be introduced into the system that can be selected for by evolutionarily competitive forces.  Genetic operations include the mutation and recombination of the signal, sensor, action associations.  The recombined associations become
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
supporting the evolved history of the CAS agents. 

Genetic operators can bind sensors to different pathways to respond to alternative contexts.  Responding to a set of situational signals, is an emergent capability which is used by cooperating agents to support coordination & rival agents to support control and dominance.  In eukaryotic cells signalling is used extensively.  A signal interacts with the exposed region of a receptor molecule inducing it to change shape to an activated form.  Chains of enzymes interact with the activated receptor relaying, amplifying and responding to the signal to change the state of the cell.  Many of the signalling pathways pass through the nuclear membrane and interact with the DNA to change its state.  Enzymes sensitive to the changes induced in the DNA then start to operate generating actions including sending further signals.  Cell signalling is reviewed by Helmreich.  Signalling is a fundamental aspect of CAS theory and is discussed from the abstract CAS perspective in signals and sensors.  In AWF the eukaryotic signalling architecture has been abstracted in a codelet based implementation.  To be credible signals must be hard to fake.  To be effective they must be easily detected by the target recipient.  To be efficient they are low cost to produce and destroy. 
a particular configuration of sensor pathway can be deployed.  This situation is seen in hormone are signalling molecules: ACTH, TRH, Melanocyte stimulating hormone, Testosterone, Oxytocin, Vasopressin, Insulin, Growth hormone, Estrogen, Progesterone, Angiotensin II, Asprosin, EPO, Irisin, Leptin, FGF21 hormone, Prostaglandins, TSH, Thyroxine, Glococorticoids; that are transported by the circulatory system to interact with target organs having appropriate receptors.  The levels of hormones can fluctuate massively, as in pregnancy. 
sensors for oxytocin is a peptide hormone which makes humans more prosocial to and socially competent in their in-group and more antisocial to everyone else.  The effects are contingent; changing during stress and in the presence of a threatening outgroup.  Oxytocin makes people look at eyes longer, encouraging improved accuracy at perceiving emotions.  It enhances activity in the TPJ supporting modeling of other people's thinking.  Dogs and their owners secrete oxytocin increasing the amount of eye contact between them.  It is associated with pair bonding: higher levels of receptors in males having lots of sex and in females performing grooming & physical contact, Sex releases oxytocin in the nucleus accombens of female prairie voles.  Such males are less interested in other females.  It is central to female mammals wanting to nurse, nursing, and remembering their child.  Its effects are context dependent and so is the regulation of the genes that control oxytocin.  Variants of a gene CD38 which facilitates oxytocin secretion from neurons are associated with differing levels of activation of the fusiform face area when looking at faces.  Hypothalamic neurons send projections to: ventral tegmentum which also becomes more receptive during child birth, nucleus accumbens, hippocampus, amygdala where it inhibits the central amygdala suppressing fear & anxiety consistently in men while still allowing women to respond to threats to their infants, frontal cortex, olfactory network where it helps new rat mums to learn the smell of their offspring; where oxytocin prepares the brain for in-group bonding, out-grouping, birth and maternal behavior.  Outside the brain hypothalamic neurons in females send oxytocin to the posterior pituitary where it enters the blood stream stimulating uterine contraction during labor & supporting milk production for weaning.  Disorders associated with oxytocin abnormalities include ASD. 


Differential responses to signal strength
Emergent CAS agents can use the ability to respond differently to different signal strengths to create models of their local environments.  In effect when the signals vary with range across the local environment they provide the coordinates of a map.  This can be used to coordinate the responses of neighboring cells, via the schematic models that associate particular cascades with the local environmental state. 

CAS inherently vary ensuring adaptability to appropriately changing environmental
This web page reviews opportunities to find and capture new niches based on studying fitness landscapes using complex adaptive system (CAS) theory. 
fitness landscapes


Decision signals
Signal aggregation allows suitably supplied agents the opportunity to develop evolutionarily beneficial decision based strategies.  When supported by infrastructure enabling second messenger, provide an amplified form of signals within a cell.  Since cells need to stabilize their overall state with many operations happening in parallel second messengers are useful in clarifying the signals effect.  The second messenger strategy is seen repeatedly in CAS including: neuro-transmitter guidance signals such as dopamine distribution in the brain, corporate positioning email messages in response to new situations, newspaper articles aligning the population;  amplification or NMDA is a synaptic channel which is sensitive to voltage and to the signals glutamate and its relative N-methyl-D-aspartate.  It rarely opens to glutamate unless the membrane potential becomes less negative than at rest.  That may be due to the action of other receptors nearby.  When the channel opens it allows in calcium ions which alter the strength of the synapse for days, weeks, months or longer.  That may be the basis of a form of memory.  If NMDA channels are chemically inactivated in a rat's hippocampus, the rat cannot remember where it has been.   channel, an active membrane spanning protein with a central pore through which a targeted ion is driven until the channel is opened by a signal which then allows the ions back across the channel continuing the electro-chemical wave. 
operation the strategy can alter the aggregate state of the network of agents.  And this decision including its 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.   can be signalled. 

In business specialized sensory structures such as shops, and sales offices support the parallel integration and channeling of environmental signals.  Again roles are dynamically associated with agents and goals.  The use of reorganization, really the genetic recombination operation, of reporting structures, and the replacement of staff, introducing point mutations, create the potential for genetic variation that enables adaptation in evolutionary biology is a trait that increased the number of surviving offspring in an organism's ancestral lineage.  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. 

























































































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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. 
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Each goal has a series of associated complex adaptive system (CAS) strategy strings. 
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