is the beyond random repetition of matter &/or motion from any given fixed perspective.
Cognitive 
Physics
Cognitive
PhysicsPhysics
Consider a computer entity that regards all sensor information as chronological strings of data made up of the smallest isolable incoming particles. As a portion of definition, each of these particles is assigned standard specific additional information known to be pertinent to sensor perception of this kind. For instance, the definition of a particle is obviously extended to include the type of sensor perception, however there are other commonly known standard distinguishing aspect assigned to the particles generated by a given sensor, such as: the dimensional direction from which it was perceived, the time of the perception, the source of the action (perhaps presumed), and many more depending of the environment and the nature of the sensor.
Particle Portraits of Knowledge
Approximate Definition Artifacts (ADAs)
This cognitive artifact is the isolated cluster of particles that occurs as the results of any given attempt by a given entity; to define any thing, aspect, or other concept within a given universe.
Theoretical continuity of order is recorded and reflected by an entity as it attempts to effectively shape its universe (physical and cognitive space) according to the given entity's objectives.
Particle Flow of Definition-Quarks in the Processing Cycle of a Self Shaping Circuit
Definition Artifacts
The machine's experiences are records composed of i/o particles that represent the most basic sensor signals and shaping commands that can be isolated (first by the creator, then subject to mutation by the entity).
This incoming stream of sensor particles, and outgoing shaping particles, are the purest and most reliable (also perpetual) record of what has occurred. As soon as the entity interprets, formats, or assimilates this quark-scaled data, it is subject to distortion. An entity that handles i/o as chronological streams of quark scaled particles can perfectly recall and progressively analyze historical events and its own interaction within such events.
1. The processing cycle begins with the definition of useful environmental concepts (isolated within the sensor particle streams). These particles are clustered within indicative atomic formats to represent isolable flux in the target environment. More complex structures (definitions) are theorized representing durations or concepts of environmental experiences.
2. Atomic structures are clusters into value-polarized cause/effect event records. (Such records are definition particle portraits of individual cognitive-cycles. A cognitive-cycle is an environmental flux, followed by reactionary entity shaping, followed by the self-induced/expected flux.)
3. Access parallel order. Unknown flux is associated with the most similar known flux.
4. Historical reactionary output/shaping particle clusters and expectation-records are resected according to the incongruent particles of the simile compare used to reference the parallel order.
5. Resected historical reaction is implemented. The target environment is effected according to output/shaping particles. (Notice that output/shaping particles will be handled using approximately the same cognitive format as input/sensor particles. The only differences are the symbols themselves, and the opposite directions of the i/o actions.)
6. Expected-flux is compared with post event flux to evaluate effectivity of simile reference and resection attempt.
7. Post-flux is processed (Return to step 1).
Detecting Patterns
Patterns are discovered and recorded exclusively by entities. Patterns are recognized initially as particle repetition beyond random expectation.
If The Definition Is In Error
Such definition attempts will commonly contain obscurities, inconsistencies, errors and omissions, reflecting imperfect entity perceptions and conclusions.
Human beings commonly develop very effective cognitive systems. All of these systems are based on inaccurate and incomplete data. Yet using said faulty data, and making numerous errors in the observation, comparison and processing of this imperfect order; they frequently arrive at useful or even correct solutions for their problems.
V. SIMILE SELECTION (non-default)
SIMILE CONDUITS TO PARALLEL ORDER. The (imperfect) Compare Event.
What about this decision of... "Which is the most similar?"
Human beings seem to have been blessed with a natural ability for picking out similes. I suspect it helps that they are so reliably imperfect at such processes as comparison and memory.
But a computer is flawless at comparisons and memory. A computer seems almost useless on the question; which one of those is most similar to this? (Or which factor, in the list of B factors, is most similar to the radical source, factor A?)
A computer is capable of making an evaluation of "greater than" and "less than", if a polarized spectrum of relative incrementation has been designated. But a computer can not simply select a simile (to factor A) from a list of candidates (factors B). The simile concept is beyond the capabilities of a computer.
Such imperfect comparisons are common in SSM processing; so in order for a computer to be able to host a Self Shaping Machine, we must show the computer how to be tolerant during the compare event.
We will inject a subroutine that will make a...
A. Simile Compare Decision (SCD).
In order to be able to mathematically recognize a relevant simile (beyond default methods), we must introduce a third factor to the comparison event.
A normal perfect compare has only two primary elements.
factor A (is compared to) factor B
If A is equal to B:
then the results of the comparison event is POSITIVE.
If not equal, the comparison is NEGATIVE.
This 3rd factor must allow a positive compare between two primary elements that are not equal. This 3rd factor will selectively augment certain defined aspects (ADA cell points or bonds) of the comparison event. A Simile Compare Decision is a comparison event that uses this third factor to achieve (qualify) a "match," between two primary factors, that are not equal.
ac = a(b or c or d)
Parameter Expansion
(evolved shapers - non default method)
There are many such qualifying parameters that may be assigned (on an cell by cell basis) to the definitions of any given ADA comparison factor or factors. The collection of these qualifying aspects (as it interposes in the comparison event) is the Simile Compare Catalyst (SCCatalyst). (In an evolved shaper, this replaces simple creator assigned atomic particle-proximity priorities, which is the primitive default method of simile selection.)
Priority should be given to the development of SCCs concerning what constitutes a relevant similarity, especially at the key Simile Compare Decision points of a given task network.
The Key: The Simile Compare Catalyst.
A Simile Compare Decision is made through the application of a special exclusive/inclusive SCCatalyst (called an SCC-ADA) that intervenes in the comparison decision, to indicate an "equal" compare between (two or more) individually unique (and truly unequal) ADAs.
These SCCs would indicate specifically which cell points of the related ADAs (involved in a given type of Simile Compare Decision event) either: compared normally, did not have to be considered in the comparison event, or might be restricted so that "equality" will be registered only if the corresponding ADA cells fall within certain given parameters.
Notice that a simile may conceivably share no equal specifics with the radical; all cells may be considered "equal" in type only.
These SCCatalysts used to authenticate the SimilComps need not be perfect, complete, nor even correct; they must only generate some degree of effectivity. The processing cycle of the SSM will augment and mutate these pivotal processing SCCatalysts toward more effective operations policies, with these effectivity evaluations based on modular priorities and objectives.
B. Cell Point Priorities
Forcing A Selection Between Multiple Unqualified Candidates.
Screens for SCCatalysts that Designate
Priority, Value, and Perspective.
(The Relevant Connection)
Value-maps/Perspective-screens
An SCCatalyst will widen the parameters of a comparison event to allow a greater spectrum of candidate-ADAs (CandADA) to qualify as a "match." If no match is found, the circumstances may yet demand that a decision be made, as to, which of the failed attempts compares as the most relevant match. To be able to make this discrimination, a sequence of cellular priorities must be established, and applied to individual (cell by cell) parameters.
A Parameters Relevance Priorities Screen (PRPS) is a cellular relevance guide, a map which accompanies an SCCatalyst, and overrules the creator assigned defaults. This PRPS screen designates the priorities (of the qualifying relevance) of each ADA cell being compared in the event.
This "relevance map" answers the question, "How important is it?": that a given cell factor is equal, and what degree of inequality will be tolerated for the individual and collective cells. (These degree parameters usually are polarized and designated with an incremented spectrum of values.)
Most SCCatalysts are accompanied by a number of augmenting screens that designate a cellular sequence of priorities, that is a blueprint of, which cells are most critical to a relevant (successful) compare, from this screen's unique value perspective. If none of the candidates fall within the qualifying parameters, a value appraisal may be desired, in assessing; which of these failed candidates is theorized to be the most useful simile.
Such priorities designation is necessary in a hostile environment, where a given entity will frequently be faced with a real-time practical demand, to locate a historical simile of the flux portion of an event polarized definition cluster containing a reactionary sequence for shaping the environment in an effective manner. This flux is most commonly of the cause, problem, or opportunity type, linked within the definition cluster of an event record, to an effect, solution, or acquisition plan, respectively.
Unavoidable Premature Conclusions
Because, when all SCCatalysts have been tried, and no similADA has been found that fits within the parameters of a positive compare, reality frequently still demands that (at some point in the task grid) a choice be made. A decision must be made that will answer the question: "Which of the candidates came closest to being suited for a 'positive' compare?"
These calculations would produce a best failed candidate, which would be of a less reliable relevance to the perhaps distantly parallel problem. This re-qualified ADA structure may be the best non-random framework available, a point from which an SSM may begin trials of mutated versions of a solution-ADA, that may or may not be effective, but would ordinarily outperform randomly constructed configurations.
C. Accessing Parallel Order
INCLUSIVITY: Common Profiles Of Order; Established From
A Multiple Of Unique Fixed Perspectives
1. Cell Type
Most ADAs may be redefined from a parallel perspective, not by the specific content of cells, but by the parameters and types (the nature of the contents) of the cell points, in the given ADA structure. For instance, an ADA that contains four cells, might be described either as an ADA made of four specific cell contents, or an ADA made of four inclusive types with parameters; or a given combination of both types.
The individual cell parameter norms of these groups may be compared to establish the group parameter boundaries of each cell point. A valid parallel perspective need not include the specific contents of a cell; it may only be a description of cell types and inclusive parameters, that are indicated by a comparison of the collective corresponding cell group contents.
This establishment of structurally correlating cell positions between individual ADAs is a more inclusive (and less specific) perspective from which to view the data of a given ADA or ADA group.
Such a structure is very useful within the calculations of an SSM as an SCCatalyst for establishing relativity (achieving SimilComps), between known and unfamiliar ADA knowledge structures, and for isolating the radical cell parameters of an unfamiliar ADA structure.
A candidate ADA of a Simile Compare Decision, that compares as equal, through an SCCatalyst made according to the parameters of a structurally similar ADA group, has a greater than random probability of containing relevant and/or useful continuity of effective IEOrder.
An ADA cell-point May Have Varying Degrees of Inclusivity
Human beings record events in an inclusive, and multi-leveled, redundant fashion.
For example: if you were 40 years old today, and had taken an automobile journey when you were 10, you might recall this adventure in varying degrees of inclusive generality.
For instance, if you went to New York with your parents and older brother, stayed one night in a Hilton hotel; and the water pump (on the Ford) failed during the trip home; causing your family to stop at the Ajax garage for several hours. You might conceivably remember this event in different versions of (point by point) inclusivity.
You might remember this trip with your parents, but the memories might have faded, and you might no longer recall that the trip was to New York, but still know that it was a large city. You might recall that either your older brother or sister accompanied you, and that the car broke down, because of something wrong under the hood. These missing details leave you with a general, more inclusive, yet factual (and useful) portrait of the event.
2. Inclusive Repetitive Events
Multi-Definitive Perspectives On Order
Association By Similar Definition, From A Given Unique Perspective On Order
Repetitive effective relativity between ADA cell points (when overviewed by an SSM system) inevitably provides simile conduits to solutions and useful extended continuity. Consistent relativity between cell points (within groups of ADAs) in the form of limits, qualifiers, exclusions, inclusions, exceptions, etc.; display cause and effect parameters that are useful in the mechanical deductions of an SSM for dealing with unprecedented ADA cell factors (unknown flux i.e. cause, problem, or opportunity).
Furthermore, within any SSM chain of reference, at the point of any connection, (i.e. a link by simile compare event or perfect compare event via formatted polarization) a simile compare event may be used in the place of a perfect compare event.
A given problem may be solved by the application of a known and tested direct solution formula; or a value polarized reference to a probable solution for a problem, may be accessed by a SimilComp event, perhaps using an SCCatalyst to qualify this reference to parallel continuity.
This selection might have no apparent direct connection with a conventional orderly path toward the isolation of a solution. Whether an ADA formula is logical and reasonable, need not necessarily be determined, only whether (or not) it is effective in real practice.
ADA action structures, formulas, and SCCatalysts will commonly be adopted (by SSM networks), not because of their apparent logical application, but because they are effective a (relatively) high percentage of the time.
3. List Cells
The ADA formatting perspective of a "list-cell," is one example of a reliable (and useful) type of specific relativity among information clusters (ADAs). A list-cell-ADA would contain (at least) one list cell point; this point would contain a list of interchangeable cellular specifics; each specific would be workable (within the complete ADA action), when implemented as the contents of the list cell.
A list-cell-ADA consists of cells that have defined and fixed specifics, with the exception of one cell: this cell would contain a list of optional factors, each factor being effective in use (interaction). A comparison of this group of factors would establish common denominations and parameters.
If an unfamiliar candidate (specific or factor) were considered for use in the position (vessel) of the list cell; these common denominators, parameters, and other aspects of relativity, could be applied to forecasting the probability of an effective cell vessel contents substitution. (This presumes that you have some information about the unfamiliar candidate. In most cases, you would know a great deal about a given radical factor, but may have no history of its use in the ADA list-cell position in question.)
Single cell substitution is a common type of ADA alteration. Consider the case of the primate-entity who sticks a twig in a hole and pulls the twig out with ants (food) on it. This is implementation of the solution portion of a food acquisition event; the problem portion probably being, entity desires food. If the entity "cell substitutes" from this base ADA, it may try this action sequence with a beehive. (Of course, there is no guarantee of complete success.)
The elements selected for cell substitution may be random, or governed by networks that do nothing but recommend and analyze cell substitutions. These networks would be specialists according to the general objective type, and further qualified by specific action, subject and parameters.
Once you understand the kinds of relativity that exist between ADA knowledge structures, that these are tangible artifacts which profile the order within a defined reality; then you discover that solutions for a single given problem might be found by a number of paths. Furthermore, these isolated methods of finding solutions (through their different approaches), are cognitive action ADAs themselves, which may be expanded and improved through mutation, testing and evolution.
D. Combining Simile Conduits And Formatted Links
Simile Bridges To Parallel Order
Such a connection in its most basic form would consist of two polarized isolated ADA structures, with either their positive or negative portions being qualified as "similar" in a comparison event.
Whether this connection is of any relevance, may or may not be known; but such connections will uncover relevant parallel continuity with a frequency that will far surpass a random selection of referrals.
Furthermore, these connections themselves can be defined using a complete spectrum of inclusive/exclusive portraits, with the successful types being recorded and duplicated as priority avenues for future references, repeating (by staying within the inclusive relevant parameters) a successful type of bridging event.
1. Four Primary ADAs Involved In A Polarized Simile Bridge To Parallel IEOrder.
Building Domino Bridges:
A Polarized ADA Chain
To Parallel Information Lines.
a. ADA A is given, the definition
cluster of the flux.
b. ADA B is the historical similar flux.
c. ADA C is the reactionary portion
of the entire historical event.
d. ADA D is the resected reaction
created out of pieces of A and C.
Polarized Formatting Perspectives PFP
Flux And R/O May Be Further Defined As
Three Fundamental Types
Cause and Effect C/E
Problem and Solution P/S
Opportunity and Acquisition O/A
One reason for creating Polarized Formatting Perspectives, such as C/E, P/S, and O/A, is to use these two-poled ADAs as domino bridges to parallel continuity. This value polarization (of an information artifact) is what allows this dominoes-type referencing to access probable (beyond random) relevant continuity, by creating a bridge, from one ADA line (information structure), to another parallel ADA cluster.
A connecting bridge would be comprised of (at least) two polarized event-ADA information-clusters (or dominoes in this analogy). They might be any two event-ADAs that have been formatted in any common polarized perspective, perhaps two problem/solution artifacts (ADAs), representing two different action events, each having a positive solution portion, and a negative problem portion.
A polarized conduit is a reference through a defined format, accessing parallel ordered continuity between event-ADA portions.
A connection may be made because of a similarity that exists between the two negative, or the two positive, factors of two given event-records. If either of these polarized portions is equal or simile-equal to its like-poled counterpart, then there is a higher than random probability, that the two remaining counter portions are related in a useful (relevant) way.
If one of these four factors is completely unknown, with the other three being known, the odd-polarity factor may be adopted as a working frame for the missing counter portion, (again with a relevant reliability far beyond random expectation).
Furthermore, not only the continuity of this known whole ADA, but its relationship and connections to other known ADAs may be found to be relevant and useful as a reference to parallel order.
These "domino bridges" are definable, as with all action or aspects in cognitive space. A detailed portrait of the type of connection, may be attempted. (This portrait may indicate spectrums of inclusivity and exclusivity.) A "domino bridge" of a specific type and description, that is found to be an effective reference (within any given module reality), will be discriminated and duplicated during future referral quests of similar type.
A domino bridge may contain more than two ADA dominoes; some of these connection-links would be created and used solely as a specific kind of linking agent, adopted for this use because of its historic effectivity as such an agent.
Such "links" are discovered either through a simile-reference, or randomly. Their usefulness may be measured (and proven) with isolated exclusion testing techniques.
I can see no limit to the number of polarized, perfect, and simile linking ADAs that may be involved in a single successful chain of reference. However, in cases where no precedent of a bridge in this form is known, one may suspect that the more dominoes (and simile-compares) the bridge contains, the less likely that relevant (useful) parallel order will be accessed.
2. Various Simile Points At Which To Fuse A Connection To IEOrder Continuity
A simile of the current flux might be sought after it has been modified, or an SSM might search for a simile of the (resected) reactionary order. Conduits to parallel order may be found through many available ADA dimensions of perspectives of definition.
RESECTION OF PARALLEL ORDER (default)
The default procedure for resection: Each point of incongruence isolates an "old verses a new" definition particle. When resecting the parallel reactionary (old) order, all occurrences of the old particle are replaced by the respective (corresponding) new (incongruent) particles of the flux.
Revising and Mutating: Theoretical IEO (non-default)
A resection problem in an experienced (evolved) SSM is handled like any problem; old resection-event problems are compared to new resection-event problems. If perfect-matches are not found, similes are referenced, updated and applied to a given resection problem.
The Incongruent Fragment
The key to this resection task, is the ADA portrait of the "difference fragment" that was produced at the incongruent points of the "new flux = old flux" comparison.
A fragment is an ADA structure representing the particles within a given comparison event, that were not perfectly congruent.
A fragment is produced anytime there is an unequal compare between (nearly congruent) ADAs (or SSMs). This fragment is an ADA portrait of the difference (incongruence) between the two flux-ADAs.
This (flux) fragment will be particularly useful and indicative, for example, when compared directly to the fragment produced when one compares the forthcoming new proposed Reactionary Order, to the old (historical) Reactionary Order.
It is valuable to do this kind of reflection on related groups of fragments. This plane of knowledge will provide "back door keys" to decision points at all depths. Intricate SSM task networks, developed specifically for this task will be focused on ADA groups of known fragments and their respective parent ADAs.
A. The Five Elements of a Resection Event
1. The New Flux Definition Artifact.
2. The Closest Known Flux Definition.
3. And Its Attached Reactionary Order Portion.
4. Fragment, Differential From 1 And 2.
5. Most Similar Known Resection Event, defined in the Problem/Solution Format.
Solving Resection Problems
An inclusive through specific (cell by cell) definition of the entire compare event (including the fragment), is the definition of the problem portion (the search source) used for discovering and accessing similar historical resection event(s).
(However, as with all simile selections in cognitive space, in cases where more inclusive cell points are qualified as "equal," it is considered less likely that relevant [effective] parallel order will be accessed.)
In the illustration "Resection of Reactionary Order" a problem is reacted to by resecting and applying the known solution portion of a similar historical problem. New particles replace old particles in the reactionary order, which includes an expected effected, as well as a solution action sequence.
A flux may also be defined as a precursive to an anticipated polarized historical equation (which may include effect-expectations) such as P/S, O/A and C/E.
VII. Testing Solutions on "RAMagination Models"
Before an unprecedented solution is tested on reality, it may be tested within the model of reality that is maintained by the SSM. This processing practice of deliberately creating RAMspace Models for the purpose of testing intra-modularly created solutions, ADAs, and SSMs, is the macro flow of "imagination."
SSM "Imagination"
Man is capable of constructing deliberate specific mind models. He assigns all portions and parameters to his internal 3-dimensional renditions of the reality of a given task environment, and proceeds to "test" solution candidates within this fantasized RAModel. This simple cognitive event, the testing of resected or parallel order on models constructed in computer RAMspace, along with the production of a diverse spectrum of ADA and SSM mutations (a parallel expansion), are the rudimentary cognitive mechanics of "imagination." It may be that the premier cognitive distinction between man and animals lies in this single aspect of man's manufacturing and testing (within an elaborate mind-model) of unique (mutated) ADAs and task networks.
Putting a twig in a hole, for example, is exactly the sort of phallic (random) behavior that you might expect from a primate. An animal could easily stumble onto such an effective and convenient food acquisition plan, without employing deliberate model testing in cognitive space (which I suspect is beyond the capabilities of animals).
Notice that an entity may discover the action of a tool, without having invented it. An entity also may copy any event sequence it is exposed to. Neither of these processes requires RAModel testing of unique self-produced solutions.
VIII. IMPLEMENTING ACTION
A. SHAPING THE SELF AND TARGET ENVIRONMENT
Directions for Shaping (Physical and Cognitive Matter)
A single entity maintains an existence, and exercises shaping force, in both physical and cognitive space.
An entity reaction to a given flux might involve a single command or a string of commands, perhaps with interaction expected (i.e., self triggered target flux anticipated during the string), which may effect the course of the shaping sequence. Isolated configurations of incoming flux strings may also be accompanied by points of interaction, (i.e., shaping commands applied by the entity).
B. Two Kinds of Shaping Force
One Entity Controls Two Kinds Of Shaping Force, One For Each Space.
Entities control two separate types of shaping force, for use in each of the two different kinds of space.
1. Physical Shaping Force: Hands, Voice, Etc.
For Shaping The Tangible World Of Physical Space
(Notice that a target universe may exist within a given cognitive space, in which physical shaping force, such as hands and voice, would be replaced with cognitive shaping force [XIII B. 2. below], the ability to record and alter records and instructions.)
2. Cognitive Shaping Force:
The Action Of Thinking
For Shaping The Structures (Definition Clusters and Processing Circuits) Of Cognitive Space
Physical Space and "Cognitive Space" Have Some Common Features.
Each space contains a type of matter.
Each space contains a type of energy.
Each space has matter in orderly motion (change, flux).
Physical space has laws that govern the interaction of matter and energy in space and time.
Cognitive Space Also Has Laws.
The laws of Cognitive Physics are based on FRSM/SSM designs, mathematics, and the (processing) capabilities and limitations of the CPU/MEM portion of the entity.
C. BOTH FORCES ARE CONTROLLED FROM COGNITIVE SPACE
All Entity Force Originates From A Cognitive Space
Both of these shaping forces are controlled by the entity (as it exists) within the cognitive space.