INTRODUCTION
 

IT begins as all begins - a random thought, perhaps a dream - some fragment of the man within. You take it and examine it and expand upon it. It grows and grows, and suddenly - there it is.

You are climbing a mountain of life - onward and upward, following the winding paths, dodging the pitfalls, skirting the boulders, charting yet uncharted regions - enjoying the beauty and adventure of the search. The height increases, the view broadens, the perspective clears - a few short steps, and you have reached the peak.

And then you must decide whether forever more this shall remain with you alone or whether it shall be communicated to others - and you decide that it shall be communicated.

You are there and you know you are there - but how? You stand at the peak of your mountain and look below upon a complete but undefinable thing. At the base there are so many approaches - so many different yet similar paths - all, in time, ending at your feet.

And so you take this dream - this living breathing piece of you - and chop it up, so to speak, into small finite bits that seem to "fit" together and in this form present it to the people with the hope that someday they may put them all together and see the dream themselves.

The responsibility then falls upon the reader to take these pieces of a living jigsaw puzzle and put them all together. However, even those most adept in this patient but mechanic art shall never find the view in this alone For, in the chopping and the sorting, some small bits are always lost. And so, upon the reader, falls a second, greater burden - to call upon that source which lights the way for him alone and find the missing parts.

Before you, in the following pages, is a kit which we have chosen to call Plan Theory. The bits and pieces are there, neatly packaged in bundles labeled Sections and Chapters, together with instructions for assembly and some oratory to hint of the view to come.

As you proceed through the text, opening each bundle and absorbing its contents, you should realize that each is but a fragment of the whole.

The view broadens, the perspective clears, the extremes fold to the middle - and there it is.
 
 
 

Ever since the dawn of man, individuals over the ages have probed the secrets of the universe. In the course of time, the great philosophers have come and gone, leaving a heritage of theories and predictions for those who followed them. The great masses of the Earth have been enslaved and freed, bought and sold and again sold in the gigantic complex of forces which constitute our environment. Each man in his time chooses one of the many winding paths and begins his journey, slowly climbing the mountain of life.

Let us now thrust our pick into the mountain of life and begin our climb. Let us follow the winding, twisting paths and forge our way towards the peak. The road is not an easy one. Along the way lie the massive traps and pitfalls of life. We shall endeavor to search out these and skirt about them. If we succeed, we shall be one of the privileged few who has had the opportunity to look down from the peak of the mountain upon the masses of the universe and see all things, for the first time, in their true perspective.
 
 
 
 

SECTION ONE
 
 

MECHANICS
 
 
 
 

 
 
 
PLAN THEORY
 

CHAPTER ONE
 
 
 
GENERAL FUNCTIONS
 
 
 
 
 

DEFINITIONS OF STANDARD SEQUENCES

ALPHA SEQUENCE - Alphabetical Order

GAMMA SEQUENCE - Chronological Order

DELTA SEQUENCE- Continuity Order
 
 

BASIC TERMS

To avoid the creation of a loop in the Delta sequence of our definitions, we shall treat the term 'set' as an undefined term in this text. Instead, we say that a SET is a collection of certain elementary components called MEMBERS . These members may be of two basic types, tangible and intangible. We refer to intangible members of a set as DATA and to tangible members, as MATTER. If some of the members of a set are matter, the set may be referred to as a STRUCTURE.

TYPES OF SETS

A set may contain many members, simply one member, or no members at all. If a set contains no members, it is called an EMPTY SET and is symbolized by "0". A non-empty set is said to be FINITE if all of its members can be completely described, listed, cataloged, etc. by ordinary methods; if this cannot be done it is said to be INFINITE. If a set contains all members, i.e., all data and mater in a specified area, it is referred to as a UNIVERSAL SET. In a technical sense, the "specified area" must be "our entire universe", but, in a more general sense, it may be any area.

SUBSETS

A set, A, is said to be a SUBSET of another set, B, if and only if set B contains every member of set A. The prefix "sub-" suggests that there would be at least one member of set B which was not contained in set A. If this is the case, set A is said to be a PROPER SUBSET of set B or, simply a subset of set B. It is possible, however, that every member of set A is a member of set B and every member of set B is a member of set A, i.e., they are identical. Technically, in this case, set A would still be considered a subset of set B but, to distinguish it from the more probable case, it is called an IMPROPER SUBSET.

COMPLEMENTS

The ABSOLUTE COMPLEMENT of a set, A, is that set, denoted by A', which contains every member of the technical universal set which is not contained in set A. The absolute complement, then, is the complement of a set with respect to the Universe. Although this type of complement has definite uses, we will be concerned mainly with the complement of a set with respect to another set, the relative complement. The RELATIVE COMPLEMENT of a set, A, with respect to another set, B, is that set, denoted by A'B, which contains those and only those members of set B which are not contained in set A.

Certain elementary notations are used in set theory, some of which are illustrated by figures 1-1, 1-2, 1-3 and 1-4. References to specific sets in the following discussions refer to these figures.

Sets are usually identified by capital letters of the English alphabet. Average sets, such as set A, are diagrammed as circles and their members (if any) are specified (if desired) by placing their names or identifying symbols within the circle. Universal sets are diagrammed as rectangles and are identified by a symbol placed in the upper left hand corner. In the case of a technical universal set, such as the set in figure 1-3, the single letter "U" is used. In the case of a general universal set, such as that shown in figure 1-4, the symbol "U" is used with a subscript giving the sets' name or identifying symbol.

If it is desired to list the members of a set, they are placed in brackets, e.g., the members of set A would be listed as {a,b,c,d,e}. All members of a set need not be listed if the set has many members and they form some obvious sequence. For example, the set consisting of the letters of the English alphabet could be listed {a,b,c, ... ,x,y,z}, the "..." standing for the omitted letters.

Subsets

When sets having members in common are diagrammed, it is customary to show the sets "mapped over" one another to illustrate their configuration. For example, since set B is a subset of set A, the two sets could be diagrammed either as they are in figure 1-1 or as they are in figure 1-2 but, in figure 1-2 their relationship is more obvious.

Complements

Diagrams are particularly helpful in illustrating complements- especially relative complements. Examples of complements in the figures below are:

Absolute

A' is all data and matter in this Universe except the first five letters of the English alphabet.

Relative

B'A is {a,b}

A'B is {0}

A'C is {n,o}

A'D is {f,g,h,i}

D'A is {a,b,c,d}
 

BASIC OPERATIONS

If one is given a non-empty set, there are only two basic things that one can "do to it". One can either add members to it or delete members from it. We refer to the act of adding members to a set as PROGRAMMING and to the act of deleting members from a set as REPROGRAMMING. When one or both of these operations are performed upon a set and the exact operation(s) are unknown or are irrelevant, we say that the set is MODIFIED.

STATIC STATES

A set is referred to as STATIC if it is not undergoing programming or reprogramming. If the diagrams of two static sets,  A and B, are mapped over one another, there are only three basic configurations that can occur.  The two sets can have no members in common, some members in common, or all members in common.

SPECIAL OPERATIONS

Besides the two fundamental operations we discussed earlier, programming and reprogramming, there are two special types of modification that we will use throughout this text, union and integration.

Union

If a previously empty set is programmed with the members of two sets, A and B, then the previously empty set is said to be the UNION of the two sets, A and B, and is denoted by A U B. Union, then, is a kind of "set addition". In the process of forming set A U B, not necessarily all of the members of the two sets, A and B, were used. If they were all used, i.e., if both set A and set B are subsets of set A U B, then the two sets are said to have been MERGED. However, if set A and/or set B is not a subset of set A U B, i.e., some members were deleted in the process, the two sets are said to have been COLLATED.

Integration

Let us consider the two sets A and D shown in figure 1-4. If we program set D with the members a, b, c, and d (from set A) and we also program set A with the members f, g, h, and i (from set D), then the two sets will become congruent.
Similarly, if we reprogram set A to delete the members a, b, c, and d and we also reprogram set D to delete the members f, g, h, and i, the two sets will also become congruent. Note that in both processes we have been dealing with relative complements;
{a,b,c,d} is D'A  and  {f,g,h,i}  is  A'D. This method of modifying two non congruent sets so that they become congruent is called INTEGRATION.

As we have seen, one may integrate two sets by either programming or reprogramming. These two methods are formally presented in the following properties.

PR-1-1 Integration Through Programming

Given two non congruent sets, A and B:

If set A is programmed with A'B and set B is programmed with B'A, then the two sets, A and B, will become congruent.

PR-1-2 Integration Through Reprogramming

Given two non congruent sets, A and B:

If set A is reprogrammed to delete B'A and set B is reprogrammed to delete A'B, then the two sets, A and B, will become congruent.
 
 

DYNAMIC STATES

A set is referred to as DYNAMIC if it is undergoing programming or reprogramming.

Congruence and Complementary State

Intersection
 

Like static sets, two dynamic sets may also intersect. However, in this case, there are two basic possibilities. Consider the case of the two sets, A and D, shown in figure 1-4. If we agree that both of these sets are dynamic, then members are continually being added to them and/or deleted from them. Let us suppose that set A is programmed with a member and set D is programmed with a member. If the members are congruent, the sets will tend to get "closer together"; if they are not congruent, the sets will tend to get "farther apart". Similarly, if each of the sets is reprogrammed to delete one member they will tend to get closer together if the members deleted were not contained in their intersection and farther apart if they were. In this case, if the latter were true, the two sets would become complementary.

When dealing with dynamic sets, then, it is convenient to split the state of intersection into two separate cases. Two non congruent dynamic sets are said to CONVERGE if they continually approach a congruent state and to DIVERGE if they continually approach a complementary state. If two dynamic sets, A and B, converge, the relationship is denoted by A< B; if they diverge, the relationship is denoted by A > B. Both notations are commutative.

Properties

The conditions under which two dynamic sets will remain congruent or complementary, or will converge or diverge under programming and under reprogramming are given in eight properties which treat all primary cases.

These properties follow, concluding our discussion of set theory.
 

PR-1-3 Invariance From Complementary State Under Programming (Fig. 1-5)

Given four sets, A, A_k, B and B_k, such that no two of the sets intersect:

If, periodically, set A is programmed with a member of A_k and set B is programmed with a member of B_k, then the two sets, A and B, will remain complementary.

PR-1-4 Invariance From Complementary State Under Reprogramming (Fig. 1-6) Given two complementary sets, A and B.

If, periodically, set A is reprogrammed to delete one of its members and set B is reprogrammed to delete one of its members, then the two sets, A and B, will remain complementary.

PR-1-5 Invariance Prom Congruence Under Programming (Pig. 1-7)

Given four sets, A, A_c, B and B_c such that set A is congruent to set B and set A_c is congruent to set B_c:

If, periodically, set A is programmed with a member of set A_c and set B is programmed with the congruent member of set B_c, then the two sets, A and B, will remain congruent.

PR-1-6 Invariance Prom Congruence Under Reprogramming (Fig. 1-8)

Given two congruent sets, A and B:

If, periodically, set A is reprogrammed to delete one of its members and set B is reprogrammed to delete the member which is congruent to that member which was deleted from set A, then the two sets, A and B, will remain congruent.

PR-1 -7 Convergence Under Programming (Fig. 1-9)

Given four sets, A, A_c, B and B_c, such that set A is not congruent to set B and set A_c is congruent to set B_c:
 

If, periodically, set A is programmed with a member of set A_c and set B is programmed with the congruent member of set B_c, then the two sets, A and B, will converge, approaching congruence as a limit.

PR-1-8 Convergence under Reprogramming (Fig. 1-10)

Given two intersecting sets, A and B:

If, periodically, the subset of set A, B'A, is reprogrammed to delete one of its members and the subset of set B, A'B, is reprogrammed to delete one of its members, then the two sets, A and B, will converge, eventually becoming congruent.

PR-1-9 Divergence Under Programming (Fig. 1-11)

Given four sets, A, A_k, B and B_k, such that set A is not complementary to set B and set A_k is complementary to set B_k:

If, periodically, set A is programmed with a member of A_k and set B is programmed with a member of B_k, then the two sets, A and B, will diverge, approaching a complementary state as a limit.

PR-1-10 Divergence Under Reprogramming (Fig. 1-12)

Given two intersecting sets, A and B:

If, periodically, the common subset of the two sets, A and B, set A(intersect)B, is reprogrammed to delete one of its members, then the two sets, A and B, will diverge, eventually becoming complementary.

The set of properties 1-1 though 1-10 are referred to collectively as the SET THEORY PROPERTIES. Because of their importance in the text, we restate them here in a more general form.

PR-1 -1 Integration Through Programming

If two non-congruent sets are programmed with their relative complements, then they will become congruent.

PR-1 -2 Integration Through Reprogramming

If two non-congruent sets are reprogrammed to delete their relative complements, then they will become congruent.

PR-1 -3 Invariance From Complementary State Under Programming

Two complementary sets will remain complementary under programming PROVIDED that no member with which one set is programmed is a member of the other set.

PR-1-4 Invariance From Complementary State Under Reprogramming

Two complementary sets will remain complementary under reprogramming.

PR-1-5 Invariance From Congruence Under Programming

If two congruent sets are programmed with congruent members, then they will remain congruent.

PR-1-6 Invariance From Congruence Under Reprogramming

If two congruent sets are reprogrammed to delete congruent members, then they will remain congruent.

PR-1-7 Convergence Under Programming

If two non-congruent sets are programmed with congruent members, then they tend to converge, approaching congruence as a limit.

PR-1-8 Convergence Under Reprogramming

If two non-congruent sets are reprogrammed to delete members not contained in their intersection, then they converge and eventually become congruent.

PR-1 -9 Divergence Under Programming

If two non-complementary sets are programmed with non-congruent members, then they tend to diverge, approaching a complementary state as a limit.

PR-1 -10 Divergence Under Reprogramming

If two intersecting sets are reprogrammed to delete members contained in their intersection, then they diverge and eventually become complementary.
 
 

THE GENERAL FUNCTION CONCEPT
 
 

Let us consider the case of two sets, A and B. We wish to determine a method for establishing a correspondence between the members of set A and the members of set B. To accomplish this, we introduce a third set, C, and assign to set C the task of performing a certain operation upon the members of set A which will transform each member of set A into a member of set B. We then pair each member of set A with that member of set B into which it was transformed, thus establishing the desired correspondence.
 

Let us agree to refer to set C as a PROCESSOR since its task is to "process" the members of set A. For purposes of identification, let us also agree to refer to set A as the DOMAIN of the processor and set B as the RANGE of the processor. The members of the domain and range of a processor will usually be referred to respectively as DOMAIN MEMBERS and RANGE MEMBERS. The set formed by a specific processor together with its range and domain is called a FUNCTION.
 

We refer to that correspondence established between a member of the domain of a processor and a member of the range of that processor by pairing the domain member upon which the processor performs a certain operation with the range member which results from that operation as an ORDERED PAIR. When it is desired to list ordered pairs, they are presented in the general form (Domain Member , Range Member), the domain member always being placed first. The method in which a given function's processor forms ordered pairs is called the PLAN OF OPERATION of the function.
In a way, one might say that domain members "initiate" the action of a processor since it is these members upon which the processor performs a certain operation. Similarly, one might say that range members "terminate" the action of a processor since these members are the results, so to speak, of the process.
 

SPECIAL TERMS

In general discussions, the exact members of the domain and/or the range of a given processor are irrelevant. In such cases, we specify that the domain and/or the range of the given processor is to be considered  to indicate that it may (but not necessarily does) contain any member of the technical universal set.

A set so constructed that each of its members is also a member of one or more of the three basic parts of a function, i.e., a subset of a function, is called a PROGRAM.
 

RELATIVITY

The range member with which a given domain member is paired is entirely relative to the processor doing the pairing. Different processors have different plans of operation and form different ordered pairs. Because of this fact, an ordered pair " itself" has no meaning at all; one must know the processor which formed it for it to have any significance. Hence, when ordered pairs are listed, if the processor is not obvious from the context, some form of notation must be employed which will show
the processor.  We shall use two forms of notation in this text, the statement notation and the standard function notation.

DIAGRAMS

Processors are diagrammed as triangles and their members are specified (if desired) by placing their names or identifying symbols within the triangle. Domains and ranges of processors are diagrammed as are average sets.
 

STATES

In a function, it is the duty of the processor to pair every domain member with a range member. A given processor may or may not be capable of doing this. If a processor is capable of assigning a range member to every domain member it encounters, then the processor is said to be NORMAL. If, however, there exists any domain member to which the processor is incapable of assigning a range member, then the processor is said to be ABNORMAL.
 

If a processor is abnormal, the cause can probably be traced to two very basic reasons. First, of course, it is possible that the right range member simply does not exist. However, it is also possible that some subset of the processor, by its existence, is preventing the processor from choosing a range member which it would freely pair with the domain member if the subset were deleted. We refer to such a subset as an INHIBITOR.
 

It is often desired to change the state of a processor, i.e., force a normal processor to become abnormal and visa versa. Basically, the state of a processor can be changed by modifying it and/or its domain. Many specialized methods can be developed once one becomes familiar with a specific case.
 
 

ABBREVIATIONS

Because certain basic terms in this concept are used frequently throughout the text, certain standard abbreviations have been chosen. The terms and their abbreviations are:
 
 

The three basic parts of a function - the processor, the domain of the processor and the range of the processor - are all variables. We may define the processor so that it will operate any way that we desire it to operate and we may specify the members of the domain and range at our option. It should be obvious that virtually everything in existence can be put into the form of a function by carefully defining these variables - from the coffee grinder in the corner drug store to the most complex organic structures In this chapter, we will confine ourselves to general types of functions and will then expand upon these basic concepts in later chapters.
 
 
 
 
 

GENERAL STATIC FUNCTIONS

Since the processor of a function set, it may, like any set, be either static or dynamic. We refer to a function whose processor is a static set as a STATIC FUNCTION.
TYPES

Intuition would suggest that a given static function would pair different domain members with different range members, i.e., that the range members chosen would be relative to the domain members processed. It is possible, however, that a processor would pair every domain member with the same range member. We distinguish between these two possibilities by referring to a static function whose processor forms ordered pairs such that the range members of all ordered pairs formed are congruent as a CONSTANT STATIC FUNCTION and referring to a static function whose processor forms ordered pairs such that the range member of each pair is relative to the domain member with which it is paired as a VARIABLE STATIC FUNCTION.

PROPERTIES
Static Function Properties

All static functions conform to the following four properties which we refer to collectively as the STATIC FUNCTION PROPERTIES. 
 

Application of Set Theory Properties

Since, as we have said, the processor of a function is a set, we may use any applicable set theory properties in dealing with it. In the case of the static function, we are limited to the two integration properties, integration through programming and integration through reprogramming. However, these two properties are very useful in the light of the first two static function properties. These two properties tell us the characteristics of functions whose processors are congruent and the integration properties tell us how we can make two or more processors congruent.

Special Properties

Often, we are confronted with a situation in which we know some, but not all, of the three basic parts of a given function. Under certain conditions, the unknown parts can be determined; these conditions are given in the following properties

Besides the two possibilities covered by PR-1-15 and PR-1 -16, it is also possible that one would know the ordered pairs that a processor had formed but not the processor. We refer to the act of determining a processor which will form a given set of ordered pairs as RATIONALIZATION.

PR-1 -17 The Rationalization Property

Let F_s be a static function, P_s be its processor, D_s be the

domain of P_s and R_s be the range of P_s. When every member of
D_s
has been processed by P_s, P_s will have formed x

ordered pairs.
If n of the x ordered pairs formed by P_s of F_s are known,
then the configuration of P_s can be approximated, the approximated configuration approaching the actual configuration as n approaches x.
 
 
 

In purely theoretical matters, it is convenient to use the standard set theory definitions of congruence and complementary state; however, in applied discussions, such as we will encounter later in the text, it is rather difficult to simply "look" at a processor and see if every member of it is a member of another processor and vice versa.

Consequently, when the set theory definitions become impractical, some other form of definitions must be derived to replace them. When this occurs, we shall use a form centered around the ordered pairs which the processors in question form. From static function I and static function III we know that if two processors process the same domain member, they will pair it with congruent range members if they are congruent and non-congruent range members if they are complementary. We can say, therefore, that two processors are congruent if the sets of ordered pairs which they form from the same domain members are congruent and that two processors are complementary if the sets of ordered pairs which they form from congruent domain members are complementary.

Intersection

When a processor forms an ordered pair, not necessarily all of the processor's members were responsible for the formation. That subset of a processor which is actually responsible for the formation of a given set of ordered pairs is said to be the RELATIVE SUBSET of the processor with respect to the given set of ordered pairs. If two processors intersect, the ordered pairs formed from a given domain member will be congruent if the relative subset is contained in the intersection and non-congruent if it is not. When dealing with functions, then, intersection is simply a combination of congruence and complementary state. Consequently, if two processors intersect, it is convenient to just "split them up" into sufficiently small relative subsets and label the subsets "congruent" or "complementary".

The concept, of which this "idea" is a part, is commonly called COMPARTMENTALIZATION.

SUMMARY

Because of the importance of the properties presented in this article, we restate them here in a more general form.

PR-1-11   Static Function I

Congruent processors will pair congruent domain members with congruent range members.

PR-1-12 Static Function II

Congruent processors will form ordered pairs with non-congruent range members when the domain members processed are not congruent.

PR-1-13 Static Function III

Complementary processors will pair congruent domain members with non-congruent range members.

PR-1-14 Static Function IV

Complementary processors will form ordered pairs with congruent range members only if the domain members processed are not congruent.

PR-1-15 The Prediction Property

The nature of a function's range may be determined through knowledge of its processor and domain.

PR-1-16 The Historical Property

The nature of a function's domain may be determined through knowledge of its processor and range.

PR-1-17 The Rationalization Property

The nature of a function's processor may be determined through knowledge of the ordered pairs it has formed, the accuracy being relative to the quantity of ordered pairs known.
 
 
 

A DYNAMIC FUNCTION is a function whose processor is a dynamic set. Since the processor is dynamic, it is continually undergoing modification. The changes which occur in the processor may or may not have some relation to the domain members which are processed. On the basis of the relationship which exists, we subdivide dynamic functions into three basic types as follow:

An INDEPENDENT DYNAMIC FUNCTION is a dynamic function such that the changes which occur in the processor have no relation to the domain members which have been processed.

A TRANSITIONARY DYNAMIC FUNCTION is a dynamic function such that the changes which occur in the processor are partially relative to the domain members which have been processed

A DEPENDENT DYNAMIC FUNCTION is a dynamic function such that the changes which occur in the processor are relative to and only to the domain members which have been processed.

We have little use in this text for the independent dynamic function and the transitionary dynamic function and we shall not discuss them further. We devote the remainder of this article to the properties of the dependent dynamic function.

DEPENDENT DYNAMIC FUNCTIONS

Dependent Dynamic vs. Static

Let us consider the case of a static processor, P_s. P_s encounters the domain member D₁ and pairs it with the range member R₁. The process then ends. If P_s would again encounter D₁, then it would again pair it with R₁ - over and over again.

Now, let us consider the case of a dependent dynamic processor, P_d. P_d encounters the domain member D₁ and pairs it with the range

member R₁. Then something "happens" to P_d. By definition, it undergoes some change which is relative to and only to D₁. D₁ has "left its mark", so to speak, upon P_d. If P_d would again encounter D₁, it would not necessarily pair it with R₁. It could, of course, but it need not - for P_d has changed; compared to the P_d a few moments ago (before D₁ was processed) it is a different processor.
 

Special Relativity

As the processor of a dependent dynamic function forms an ordered pair, certain members come into being whose characteristics are relative to the domain member being processed. When the ordered pair has been formed, these members become part of the processor and contribute to the formation of all future ordered pairs. As the processor forms more and more ordered pairs, it receives more and more such members. We refer to these members which have been added to the processor of a dependent dynamic function because of domain members which have been processed as the processor's PROGRAMMING.

In any function, the range members which are paired with a given set of domain members (hence, the ordered pairs which are formed), are relative to and only to that function's processor. But, in a dependent dynamic function, the processor changes every time it forms an ordered pair because it receives new programming relative to the domain member it just processed. Because of this, the processor of a dependent dynamic function is actually relative to the domain members it has processed (hence, the ordered pairs it has formed).

Since ordered pairs are relative to the processor (in any function) and the processor is relative to all previous ordered pairs formed (in a dependent dynamic function), one may conclude that, in a dependent dynamic function, a given ordered pair is actually relative to all ordered pairs which were formed before it.

We refer to a sequence of events, each succeeding phase of which is determined by all preceding phases as a CONTINUUM. A subset of a continuum, i.e., some part of the sequence, is called an INTERIM. We say that the ordered pairs formed by the processor of a dependent dynamic function form a continuum when placed in Gamma sequence.

Notation

Because of the significance of the sequence in which ordered pairs are formed in a dependent dynamic function, the conventional notations we discussed earlier are usually of little value. We therefore expand the standard function notation so that the additional variables are taken into consideration. We shall present ordered pairs formed by dependent dynamic functions in the general form

The specification of a definite interim allows us to omit any preceding or succeeding operations in which we may not be interested. The specific applications of this notation, the form may be abbreviated to exclude any unnecessary material; however, as this is done, one approaches the original standard function notation.

Application of Static Function Properties

As we have stated, a dependent dynamic function's processor undergoes programming upon completion of the formation of each ordered pair. During the interim between the time it completes the formation of an ordered pair and the time it begins to process another domain member, however, it undergoes no modification. We refer to this interim as an INSTANT. During each instant, the processor is static and, consequently, all static function properties are applicable.
Application of Set Theory Properties

Since we are dealing with dynamic sets, all ten set theory properties apply. Of special interest, however, are the four properties which deal with dynamic sets undergoing programming, for, as we have said, a dependent dynamic function's processor undergoes programming each time it forms an ordered pair. To see the possible applications more clearly, we restate these properties here, applied to our discussion.

Invariance From Complementary State Under Programming.

If two dependent dynamic functions have complementary processors, then they will probably remain complementary if the processor's domains remain complementary.

Invariance From Congruence Under Programming

If two dependent dynamic functions have congruent processors, then they will remain congruent if the processors process congruent domain members in identical sequences.

Convergence Under Programming

If two dependent dynamic functions have non-congruent processors, then they will converge if the processors continue to process congruent domain members in identical sequences.

Divergence Under Programming

If two dependent dynamic functions have non-complementary processors, then they will tend to diverge if the processor's domains remain complementary.

The second property given is absolute; the others are approximations. In general, the probability is in favor of their occurrence, but they not necessarily true in all cases. However, in applied discussions, all are quite useful.

The Projection Property

The static function properties, which may be applied to dependent dynamic functions during instants, become much more useful when one has a method of "following" the processor as it changes from instant to instant. The Projection Property is designed to fill this gap.

PR-1-18 The Projection Property

Let F_v be a dependent dynamic function and P_v be its processor. P_vat time = T can be determined if P_v at time = (T-X) is known and all ordered pairs formed by P_v during the interim X are known in Gamma sequence.
 

Change of State

Like any function, a dependent dynamic function may be normal or abnormal. However, when one discusses methods of changing the state, a few more factors become relative. In all functions, state may be changed by modification of the processor and/or its domain. In this case, however, the processor is continually undergoing modification, this modification being relative to the domain members processed. Consequently, one might be able to change state simply by changing the sequence in which the domain members are processed.

Again, more sophisticated methods are best developed when one is dealing with a special case, but the fact that a processor is dynamic adds many additional possibilities.
 
 
 

POWER

Interpretation

We are given a certain dependent dynamic function and we wish that function's processor to choose from its range a certain range member and pair it with some domain member. It is not relevant which domain member is used; it is relevant only that a certain previously selected range member is paired with a domain member. The General Power Axiom tells us that whatever range member we choose, we can find a domain member with which that function's processor will pair it.

When the General Power Axiom is applied to a special case, there are two basic possibilities.

First, it is possible that, for the range member we have chosen, there is a domain member which, if processed now, would be paired with it. If this is the case, then Z need only consist of one member.

Secondly, however, it is also possible that, at present, no domain member exists which the processor will pair with our chosen range member. In this case, it is necessary to modify the processor so that a domain member does exist. We recall that, in dependent dynamic functions, the processor is continually changing and that this change is relative to the domain members processed. To modify the processor, then, we define a subset of the processor's domain, Z, such that its members, when processed in a certain sequence, will change the processor in such a manner that the last domain member of the sequence will be paired with our chosen range member.
 

CONTROL

When a function's processor encounters a domain member, it "takes" the member and performs a certain operation upon it. At the conclusion of this process, the domain member has been transformed into a range member. Range members, then, are the results of the operations of a processor - the things they "produce", so to speak. We wish to determine a basic method by which the range members yielded by a processor can be controlled.

The General Power Axiom tells us that, in a dependent dynamic function, for any range member we choose, there exists a domain member which, if processed, would be paired with the chosen range member. The axiom tells us that this resource exists, but not how to tap it. Obviously, if we knew the "right" domain members to use, we could control the function.

The range member which is formed from a given domain member is relative to the processor. Hence, if we are familiar with the method in which a given processor forms ordered pairs, we can figure out what domain member need be processed to yield a certain range member. If our examination reveals that no domain member exists which will do this, we can change the processor (of a dependent dynamic function) so that a domain member does exist by allowing it to process certain carefully selected domain members. Once the processor has been sufficiently modified, we can obtain our desired range member.

The fact that the processor of a dependent dynamic function changes each time it processes a domain member provides a convenient method of modifying it. However, the sane results could be obtained by simply "taking" the processor and directly modifying it so that it conforms to our wishes. In this case, since the changes would not now be completely relative to the domain members processed, the function would become a transitionary dynamic function.

Similarly, one could apply the General Power Axiom to static functions by arbitrarily modifying their processors so that desired range members could be obtained. During the period of modification, the static functions would become independent dynamic functions, their change being relative to the person or thing doing the modifying (as opposed to the domain members processed).

In all of these cases, control of the range members produced has depended upon an intimate knowledge of the inner workings of the processor of the function involved - the processor's plan of operation. Once this is known, many elaborate methods of control can be derived.

So far, we have discussed functions - static and dynamic. But, when we use the term "function" in its most general sense, what do we mean? As we have said, virtually everything can be put into the form of a function. Consequently, virtually anything can be controlled if one is intimately familiar with the method in which it operates.
 
 

We formally state these conclusions in the General Control Theorem.

T-1 -1 General Control Theorem

PLAN THEORY

SECTION ONE

CHAPTER TWO

INORGANIC FUNCTIONS
 

In Chapter One we went through certain basic concepts in as purely an abstract and detached manner as possible. We will see these concepts, again and again through the text.

In this chapter, we shall apply the pure notions of Chapter One to that class of things which we call Synthetic structures. By SYNTHETIC, we refer to those things which are a product of man as opposed to a product of nature.

In Chapter Three, we will discuss Natural structures.
 
 
 

INORGANIC STRUCTURES

TYPES

We divide Inorganic Structures into three basic types, The "tool', the "machine", and the "computer".

We refer to a TOOL as an inorganic structure capable of performing a limited number of specific static functions ONLY with the assistance of a machine, computer, or organic structure.

We refer to a MACHINE as an inorganic structure capable of performing a limited number of specific static functions.

We refer to a COMPUTER as an inorganic structure capable of performing any static operation.
 

The Computer is mainly concerned with the processing of Data, and the Tool is mainly concerned with the processing of matter. The Machine, the transient class, is concerned a little bit with both functions.
 
 
 

THE INORGANIC FUNCTION CONCEPT

BASIC TERMS

Recall from Chapter one the notion of a processor, domain, and range of a function and the ordered pair.

An INORGANIC FUNCTION is a function whose processor is either a computer or a machine or a tool, or, more technically phrased, a function whose processor is an inorganic structure.

A domain member of an inorganic function is called a PROBLEM. A range member of an inorganic function is called a SOLUTION,

The ordered-pair formed by an inorganic function is called a DECISION. This ordered-pair has the general form (P,S), where P a specific problem and S a specific solution.

TYPES OF FUNCTIONS FORMED

Inorganic Functions can be classified as static or dynamic. Under static, there are constant and variable types. Under dynamic, there are both dependent and independent.

STATES

The ability of an inorganic structure to continuously perform its intended function is called TOLERANCE. An inorganic structure operates normally within the constraints of TOLERANCE and abnormally elsewhere, where malfunctions occur.
 
 
 

PROGRAMMING

In programming, the basic relevant factors are the Set, the Sequence and the programming method.

The two basic types of programming are DIRECT PROGRAMMING and INDIRECT PROGRAMMING.
BY DIRECT PROGRAMMING, we refer to the case when domain members need not be interpreted to be processed, i.e., domain members are already in the "Native language", so to speak, of the processor.

BY INDIRECT PROGRAMMING, we refer to the case when domain members must be interpreted before they can be processed, i.e., they are not in the so called "native language".

When dealing with the COMPUTER, we call direct programming the OBJECT PROGRAM and we refer to indirect programming as the SOURCE PROGRAM.
 

PROCESSING

The stages in processing consist of Interpreting, processing and coding.

We call that subset of a processor which transforms indirect programming into a form which the processor can comprehend the INTERPRETER.
We call that subset of a processor which transforms indirect programming which has been processed from the processor's "language" to the language in which it was programmed the CODER.

In processing, when a problem is encountered, it may be paired with a solution if a sufficient solution exists. If a sufficient solution does not exist, the problem may be stored.
If the requested rate of processing exceeds tolerance, we may see an overload condition develop.

Relevant factors in processing, by summary, are the notion of programming and consequences relative to programming rate. And there is the consideration of the processor's contents and tolerance.
 
 

In inorganic structures, all things relative to the structure are relative to its programming.

POWER

Control methods for inorganic structures may be obtained by applying the appropriate properties for general functions from Chapter one. Specifically:

METHODS OF COMPARING PROCESSORS
For Comparing Use:

STATIC FUNCTION I
STATIC FUNCTION II
STATIC FUNCTION III
STATIC FUNCTION IV

METHODS FOR DEVELOPING KNOWLEDGE

For Developing Use:

PREDICTION PROPERTY
HISTORICAL PROPERTY
RATIONALIZATION PROPERTY
PROJECTION PROPERTY

METHODS OF CONTROLLING PROCESSORS

For Control use set theory properties 1-1 through 1-10 inclusive.
 
 
 

SYNTHETIC ORGANIC STRUCTURES

A synthetic organic structure produced entirely by man from previously inorganic materials is called an ANDROID.

In Chapter Three we will be discussing natural organic structures, and we will introduce the concept of a special characteristic of these structures which we call "Identity".

Inorganic structures do not possess this property. ANDROIDS are a transient class between inorganic structures and natural organic structures.
The notion of the ANDROID class and the implications of comparisons between inorganic structures, ANDROIDS, and natural organic structures present interesting philosophic problems which are covered later on.
 

PLAN THEORY

SECTION ONE

CHAPTER THREE

NATURAL ORGANIC FUNCTIONS
 
 
 
 

In this chapter we will discuss NATURAL functions. When we say NATURAL we refer to a product of nature as opposed to a product of man. Products of man are called SYNTHETIC, and were discussed in chapter two.
 
 
 

In Chapter Two, we discussed Computers, Machines, and Tools and we touched on the notion of a type of synthetic organic structure called an Android.

In this chapter, we will be discussing Individuals. Individuals are not Computers, Machines, or Tools - and they are not Androids. However, certain patterns of operation seen in Individuals, can be duplicated by constructing an analog model using Computers, Machines, and Tools. And certain other patterns of operation cannot be explained by such analog models.

We wish, then, to introduce a new term, which we call IDENTITY, and to define IDENTITY by exclusion in the following manner: Let set A be the. set of Computers, Machines and Tools together with all things relating to them, physically and abstractly and Let set B be the set of all human beings, together with all things relating to them, physically and abstractly. Now consider the set A'B, the relative complement, or the set of things in set B which are not in set A. The things in set A'B we call IDENTITY.

We say that an INDIVIDUAL is a natural organic structure and possesses IDENTITY. And we say that an ANDROID is a synthetic organic structure and does not possess IDENTITY.
 
 
 

BASIC GENETICS
In set theory format, we can say that naturally occurring organisms are formed as a result of the intersection of two parent sets, representing parents of the new organism.

We say in a physical sense that a structure composed of GENETIC KEYS provides information. The information is in the format of a design of these GENETIC KEYS and so the program is the GENETIC KEY DESIGN PROGRAM (KDP). There are relatively few GENETIC KEYS as compared to the possibilities of the design of these " keys".

GENERAL CONCEPTS IN STRUCTURE

Organic structures form dependent dynamic functions and the concept relating to this that we wish to note here is that people change from day to day. IDENTITY, or the notion we evoke by using this word, has been basically discussed. Now, we will be a bit more practical, and say that in the general structure, we have those things which exist at the instant of conception, and those things which exist at some later point in time. We use Identity to refer to those things existing at the moment of birth and the word PROGRAMMING to refer to those things coming later, as time passes. The PROGRAMMING which is mass-related is called BIOLOGICAL and the programming which is data-related is called PSYCHOLOGICAL.

BIOLOGICAL PROGRAM

The BIOLOGICAL PROGRAM consists of ACTIVE MATTER AND DORMANT MATTER, and Identity. The active matter is biological programming capable of easily performing its intended function and the dormant matter is that biological programming which is not capable of easily performing its intended function, at this time.

In the figure below, we schematically represent this idea and we call this structure, consisting of mass arranged this way, the BODY
 
 
 
 
 
 

PSYCHOLOGICAL PROGRAM

The PSYCHOLOGICAL PROGRAM consists of CONSCIOUS DATA AND UNCONSCIOUS DATA and Identity. The conscious data is that psychological programming that is easily recalled and the unconscious data is that psychological programming that is not easily recalled, at this time.

In the figure below, we schematically represent this idea and we call this structure, consisting of mass arranged this way, the MIND.

THE GENERAL CONCEPT

From the theoretical ideas of Chapter One, we now model a concept for organic functions.

A function whose processor is an organic structure is called an ORGANIC FUNCTION. In this function we refer to domain members as STIMULI and to range members as REACTIONS. We abbreviate Stimuli "S" and Reactions "R" and we call the ordered pair formed, in the form "(S,R)" a DECISION.

Certain Stimuli, called DRIVES, are common to all organic structures. The fundamental DRIVES are:

1. Desire for an energy source.

2. Desire to exist within certain environmental parameters.

3. Desire to continue

THE BIOLOGICAL CONCEPT

In the Biological Concept, the Biological Processor is the body. The process whereby the body makes decisions paring stimuli with reactions is called WORK. In doing work, we note a by-product which we call HEAT.

Bodies operate in normal and abnormal states. The notion of TOLERANCE, with respect to the biological processor is the concept that work and its by-product, within tolerance, constitute a normal state and that when tolerance is exceeded an abnormal state results, the ultimate form of which is DEATH.

THE PSYCHOLOGICAL CONCEPT

In the Psychological Concept, the Psychological Processor is the mind. The process whereby the mind makes decisions pairing stimuli with reactions is called DISCRIMINATION. In this decision-making process, we note a by product which we call FRUSTRATION.

Minds operate in normal and abnormal states. The notion of TOLERANCE, with respect to the psychological processor is the concept that DISCRIMINATION and its by-product, within tolerance, constitute a normal state and that when tolerance is exceeded an abnormal state results, the ultimate form of which we call INSANITY. We note a condition which we call HAPPINESS well within tolerance and a condition called FRUSTRATION in the neighbor hood of tolerance.
 
 
 

During life, natural organic structures encounter programming. This programming is biological and psychological.

We want to discuss certain characteristics of programming which are especially relevant.

In programming, the main relevance can be grouped into the areas of the (1) set which is transmitted, (2) the sequence of the members, i.e., order of transmission in time, and (3) the method of transmission.

We are interested in the transmitted set for obvious reasons, and specifically, the contents of the set. Programming may be pure stimuli, in the form "Go do", but in a more realistic look we usually find stimuli, paired and stimuli, unpaired; so programming contains decisions (made elsewhere) with stimuli (decisions not yet made). Special programming consists of drives, which we listed earlier. Drives must be dealt with, because they are a necessary condition for survival.

Regardless of what is in a set of programming, the sequence of the program in time has essentially equivalent merit or weight. This is due to the theoretical concept of a dependent dynamic function which was discussed in Chapter One, which is more obvious here from a practical standpoint. Since, as stimuli are encountered and processed, there is a change in the organism, given a program and a second program with the same contents but different sequential order, there would be a completely different end result if two completely identical organisms were given these programs.

Our last point is certain differences in the methods by which programming is received. These are more obvious with psychological programming. Mainly there are direct and indirect methods, which are intuitively obvious. The direct methods take the form "Now, Look" where there is an inward or outward motivation to accept this program and then there are indirect methods such as passive observation with minimum motivation (Now, Look) where information lust "comes".
 
 
 

We now wish to turn our attention to a special characteristic of indirect psychological programming. Comprehension of this concept requires a certain amount of insight which the reader should have. This discussion parametrically defines the concept, which we have chosen to call COLORING.

DEFINITION:
We say a COLOR is a plane or level of communication which exists among the members of a subset of a society because a set of data exists in the intersection of the memories of the members of the given subset which does not exist in the memories of the remaining members of the given society.
The ability of an organism to comprehend the various colors which exist in its environment is called DENSITY. COLORS are rated on a scale from high to low representing a band of degree of obscurity from most to least. We say low DENSITY to imply high perception and high DENSITY to imply low perception of these levels.

DENSITY ratings can be absolute or relative. ABSOLUTE DENSITY ratings refer to the density of an organism with respect to an established or fixed static standard. The concept of RELATIVE DENSITY refers to the density of a given organism with respect to the density of another organism. The RELATIVE DENSITY of an organism, A, with respect to another organism, B, is that quantity of colors which organism A can comprehend above or below, denoted by + or - respectively, that quantity of colors which organism B can comprehend.

Continuing, we introduce the concept of OBJECT and PATTERN. LOGIC is a set of data related and oriented around an object and/or the methods to be used in attempting to achieve the object. We call OBJECT LOGIC a set of data oriented around a real or imaginary OBJECT which is to be achieved, i.e., the "end" as opposed to the "means". We call PATTERN LOGIC a set of data oriented around the method to be used in achieving a real or imaginary object, i.e., the "means" as opposed to the "end".

To get formal, if we make up a table of colors and arrange them in order by sophistication and start with, say, 00 at the low end and end with 99 at the high end, we can set up a nomenclature in the form

L xx t

where L is an identifier signifying this coding system, xx is the appropriate two-digit number from the scale, and t is an identifier for the type, say P, for pattern; O for object; M, for a mixed combination; and M, for an unknown type. For example, in the nomenclature, we would read L07P as "Seventh Color Pattern Logic".

Now, getting a little mathy, we can write a definition for the concept of PERCEPTIVENESS as

PERCEPTIVENESS = 1/DENSITY and

we can write a definition for the concept of APTITUDE as

APTITUDE = dp/dt where P is Perceptiveness and t is time.
 
 
 

STAGES IN PROCESSING

Processing is basically a three part process. In the first part, there is the notion of INTERPRETING. This is the idea that before anything can be done with a stimuli, its existence must be noted and it must be recognized. After this encounter/recognition process the stimuli is handled and a reaction sought. Then there is a final stage called CODING where a format for the expression of the decision is formulated.

POSSIBILITIES IN PROCESSING

We use the term PROCESSING to imply all these events. Taking a random stimuli, one can systematically trace through the process and note various possibilities. Consider a stimuli just encountered. Now, ideally, it will be pared with a reaction. But suppose a sufficient reaction does not exist. Then the Stimuli could be stored, waiting for some later time when a suitable reaction may come to exist. There is also the notion that some type of INHIBITOR may exist, blocking a reaction at this time.

Finding reactions to satisfy stimuli in a routine manner is a normal condition with everything running smoothly. However, things do not necessarily run smoothly in life processes (or most anywhere else) all the time and so we want to look at predictable consequences when routine is not the case. If our stimuli cannot be pared, they will have to be stored. But this is not always possible. One definition of the condition of DEATH is that death occurs when an organism encounters something it cannot deal with (pair, store) and also cannot ignore. BIOLOGICALLY, we cite by obvious example the case of some disease which the immune mechanism cannot handle. The mechanism cannot say "Wait, now until I figure out what to do" if it does not figure out what to do, the body dies. PSYCHOLOGICALLY, things follow this model to a point with anxiety and frustration increasing towards the Tolerance point as a function of time as long as the condition exists.

OVERLOAD CONDITIONS

Processing proceeds at a definite rate. We call the rate at which the processor of an organic function processes the stimuli it encounters INTELLIGENCE. Getting a bit mathy again we define the concept of EFFICIENCY as (INTELLIGENCE) x (DENSITY). In an overload condition, the relative factors in processing combine in contribution to the condition. The relative factors are the information (contents) en the processor, the DENSITY, the INTELLIGENCE, and the TOLERANCE level. One can see, how by taking various situations and changing these factors, that overload conditions can occur in a variety of ways.

SUMMARY - CHART

INTRODUCTION

CHANGE OF STATE is the phrase we use to mean the change from a normal to an abnormal condition or vice versa. In this section, discussing natural organic functions, or, more plainly, real people, we want to go through some basic methods of doing changes in state - based on ideas presented previously. By presenting this discussion, methods of applying these previous ideas can be seen. Also, parallels can be drawn to similar analogous situations with models which are not organic functions.

SYNTHESIS OF NORMALITY

A system goes to an abnormal state mainly because a sufficient reaction does not exist or inhibitors exist or there is an overload condition in the processor. For the case of a sufficient reaction not available, one could supply the reaction or remove the stimuli which are involved. In the case of inhibitors, you can reprogram to remove them -or remove the stimuli that are causing the situation to be relevant. In an overload, you look for methods to increase intelligence or decrease programming rate.

The four basic methods are to remove stimuli, add reactions, remove inhibitors and increase intelligence. Now let us expand a bit.

To remove stimuli, one may reprogram domain, increase the density of the interpreter, and increase the color level of the stimuli.

To add reactions, program the processor with decisions that will increase knowledge and/or motivations to change. Also, you may change the sequence of transmission and/or the method of transmission.

To remove inhibitors you can reprogram to delete or program to neutralize.

To increase intelligence, program to increase knowledge with a view towards the idea that "practice makes perfect" and the notion that the more use is made of the processor, the higher the intelligence, in time.

SYNTHESIS OF ABNORMALITY

Synthesis of abnormality, or purposely causing destabilization, is simpler than synthesis of normality - following the general rule that it is easier to destroy than create.

Basically, one can add new stimuli, modify the processor so it cannot handle existing stimuli, or change the nature (color level, e.g.) of existing stimuli so that the change favors destabilization.

Modifications would have the general form of techniques which would decrease intelligence, decrease density, and decrease tolerance with the addition of inhibitors.

Methods of changing the nature of existing stimuli would be to change the sequence of the stimuli, increase or decrease color level and accelerate rate of programming.
 
 
 
 
 

THE NORMAL SOCIAL PATTERN (NSP)

It is often desirous to speak in terms of generalities. In Natural Systems, this is accomplished by use of the Normal Social Pattern. In general, the NORMAL SOCIAL PATTERN is the set of basic desires common to all organisms. What this set contains is dependent upon how it is defined. We shall rely upon four basic methods of doing this, each of which is defined below. In future reference, the abbreviation "NSP" will be used for Normal Social Pattern and the four subdivisions shall be abbreviated as shown below.

Definition (TNSI)

The TECHNICAL NORMAL SOCIAL PATTERN by INTERSECTION shall be the set formed by the intersection of the Identities of all Individuals in existence. Abbreviation: TNSI

Definition

The APPLIED NORMAL SOCIAL PATTERN by INTERSECTION shall be the set formed by the intersection of the Identities of all Individuals in a given society or culture. Abbreviation: ANSI

Definition

The TECHNICAL NORMAL SOCIAL PATTERN by MAJORITY shall be the set formed by the data common to over fifty per-cent of the Identities of all Individuals in existence.

Abbreviation: TNSM

Definition

The APPLIED NORMAL SOCIAL PATTERN by MAJORITY shall be the set formed by the data common to over fifty per-cent of the Identities of all Individuals in a given society or culture.

Abbreviation: ANSM

Discussion

At present TNSI is an empty set and the pattern is not defined. Taking into consideration only the inhabitants of our planet would reduce the set to virtually nothing, and the further consideration of all organisms in existence finishes the job.

ANSI exists if the application is made to a sufficiently small enough society.

If TNSM exists at all, it is not large enough to allow the formation of any worthwhile patterns and the probability is that it does not exist at all.

ANSM is used today by psychologists as a basis for normal behavior. The set is applied to this country usually, and can be found listed as the set of "Basic Human Needs" in many texts. Conformance to it indicates that the probability is in favor of the organism being normal.

The two patterns determined by majority, TNSM and ANSM, are simply expressions of basic trends. By definition, they indicate what the majority of the people have in their Identity. Because the average person does or does not have a certain characteristic in his Identity is not a valid reason for the assumption that a specific person should or should not have it. It is merely a statement of probability. The fact of whether a person is normal or not rests solely with the person internally. The confusion of the terms "average" and "normal" results in a philosophy that is unsound.

The two patterns determined by intersection, TNSI and ANSI, are valid with respect to all organisms in the defined set. Since TNSI does not exist, we are left only with ANSI. ANSI is useful when applied to small cultures. It gives us a valid picture of the basic desires of the members of the culture. The NSP is only completely valid, however, when it is used in the form of ANSI and applied to a specific Individual. When this is done, the pattern is identical to his Identity
 

THE GENERAL SOCIAL PATTERN (GSP)

Whenever it becomes necessary to speak in terms of generalities about a social structure, the group specifically, we will use a plan called the General Social Pattern (GSP). GSP is the set of decisions made by the processors of organisms and is, hence, the set of things that organisms are currently doing as opposed to NSP which is what they want to do and to DPP which is what the powers that be say they are supposed to do. (DPP follows below) GSP is divided basically into four subsets, the definitions and abbreviations for which are shown below.

Definition TGSI

The TECHNICAL GENERAL SOCIAL PATTERN by INTERSECTION shall be the set formed by the intersection of the sets of decisions of all organisms in existence. Abbreviation: TGSI

Definition AGSI

The APPLIED GENERAL SOCIAL PATTERN by INTERSECTION shall be the set formed by the intersection of the sets of decisions of all organisms in a specific society or culture. Abbreviation: AGSI

Definition TGSM

The TECHNICAL GENERAL SOCIAL PATTERN by MAJORITY shall be the set formed by those decisions common to over fifty per-cent of all organisms in existence. Abbreviation: TGSM

Definition AGSM

The APPLIED GENERAL SOCIAL PATTERN by MAJORITY shall be the set formed by those decisions common to over fifty per-cent of all organisms in a specific society or culture. Abbreviation: AGSM

THE DEW PROCESS PROGRAM (i.e., The LAW) (DPP)

When speaking in generalities about a legal structure, specifically some form of state, we use a plan called the Dew Process Program (DPP), which, in effect, the set of laws of the state and, hence, the set of things that the state feels the people should be doing. DPP is basically divided into four subsets, each of which is defined below. We reference to these by abbreviation as the title is lengthy.
 

Definition TDPI
The TECHNICAL DEW PROCESS PROGRAM by INTERSECTION shall be the set formed by the intersection of the sets of laws of all states in existence. ABBEV.: TDPI

Definition ADPI
The APPLIED DEW PROCESS PROGRAM by INTERSECTION shall be the set formed by the intersection of the sets of laws of all states in a specific area. ABBEV.: ADPI

Definition TDPM

The TECHNICAL DEW PROCESS PROGRAM by MAJORITY shall be the set formed by those laws common to over fifty per-cent of all states in existence. Abbreviation: TDPM

Definition ADPM

The APPLIED DEW PROCESS PROGRAM by MAJORITY shall be the set formed by those laws common to over fifty per-cent of all states in a specific area. Abbreviation: ADPM
 

INTERRELATIONSHIPS

All three plans are interrelated in certain ways. Initially, the source for DPP and GSP is NSP. DPP, of course, is "written down somewhere". GSP is also written down, e.g., in psychology texts. NSP is elusive and changing and is the most dynamic of all three. Consequently, in a social order with all three plans operating, there is what is commonly called a "CULTURAL LAG" between the plans as a function of time. In the "lag", NSP moves ahead, GSP follows NSP, and DPP trails behind (it is the hardest to change). The overall effect of this is a general "damping effect" on progress. Also, if there is a large "spread" between the three plans, it becomes possible to make any decision you want and find a way to justify it, or, conversely, to condemn any practice you want and find a way to justify it.

Societies like this are called "transient spaces" and they are covered in greater detail later on. They are complex systems, where almost "anything goes" and it is easy to get "lost in the shuffle".
 

CHARACTERISTICS OF THE MAJOR PLANS  -SUMMARY CHART
 
 
 

INTRODUCTION

We say that a SOCIETY is a set of organisms having some means of intercommunication, together with all inorganic and synthetic organic structures which assist them.

Here, we want to run through some useful analytical guides for examining societies.

INTERRELATIONSHIPS

INTERRELATIONSHIPS between societies can be studied by models based on the STATIC FUNCTION PROPERTIES which were given in Chapter One. The mechanism of application is to note the properties of the collective processors of the organisms and other things in the society under analysis.
 

Interrelationships are obviously studied by comparing two societies, but less obviously one should consider comparisons of a society to a society (the same society) at different points on the time line.

BEHAVIOR UNDER MODIFICATION

BEHAVIOR UNDER MODIFICATION in societies can be analyzed through the application of the SET THEORY PROPERTIES 1-3 through 1-10 inclusive which were given in Chapter One.
 
 

INTRODUCTION

We have presented the Organic Power Axiom and the Hope Theorem. Now we introduce the notion of control. The General Control Theorem is stated as follows:

THEOREM: Anything can be controlled through knowledge of its plan of operation.

The fundamental stages in control are observation and application of that learned in observation. We observe by methods of comparison and development.

TYPES OF ORGANIC CONTROL
There are three basic types of control based on what we have discussed so far. These are Programming, Reprogramming, and a concept that we call CHANGE OF BASIS which we now introduce.
 

All things relative to man are relative to the Identity of man. By the phrase CHANGE OF BASIS we mean the modification of an organism's Identity.

PRINCIPLES IN OBSERVATION

Comparison

PROPERTY: COMPARISON I

Congruent organisms will pair congruent stimuli with congruent reactions.

Congruent organisms will form decisions with non-congruent reactions when the stimuli processed are not congruent.

Complementary organisms will pair congruent stimuli with non-congruent reactions.

Complementary organisms will form decisions with congruent reactions only if the stimuli processed are not congruent.

PROPERTY:

ORGANIC PREDICTION PROPERTY

The nature of the reactions yielded by an organism may be determined through knowledge of the organism and the stimuli it has processed.

ORGANIC HISTORICAL PROPERTY

The nature of the stimuli an organism has processed may be determined through knowledge of the organism and the reactions it has yielded.

The nature of an organism may be determined through knowledge of the decisions it has made, the accuracy being relative to the quantity of decisions known.

PROPERTY: ORGANIC PROJECTION PROPERTY

The nature of an organism at a given time can be determined if the nature of the organism at a previous time is known and the decisions made by the organism during the interim are known in sequence, as a function of time.

Social Controls

Controls through programming

PROPERTY:

ORGANIC INTEGRATION THROUGH PROGRAMMING

ORGANIC INVARIANCE FROM CONGRUENT STATE UNDER PROGRAMMING

If two congruent organisms receive congruent programming, then they will remain congruent.

ORGANIC INVARIANCE FROM COMPLEMENTARY STATE UNDER PROGRAMMING

If two complementary organisms receive complementary programming, then they will remain complementary.

ORGANIC CONVERGENCE UNDER PROGRAMMING

If two non-congruent organisms receive congruent programming, then they will converge, approaching congruence as a limit.

ORGANIC DIVERGENCE UNDER PROGRAMMING

If two non-complementary organisms receive complementary programming, then they will diverge, approaching a complementary state as a limit.

Controls through Reprogramming

PROPERTY: ORGANIC INTEGRATION THROUGH REPROGRAMMING

If two non-congruent organisms are reprogrammed to delete their relative complements, i.e., those characteristics which they do not have in common, then they will become congruent.

ORGANIC INVARIANCE FROM CONGRUENT STATE UNDER REPROGRAMMING

If two congruent organisms are reprogrammed to delete congruent characteristics, then they will remain congruent.

ORGANIC INVARIANCE FROM COMPLEMENTARY STATE UNDER REPROGRAMMING

Two complementary organisms will remain complementary under reprogramming.

ORGANIC CONVERGENCE UNDER REPROGRAMMING

If two non-congruent organisms are reprogrammed to delete those characteristics which they do not have in common, then they will converge and eventually become congruent.

ORGANIC DIVERGENCE UNDER REPROGRAMMING

If two non-complementary organisms are reprogrammed to delete those characteristics which they have in common, then they will diverge and eventually become complementary.

Individual Controls

ORGANIC DESTRUCTION

An organism can be destroyed, i.e., forced to die or go insane, by programming it with a stimulus which it can neither pair nor store.

CHANGE OF STATE

The state of an organism may be changed by modifying the organism's processor and/or its domain.

RELATIVITY

All things relative to man are relative, in the final analysis, to the Identity of Man. Therefore, if Identity is changed, then so is all relative to man.

SUMMARY    FOR SECTION       ONE

SECTION TWO
 
 
 
 
 
 
 
 

S L PHILOSOPHY

I stand near the center of a void - a zone of complete darkness and virtual emptiness. I look to the South, East, and West to infinity, and see nothing. I look to the North and see before me a gigantic formless mass of plasma - of the sub atomic particles in elementary form. Such is the state of the Universe. Under terrific gravity, there is no light given off by the mass; nor is there heat emitted. Darkness is upon all that exists.

At length there is a terrific explosion - huge sections of the mass fly out in all directions. As this occurs, the gravity is decreased and the sub atomic particles, now unstable, react violently liberating immense heat and light causing the void to be flooded with illumination.

Again the process is repeated. Each of the original large chunks now blasts into many fragments, each flying out in all directions. These fragments also decompose into smaller bits which break into still smaller ones. At last some of these blast into gas and dust.

Today we know the original chunks as the Galaxies of our Universe. We call the parts into which they decomposed the Solar Systems of the Galaxies. The smaller particles formed by their decomposition are known as the Planets of the Solar Systems. Finally we have the Satellites or Moons of the planets, the Asteroids, and the Comets, Meteorites, space dust, gas, and so forth which formed form the partial or complete decomposition of Planets.

Although the original chunk is now almost completely decomposed, it continues to expand. The Galaxies, Solar Systems, Planets, and so forth continue to expand, flying apart at a fantastic rate. The original point where the basic mass was is now empty, giving the universe a doughnut like shape. The great speed of the expanding masses causes the light rays to be stretched out, so to speak, dinning the normally bright light from other Solar Systems and Galaxies and creating the illusion of day and night on many of the planets. The dimmed light is referred to as starlight.

Let us now turn our attention to one insignificant bit of the original mass; a chunk of the Galaxy we call the Milky Way. We know it well - it is our Earth. Let us examine this chunk of mass and observe its properties. Let us look in to the characteristics of its inhabitants and attempt to explain this massive chain of circumstances that we refer to as life. Let us examine its past, observe its present state, and attempt to predict its future course. It is to this task, then, that we now turn our attention.

SECTION TWO

CHAPTER FOUR
 
 
 
 

INVERSE LAWS
 
 
 
 

In our discussion of Organic Structure, we formally defined Identity as the data portion of the Key Design Program and briefly examined some of its properties. The subject of man's Identity, however is much farther reaching than a simple definition or a brief examination. Indeed, we will find ourselves referring to it again and again in future discussions. Because of its extreme importance to us, we present a more detailed discussion of the properties of Identity at this time.

Identity is the core of man - the very essence of man's being. A man's Identity distinguishes him from other men as a unique Individual and gives him a place in the highest class of a society. Identity is the basis of all progress - the source of all new ideas. It is the seat of man's drive and determination, his will to search and find - to seek out knowledge and truth. Of all the treasures of the universe, the greatest and most precious possession that an Individual will ever have is his Identity.

To man, Identity gives a unique body and mind - a physical and mental structure that has never occurred before and will never naturally occur again. To his body it imparts a special symmetry - a special beauty, a special configuration of characteristics which are his and his alone. To his mind it gives new data - new concepts and ideas that have heretofore been untapped and unexplored. It stimulates and drives him to fellow some special path not yet charted in the annals of history.

We know our Mental Identity as the hunch, the good guess, the intuitive direction the unlearned knowledge. It leads the Individual to the great invention and discovery. As such, Identity is the basis of all progress and the Individual, the only possessor of Identity, is the only one who can cause progress. All great inventions and discoveries may be directly traced to one Individual - to that one person of vision and determination whose perseverance led him into uncharted territory.

Although all naturally occurring organisms possess Identity, few use it to full capacity. Many disregard the random thought and unique drive to pursue courses already charted. Many sell short their uniqueness and individuality. In time they look to the accomplishments of others and recall to themselves, "I thought of that" when it is too late.

The future of man lies in the hands of those willing to seek knowledge and uncover the great truths. To those who follow the uncharted paths go the rewards of life. The Individual will find his greatest reward when he has followed his Identity and gained an education from himself.
 
 
 

An understanding of the nature of "security" is necessary for the complete understanding of many concepts in Organics. Its formal definition facilitates the defining of future terms related to it. For these reasons, we shall be rather thorough in our discussion so that the concept may be fully understood.

We shall begin with a standard dictionary definition of the term "security" and proceed to our formal definition.

SECURITY, noun (Latin 'securitas', freedom

from care, from 'securus', free from care)

1. A feeling of safety, whether founded on

fact or delusion; freedom from fear or apprehension; confidence of safety; hence, carelessness; overconfidence; want of caution.

2. Freedom from danger or risk; safety.

3. Certainty; assurance; confidence; assuredness

4. One who or that which guards or secures; a defense; a guard; hence, specifically, (a) something given or deposited to secure or as- sure the fulfillment of a promise or the performance of a contract; a pledge; (b) a surety; one who becomes responsible for the obligations of another.

Syn.- Protection, shelter, safety, certainty.

To provide safety and certainty, to provide exemptions from risks and dangers, some instrument must be employed to assume responsibility for such dangers. For example, if we wish to provide security with respect to the elements - that is, to secure ourselves or make ourselves exempt from the effects of rain, snow, wind, and the like, we must employ a shelter of some kind to accomplish this. Security, then, is the state existing when something is shielded from something else - some danger or risk, specifically - by some external force. We are, therefore, concerned with three basic things. First, there is some risk or danger that we wish to deal with. Second, there is something that we wish to shield or protect from this risk. And third, there is a means that we will employ to do this.

EXAMPLES
 

To aid in the understanding of our technical definition, consider the following example:

A housewife is watching television alone one night when the main fuse blows. All the lights, etc. go off and she is left in total darkness. She doesn't know how to change the fuse and, if there are any fuses around the house, the hasn't the faintest idea where they are. She therefore calls the Electric Company and has a representative come out and change the fuse, restoring power.

The housewife is the Secured Processor. She is unable to process the stimulus consisting of the burnt out fuse. There is risk involved here. There might be some burglar waiting outside, etc. She therefore enlists the aid of a Securer Processor in the form of the Electric Company's representative. The Securer Processor assumes all responsibility for the processing of the stimulus.
If there is a burglar, it will attack him. If there is some defect in the wiring, he will be the one liable to be electrocuted. The housewife has security with respect to the electric service by virtue of her Securer Processor, the representative.
 
 
 

Consider the case of an organism whose processor has a domain consisting of "x" stimuli. Let us now introduce a securer processor and assign to it the task of processing "n" of the "x" stimuli in the domain of the organism's processor. Since "n" of the stimuli originally contained in the domain of the organism's processor have now been transferred to the securer processor's domain, the organism's processor's domain now contains only (x-n) stimuli.

If n=0, then the organism's processor is still responsible for processing all "x" stimuli. If n=1, then there is one less stimulus in the domain of the organism's processor and, hence, one less decision that the organism will have to resolve for itself. As the value of 'n" approaches the value of "x"', there fore, the responsibility for the organism's decisions leans more and more on the securer processor and less and less on the organism's processor. When n=x, all the operations of the organism's processor have been assumed by the securer processor and the organism's processor no longer functions.

In Individuals, naturally-occurring organisms possessing Identity, the processor is determined by the Identity together with the programming. The Identity "colors" the programming since it is the first set of data contained in the processor. In all decisions of Individuals, therefore, a vital part is played by the Identity. Since all Individuals are unique, they yield unique decisions. They are affected differently by congruent stimuli as their processors are all different. As an Individual organism entrusts its decision making to a securer processor, however, less and less of its processor, and hence, less and less of its Identity is put to use. If it entrusts all decisions to a securer processor, Then none of its Identity is used and its mind lies idle.

As an organism entrusts more and more decisions to a securer processor, it gains more and more security, but, in the process, it loses more and more of its Identity. We express this relation- ship in the following theorem, the proof of which has just been presented.

T-4-1. S=1/I

"There exists an inverse proportion between "security" and "Identity"
such that for every unit of "security" gained by an organism, a unit
of the organism's "Identity" is lost."
 

The following two examples illustrate the sacrifice of Identity to gain security by special cases:
 

Example (loss of mental Identity)
Tim has just been hired to a job he has been seeking for some time. He feels he must make an impression upon his Coworkers that will make them respect and like him. Although he has his own ideas on many issues that they discuss, he is apprehensive about their reactions. He feels that he must sound like "one of the gang" to gain their approval. He therefore memorizes the polls and surveys in the local paper and, on more personal matters, tries to pattern himself after the boss' son. In doing this he gains the respect of the men and the admiration of the boss, but he loses a large portion of his mental Identity. His securer processors, the newspaper and the son of his boss, make all decisions for him. He no longer has any "original" views on anything.
 

Example (loss of physical Identity)
 

Jill sees a wonderful handsome boy one day and falls in "love" with him instantly. She is a bit scared, however, as she feels that she might not be his "type". The thought of making a play for him and being rebuked terrifies her. She feels that she must transform herself into his "perfect" mate. She checks with her girl friends and learns that he is extremely fond of fine, shapely blondes with clear complexions and blue eyes. She is a brunette with freckles and a cute, but rather moderate build. She has a uniqueness about her that makes her quite attractive, but she is not 'his type". She therefore arranges for her hair to be bleached and thereby become closer to her boy friend's ideal mate. She undergoes treatments to remove the freckles and has extensive plastic surgery done to modify her figure. Inert foam compounds are injected into her breasts to make her "finer" and other odds and ins are added elsewhere to help things along. She would be glad to change the eyes too if she had enough money and knew how. At last she has completely physically modified herself and is as close as possible to her boy's desires. She meets him and they marry. She gains the security of marriage and of being with the one she "loves" at the loss of her physical Identity (and mental too - she will adapt to his every desire in that line also).

These two examples concern things that could (and do), take place today. The advances in the line of plastic surgery make it possible to change ones physical Identity virtually completely. The new psychochemicals facilitate the complete overhaul of the personality and all mental characteristics. The processes bring one security, but sacrifice the Individual's most precious possession - his Identity.

DISCUSSION
 

The inverse between security and Identity represents a basic choice which, in the course of life, all Individuals must make. They must decide whether they will use their natural qualities of body and mind or whether they will put security above their Identity. The choice is evident in many decisions of daily life - whether to do or not to do, to speak or not to speak, to give in or stand firm, to move onward or remain. To those who choose Identity goes the rather lonely road of the Individual and the fast moving progressive culture of the Dynamics. We discuss the theory of Dynamics in Chapter Six. To those who choose security goes the synthetic happiness of complacency and the slow, non-progressing culture of the Statics (Chapter Six).

The Individual who chooses security above Identity and begins to sacrifice his physical and mental uniqueness to gain the respect of the group or state undergoes certain changes. As he gradually loses his Identity, he approaches as a limit the state of the Android or synthetically produced organism. Because he has lost a portion of his Identity, he is no longer a complete Individual. He is not an Android either, as he still has a portion of his Identity left. This gradual change from Individual to Android requires a new "transitional" classification.

We refer to naturally-occurring organisms which have lost a portion of their Identity as NEO-ANDROIDS. In the strictest sense of the word, the tern refers to those Individuals who have been permanently modified by a change in the Key Design. In a less formal sense, we include those who have suppressed some of their mental Identity or reshaped some physical characteristics, even though this does not affect the Key Design.

We shall discuss methods of modification in much greater detail later. For the present, we shall mention a few methods to emphasize our point. Modifications which cause mutations change the Key Design Program and affect all organisms produced by the organism involved from that time on. The new psychochemicals have such an effect. Radiation erases portions of the Key Design. Shock treatments erase portions of the mental Identity from memory. In the case of those techniques which do not effect the Key Design, such as voluntary suppression of data into the unconscious data program and physical modifications which can be reversed, the organisms' offspring's may be Individuals.
 
 
 

TRANSIENT AND ABSOLUTE FORMS
 

In Section One we talked about the concept of an organic structure called an Individual and another type of organic structure called an Android. We introduced the Android saying it was synthetic and the Individual saying it was natural, or real.
Another way in which we have compared Android and Individual is in the concept of an Identity Factor; we said that this factor existed in Individual but was absent in Android. Not so many things in reality are so pure as this black and white type of concept.

Intuitively, then, one might guess that there is some class in-between the pure models we have called Android and Individual. Such a class would have some characteristics of both. A class like this, we call a TRANSIENT CLASS. The particular TRANSIENT CLASS in this case, those organic structures somewhere in the in-between region bounded by the pure notions of Android and Individual we call NEO-ANDROID.

NOMENCLATURE

We will now go through some nomenclature which is useful in explaining the notions we are discussing at this present level.

The "QUANTITY OF IDENTITY INHERITED" is that quantity determined by
the average of the quantities of Identity possessed by the structure's parent structures at the time the structure was conceived, which, for each parent structure, is determined by the formula:

The "RELATIVE PER-CENT IDENTITY" or "REL %I" is the Per-cent Identity, computed with the assumption that the quantity of Identity inherited was unity.

With these notions, one can now write mathy definitions for Individuals, Neo-Androids, and Androids.

In a strict sense, we can call Individuals the class of structures with %I at exactly 100, Androids as that class with %I at exactly 0, and all elsewhere Neo-Androids.

Or, being more practical, using the standard gaussian distribution, we can call %I above 75 Individuals, 75-25 Neo-Androids, and below 25 Androids.

CLASSIFICATION OF STRUCTURES

Various types of structures were covered in Section One. These were defined when introduced. We have now introduced and defined the Neo-Android and this completes the structures covered in the text. The flow-chart below is a helpful tool for quick reference concerning structures.

PROGRESS

Intuitively, when we think of progress, we think of a moving forward toward some yet unachieved goal. People, Individuals, move toward goals and sets of people, which we have called SOCIETIES, also meander towards goals.

In our model of an "Individual", we have presented certain ideas previously. From these ideas, we now point out that the model for an Individual is equivalent to the model for a Computer coupled with the concept of Identity.

If we drift to a theoretical notion of a "society" of Computers, and then think of progress, the model "society" as a function of time will achieve a stable state of some sort and stop. The program will "run out". At this point there will be no more "PROGRESS".

When we say SOCIETY, of course, there is more involved than Computers, from the definition given previously. The point is that the model limited in this way ceases to progress at some predictable fixed point on the time line.

In the format of the definitions and models of this text, there is essentially only one difference between a real "SOCIETY" and the limited model we have just discussed and this difference is our notion of an "Identity factor" or "Identity".

The differences, then, observable by comparing real "SOCIETIES" which show PROGRESS in an onward and continuing nature and our "run out" model brings us again to the concept of "Identity".

We say that Identity is a necessary condition for continued PROGRESS.

CLASSIFICATION OF SOCIETIES

Societies are classified into three major groups. These groups are STATIC, DYNAMIC, and TRANSIENT. STATIC societies are modeled by the "computer" model above and they are social systems in which a predominate choice of Security above Identity has led to an essential standstill. DYNAMIC societies are modeled by a predominant choice of Identity above Security and they are social systems showing continuing and onward growth. TRANSIENT societies show a combination of these two models and there is an interplay of forces at work.

The study of STATIC societies is called SOCIOSTATICS and the study of DYNAMIC societies is called SOCIODYNAMICS. We call both fields of study, SOCIOSTATICS and SOCIODYNAMICS, the study of "THEORITICAL SOCIAL SYSTEMS" because in real life they are hard to find in such a pure form. "REAL SOCIAL SYSTEMS" are not so pure and direct as these models but they show characteristics of both. A social system showing this duality and interplay of conflicting forces is called a TRANSIENT SPACE.

THEORITICAL SOCIAL SYSTEMS are covered in Chapter 6 and REAL SOCIAL SYSTEMS are covered in Chapter 7.
 
 
 
 

Competitive Basis and Competitive Advantage are both necessary conditions for competition to exist. Neither one by itself will do. And, there are certain constraining interrelationships. If Competitive Basis is as large as possible, everyone would be equally familiar with each other to the point that any contest would end in a stalemate. Realizing this, there would be no reason to compete because it would be futile.

And similarly, if Competitive Advantage was as large as possible so that everyone could overcome the other, the system would either annihilate itself or agree to stay apart so that they could survive and again there would be no competition.

So, referring to the graph, in practical reality, as Basis increases, Advantage decreases and vice versa. 

Consequently, due to this, competition is self limiting and is at a maximum when Basis and Advantage are roughly equal.

Having gone through the basic idea, we now present the concept in a formal way using "properties" -
 

PROPERTY: COMPETITION I

A Competitive Basis is a necessary condition for competition.

PROPERTY: COMPETITION II

A Competitive Advantage is a necessary condition for competition.

PROPERTY: COMPETITION III

Given two non-congruent organic structures under going modification such that their processors are converging-

As the two organic structures approach a congruent state as a limit, the competitive basis which exists between the two structures approaches an upper limit of unity.

PROPERTY: COMPETITION IV

Given two non-congruent organic structures undergoing modification such that their processors are converging:

As the two organic structures approach a congruent state

as a limit, the competitive advantage of either structure approaches a lower limit of zero.

PROPERTY: COMPETITION V

Given two non-complementary organic structures undergoing modification such that their processors are diverging:

As the two organic structures approach a. complementary state as a limit, the competitive basis which exists between the two structures approaches a lower limit of zero

PROPERTY: COMPETITION VI

Given two non-complementary organic structures undergoing modification such that their processors are diverging:

As the two organic structures approach a complementary state

as a limit, the competitive advantage of either structure over the other approaches an upper limit of unity.

CLASSICAL POLITICAL SYSTEMS

Using the competition concept. and the definitions and properties just presented, we can now write cute mathy definitions for the three classic political systems, ANARCHY, DEMOCRACY, and SOCIALISM

DEFINATION:
ANARCHY

ABS: A society in which the average competitive basis of the natural organic members is exactly zero and the average competitive advantage of these members is exactly unity

REL: A society in which the average competitive basis& of the natural organic members is not above 0.25 and the average competitive advantage of these members is not below 0.75.

DEMOCRACY

ABS: A society in. which both the average competitive basis and the average competitive advantage of the natural organic members are between zero and unity

REL: A society in which both the average competitive basis and the average competitive advantage of the natural organic members are between 0.25 and 0.75.

SOCIALISM

ABS: A society in which the average competitive basis of the Natural organic members is exactly unity and the average competitive advantage of these members is exactly, zero.

REL: A society in which the average competitive basis of the natural organic members is not below 0.79 and the average competitive advantage of these members is not above 0.25.

To link the classical structures to the Basic Inverse (Identity-Security)

we present the following three properties-

PROPERTY: POL I

Anarchy is dynamic or Identity-Oriented

PROPERTY: POL II

SOCIALISM is static or security-oriented

PROPERTY: POL III

Democracy is a transient-space

Classical concepts in Religion behave in a manner similar to concepts in the Identity-Security relationships. The Religious Properties presented below are designed to show these relationships and link up classical Religion to the master (I-S) Inverses.

PROPERTY: RELIG I

The Religious concept of "Soul" is similar to the Plan Theory concept of an "Identity Factor"

PROPERTY: RELIG II

The Religious concept of "God" is similar to the Plan Theory concept of a dynamic or Identity-oriented force.

PROPERTY: RELIG III

The Religious. concept of "devil" is similar to the Plan Theory concept of a static or security-oriented force.

PROPERTY: RELIG IV

The Religious concept of "heaven" is similar to the Plan Theory concept of a dynamic or Identity-oriented environment.

PROPERTY: RELIG V

The Religious concept of "hell" is similar to the Plan Theory concept of a static or security-oriented environment

PROPERTY: RELIG VI

Earth is a transient space.

If there is one main principle in all religious concepts, it is that man possesses a Soul. In defining the Soul, dictionaries use such phrases as "the immortal spirit which inhabits the body", the "animating or essential part", "the vital principle", "the source of action" , and "the essence". All of these phrases indicate that the Soul is the basis of man - that the Soul IS man.

The Bible teaches that the Soul is a gift of God; that God has caused the Soul to inhibit the body of man. We are taught that this gift can only be bestowed by the Creator himself and that man shall never synthesize the Soul or acquire it by any other means. Although we cannot "buy" a Soul, we know that we can "sell" ours. Men often disregard this great gift and "sell their Souls to the devil". Stories are often written of those who gained prosperity and worldly goods by "selling" their Souls.

So far, in this theory, we have not defined the Soul as such, but we have discussed in great detail the concept of Identity. We have said that Identity is the essence of man. We know that it gives man uniqueness and makes him an Individual. We know that Identity is possessed only by naturally-occurring organisms and that it cannot be synthesized or acquired in any other way. This is natures process and we must rely upon nature to perform it.

In "The Basic Inverse" we learned that Identity could be sold (suppressed) to gain security and that as security was gained Identity was lost. We know of many who feel that security is of a greater value than Identity and are quite willing to sell it to anyone who will give them worldly things in return.

We see, therefore, that both the Soul and Identity are "sold" to gain securities, that both are products of forces beyond the control of man, and that both offer uniqueness in that both give man special qualities peculiar to him alone. Since the Soul behaves in the same manner as does Identity, we must consider the theory that the Soul is Identity and Identity is the Soul. We shall assume that the two are congruent for the duration of our discussion.

The link between the Soul and Identity represents a bridge between Philosophy and Science. The expansion of such bridges will eventually result in a formal, scientific proof of all principles of the Bible and other great philosophical texts. Those who believe that Religion is invalid because science is valid should  note that science and Religion merge at this point.

There are certain classic symbols used. in literature, poetry, music, etc., that, while we will not get formal about them, do, nevertheless tend to line up with the. transition and implication of transition from Identity-oriented to Security-oriented and vice versa.
We group these "key phrases" into major areas and list them below:
 
 

THE BASIC CHOICES IN LIFE

INTRODUCTION

We present here by summary the overall implications of the choice between Identity and Security that we have been discussing here in Chapter four. Although some points require the reader to add a bit of insight - they do not really require all that much.

SUMMARY CHART FOR CHAPTER FOUR

IMPLICATIONS OF THE DECISION TO CHOOSE IDENTITY OR SECURITY
 
 

PLAN TREORY

SECTION TWO

CHAPTER FIVE
 
 
 
 

CYCLE THEORY
 
 
 
 
 

INTRODUCTION TO CHAPTER FIVE

In the beginning, all matter in our Universe was in the elementary form of the sub atomic particles. As this mass expanded or diverged, however, the sub atomic particles became unstable. They combined with each other, or converged, to form a new structure - the element. when they did this, they became more stable or secure. An element is more stable than free protons, neutrons, electrons, etc. An important change also took place. When the elements were formed, the sub atomic particles lost their 'identity' as sub-atomic particles. Today we know that an element, take gold for example, is composed of sub atomic particles. We refer to it, however, as gold. We do not refer to it as a special configuration of sub-atomic particles. These particles have combined now and the result of this merging is the element. It has a new identity, not possessed by those particles which combined to make it.

This process is repeated when the elements combine to form compounds. Many elements are unstable in elementary form. They tend to converge to a more stable form - the compound. A compound is much more stable than the elements which compose it. It does not resemble these elements, however. Again it has a new identity, the elements which formed it have lost theirs.

It would seem that we have a definite pattern here - and we do. It appears that we have a continual merging of systems to form new systems and that when this process is complete the original systems have lost their characteristics or their identity and a new system has