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Functional Logic • Quantification Theory
Author: Jon Awbrey
Contents
 1 Toward a Functional Conception of Quantificational Logic
 2 Appendix : Generalized Umpire Operators
 3 References
 4 Related Topics
 5 Resources
 6 Document History
Toward a Functional Conception of Quantificational Logic
Up till now quantification theory has been based on the assumption of individual variables ranging over universal collections of perfectly determinate elements. Merely to write down quantified formulas like and involves a subscription to such notions, as indicated by the membership relations invoked in their indices. Reflected on pragmatic and constructive principles, however, these ideas begin to appear as problematic hypotheses whose warrants are not beyond question, projects of exhaustive determination which overreach the powers of finite information and control to manage. Therefore, it is worth considering how we might shift the scene of quantification theory closer to familiar ground, toward the predicates themselves which represent our continuing acquaintance with phenomena.
Higher Order Propositional Expressions
By way of equipping this inquiry with a bit of concrete material, I begin with a consideration of higher order propositional expressions, in particular, those that stem from the propositions on 1 and 2 variables.
Note on notation. The discussion that follows uses minimal negation operations, expressed as bracketed tuples of the form and logical conjunctions, expressed as concatenated tuples of the form as the sole expressionforming operations of a calculus for booleanvalued functions or propositions. The expressions of this calculus parse into data structures whose underlying graphs are called cacti by graph theorists. Hence the name cactus language for this dialect of propositional calculus.
Higher Order Propositions and Logical Operators (n = 1)
A higher order proposition is, very roughly speaking, a proposition about propositions. If the original order of propositions is a class of indicator functions then the next higher order of propositions consists of maps of the type
For example, consider the case where Then there are exactly four propositions and exactly sixteen higher order propositions that are based on this set, all bearing the type
Table 1 lists the sixteen higher order propositions about propositions on one boolean variable, organized in the following fashion: Columns 1 and 2 form a truth table for the four turned on its side from the way that one is most likely accustomed to see truth tables, with the row leaders in Column 1 displaying the names of the functions for = 1 to 4, while the entries in Column 2 give the values of each function for the argument values that are listed in the corresponding column head. Column 3 displays one of the more usual expressions for the proposition in question. The last sixteen columns are topped by a collection of conventional names for the higher order propositions, also known as the measures for = 0 to 15, where the entries in the body of the Table record the values that each assigns to each
1 0  
0 0  0  1  0  1  0  1  0  1  0  1  0  1  0  1  0  1  
0 1  0  0  1  1  0  0  1  1  0  0  1  1  0  0  1  1  
1 0  0  0  0  0  1  1  1  1  0  0  0  0  1  1  1  1  
1 1  0  0  0  0  0  0  0  0  1  1  1  1  1  1  1  1 
I am going to put off explaining Table 2, that presents a sample of what I call interpretive categories for higher order propositions, until after we get beyond the 1dimensional case, since these lower dimensional cases tend to be a bit condensed or degenerate in their structures, and a lot of what is going on here will almost automatically become clearer as soon as we get even two logical variables into the mix.
Measure  Happening  Exactness  Existence  Linearity  Uniformity  Information 
Nothing happens  
Just false  Nothing exists  
Just not  
Nothing is  
Just  
Everything is  is linear  
is not uniform  is informed  
Not just true  
Just true  
is uniform  is not informed  
Something is not  is not linear  
Not just  
Something is  
Not just not  
Not just false  Something exists  
Anything happens 
Higher Order Propositions and Logical Operators (n = 2)
By way of reviewing notation and preparing to extend it to higher order universes of discourse, let us first consider the universe of discourse based on two logical features or boolean variables and
The universe of discourse consists of two parts, a set of points and a set of propositions.
The points of form the space:
Each point in may be indicated by means of a singular proposition, that is, a proposition that describes it uniquely. This form of representation leads to the following enumeration of points, presented in two different styles of typography that are used in this text:
(u)(v) , (u)v , u(v) , uv


Each point in may also be described by means of its coordinates, that is, by the ordered pair of values in that the coordinate propositions and take on that point. This form of representation leads to the following enumeration of points:
The propositions of form the space:
As always, it is frequently convenient to omit a few of the finer markings of distinctions among isomorphic structures, so long as one is aware of their presence and knows when it is crucial to call upon them again.
The next higher order universe of discourse that is built on is which may be developed in the following way. The propositions of become the points of and the mappings of the type become the propositions of In addition, it is convenient to equip the discussion with a selected set of higher order operators on propositions, all of which have the form
To save a few words in the remainder of this discussion, I will use the terms measure and qualifier to refer to all types of higher order propositions and operators. To describe the present setting in picturesque terms, the propositions of may be regarded as a gallery of sixteen venn diagrams, while the measures are analogous to a body of judges or a panel of critical viewers, each of whom evaluates each of the pictures as a whole and reports the ones that find favor or not. In this way, each judge partitions the gallery of pictures into two aesthetic portions, the pictures that likes and the pictures that dislikes.
There are measures of the type Table 3 introduces the first 24 of these measures in the fashion of the higher order truth table that I used before. The column headed shows the values of the measure on each of the propositions for = 0 to 15, with blank entries in the Table being optional for values of zero. The arrangement of measures that continues according to the plan indicated here is referred to as the standard ordering of these measures. In this scheme of things, the index of the measure is the decimal equivalent of the bit string that is associated with 's functional values, which can be obtained in turn by reading the column of binary digits in the Table as the corresponding range of boolean values, taking them up in the order from bottom to top.

1100 1010 

0000  0  1  0  1  0  1  0  1  0  1  0  1  0  1  0  1  0  1  0  1  0  1  0  1  
0001  0  0  1  1  0  0  1  1  0  0  1  1  0  0  1  1  0  0  1  1  0  0  1  1  
0010  0  0  0  0  1  1  1  1  0  0  0  0  1  1  1  1  0  0  0  0  1  1  1  1  
0011  0  0  0  0  0  0  0  0  1  1  1  1  1  1  1  1  0  0  0  0  0  0  0  0  
0100  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  1  1  1  1  1  1  1  1  
0101  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  
0110  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  
0111  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  
1000  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  
1001  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  
1010  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  
1011  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  
1100  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  
1101  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  
1110  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  
1111  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0 
Umpire Operators
We now examine measures at the high end of the standard ordering. Instrumental to this purpose we define a couple of higher order operators, and both symbolized by cursive upsilon characters and referred to as the absolute and relative umpire operators, respectively. If either one of these operators is defined in terms of more primitive notions then the remaining operator can be defined in terms of the one first established.
Given an ordered pair of propositions as arguments, the relative operator reports the value 1 if the first implies the second, otherwise 0.
Expressing it another way, we may also write:
In writing this, however, it is important to notice that the 1's appearing on the left and right have different meanings. Filling in the details, we have:
Writing types as subscripts and using the fact that it is possible to express this a little more succinctly as follows:
Finally, it is often convenient to write the first argument as a subscript, hence
As a special application of this operator, we next define the absolute umpire operator, also called the umpire measure. This is a higher order proposition which is given by the relation Here, the subscript 1 on the left and the argument 1 on the right both refer to the constant proposition In most contexts where is actually applied the subscript 1 is safely omitted, since the number of arguments indicates which type of operator is intended. Thus, we have the following identities and equivalents:
The umpire measure is defined at the level of truth functions, but can also be understood in terms of its implied judgments at the syntactic level. Interpreted this way, recognizes theorems of the propositional calculus over giving a score of "1" to tautologies and a score of "0" to everything else, regarding all contingent statements as no better than falsehoods.
One remark in passing for those who might prefer an alternative definition. If we had originally taken to mean the absolute measure, then the relative version could have been defined as
Measure for Measure
Define two families of measures:
by means of the following formulas:
The values of the sixteen on each of the sixteen boolean functions are shown in Table 4. Expressed in terms of the implication ordering on the sixteen functions, says that is above or identical to in the implication lattice, that is, in the implication ordering.

1100 1010 

0000  1  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  
0001  1  1  0  0  0  0  0  0  0  0  0  0  0  0  0  0  
0010  1  0  1  0  0  0  0  0  0  0  0  0  0  0  0  0  
0011  1  1  1  1  0  0  0  0  0  0  0  0  0  0  0  0  
0100  1  0  0  0  1  0  0  0  0  0  0  0  0  0  0  0  
0101  1  1  0  0  1  1  0  0  0  0  0  0  0  0  0  0  
0110  1  0  1  0  1  0  1  0  0  0  0  0  0  0  0  0  
0111  1  1  1  1  1  1  1  1  0  0  0  0  0  0  0  0  
1000  1  0  0  0  0  0  0  0  1  0  0  0  0  0  0  0  
1001  1  1  0  0  0  0  0  0  1  1  0  0  0  0  0  0  
1010  1  0  1  0  0  0  0  0  1  0  1  0  0  0  0  0  
1011  1  1  1  1  0  0  0  0  1  1  1  1  0  0  0  0  
1100  1  0  0  0  1  0  0  0  1  0  0  0  1  0  0  0  
1101  1  1  0  0  1  1  0  0  1  1  0  0  1  1  0  0  
1110  1  0  1  0  1  0  1  0  1  0  1  0  1  0  1  0  
1111  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1 
The values of the sixteen on each of the sixteen boolean functions are shown in Table 5. Expressed in terms of the implication ordering on the sixteen functions, says that is below or identical to in the implication lattice, that is, in the implication ordering.

1100 1010 

0000  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  
0001  0  1  0  1  0  1  0  1  0  1  0  1  0  1  0  1  
0010  0  0  1  1  0  0  1  1  0  0  1  1  0  0  1  1  
0011  0  0  0  1  0  0  0  1  0  0  0  1  0  0  0  1  
0100  0  0  0  0  1  1  1  1  0  0  0  0  1  1  1  1  
0101  0  0  0  0  0  1  0  1  0  0  0  0  0  1  0  1  
0110  0  0  0  0  0  0  1  1  0  0  0  0  0  0  1  1  
0111  0  0  0  0  0  0  0  1  0  0  0  0  0  0  0  1  
1000  0  0  0  0  0  0  0  0  1  1  1  1  1  1  1  1  
1001  0  0  0  0  0  0  0  0  0  1  0  1  0  1  0  1  
1010  0  0  0  0  0  0  0  0  0  0  1  1  0  0  1  1  
1011  0  0  0  0  0  0  0  0  0  0  0  1  0  0  0  1  
1100  0  0  0  0  0  0  0  0  0  0  0  0  1  1  1  1  
1101  0  0  0  0  0  0  0  0  0  0  0  0  0  1  0  1  
1110  0  0  0  0  0  0  0  0  0  0  0  0  0  0  1  1  
1111  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  1 
Applied to a given proposition the qualifiers and tell whether rests or respectively, in the implication ordering. By way of example, let us trace the effects of several such measures, namely, those that occupy the limiting positions of the Tables.
Thus, is a totally indiscriminate measure, one that accepts all propositions whereas and are measures that value the constant propositions and respectively, above all others.
Finally, in conformity with the use of the fiber notation to indicate sets of models, it is natural to use notations like:
to denote sets of propositions that satisfy the umpires in question.
Extending the Existential Interpretation to Quantificational Logic
Previously I introduced a calculus for propositional logic, fixing its meaning according to what C.S. Peirce called the existential interpretation. As far as it concerns propositional calculus this interpretation settles the meanings that are associated with merely the most basic symbols and logical connectives. Now we must extend and refine the existential interpretation to comprehend the analysis of quantifications, that is, quantified propositions. In doing so we recognize two additional aspects of logic that need to be developed, over and above the material of propositional logic. At the formal extreme there is the aspect of higher order functional types, into which we have already ventured a little above. At the level of the fundamental content of the available propositions we have to introduce a different interpretation for what we may call elemental or singular propositions.
Let us return to the 2dimensional case In order to provide a bridge between propositions and quantifications it serves to define a set of qualifiers that have the following characters:
Intuitively, the operators may be thought of as qualifying propositions according to the elements of the universe of discourse that each proposition positively values. Taken together, these measures provide us with the means to express many useful observations about the propositions in and so they mediate a subtext that takes place within the higher order universe of discourse Figure 6 summarizes the action of the operators on the within
Application of Higher Order Propositions to Quantification Theory
Our excursion into the vastening landscape of higher order propositions has finally come round to the stage where we can bring its returns to bear on opening up new perspectives for quantificational logic.
It's hard to tell if it makes any difference from a purely formal point of view, but it serves intuition to devise a slightly different interpretation for the twovalued space that we use as the target of our basic indicator functions. Therefore, let us declare the type of existentialvalued functions where is a pair of values that indicate whether or not anything exists in the cells of the underlying universe of discourse. As usual, let's not be too fussy about the coding of these functions, reverting to binary codes whenever the intended interpretation is clear enough.
With these qualifications in mind we note the following correspondences between classical quantifications and higher order indicator functions:

The following Tables develop these ideas in more detail.

1100 1010 







 
0000  1  1  1  1  0  0  0  0  
0001  1  1  1  0  1  0  0  0  
0010  1  1  0  1  0  1  0  0  
0011  1  1  0  0  1  1  0  0  
0100  1  0  1  1  0  0  1  0  
0101  1  0  1  0  1  0  1  0  
0110  1  0  0  1  0  1  1  0  
0111  1  0  0  0  1  1  1  0  
1000  0  1  1  1  0  0  0  1  
1001  0  1  1  0  1  0  0  1  
1010  0  1  0  1  0  1  0  1  
1011  0  1  0  0  1  1  0  1  
1100  0  0  1  1  0  0  1  1  
1101  0  0  1  0  1  0  1  1  
1110  0  0  0  1  0  1  1  1  
1111  0  0  0  0  1  1  1  1 

1100 1010 







 
0000  1  1  1  1  0  0  0  0  
0001  1  1  1  0  1  0  0  0  
0010  1  1  0  1  0  1  0  0  
0100  1  0  1  1  0  0  1  0  
1000  0  1  1  1  0  0  0  1  
0011  1  1  0  0  1  1  0  0  
1100  0  0  1  1  0  0  1  1  
0110  1  0  0  1  0  1  1  0  
1001  0  1  1  0  1  0  0  1  
0101  1  0  1  0  1  0  1  0  
1010  0  1  0  1  0  1  0  1  
0111  1  0  0  0  1  1  1  0  
1011  0  1  0  0  1  1  0  1  
1101  0  0  1  0  1  0  1  1  
1110  0  0  0  1  0  1  1  1  
1111  0  0  0  0  1  1  1  1 











Appendix : Generalized Umpire Operators
In order to get a handle on the space of higher order propositions and eventually to carry out a functional approach to quantification theory, it serves to construct some specialized tools. Specifically, I define a higher order operator called the umpire operator, which takes up to three propositions as arguments and returns a single truth value as the result. Formally, this socalled multigrade property of can be expressed as a union of function types, in the following manner:
In contexts of application the intended sense can be discerned by the number of arguments that actually appear in the argument list. Often, the first and last arguments appear as indices, the one in the middle being treated as the main argument while the other two arguments serve to modify the sense of the operation in question. Thus, we have the following forms:
The intention of this operator is that we evaluate the proposition on each model of the proposition and combine the results according to the method indicated by the connective parameter In principle, the index might specify any connective on as many as arguments, but usually we have in mind a much simpler form of combination, most often either collective products or collective sums. By convention, each of the accessory indices is assigned a default value that is understood to be in force when the corresponding argument place is left blank, specifically, the constant proposition for the lower index and the continued conjunction or continued product operation for the upper index Taking the upper default value gives license to the following readings:
This means that if and only if holds for all models of In propositional terms, this is tantamount to the assertion that or that
Throwing in the lower default value permits the following abbreviations:
This means that if and only if holds for the whole universe of discourse in question, that is, if and only is the constantly true proposition The ambiguities of this usage are not a problem so long as we distinguish the context of definition from the context of application and restrict all shorthand notations to the latter.
References
 Quine, W.V. (1969/1981), “On the Limits of Decision”, Akten des XIV. Internationalen Kongresses für Philosophie, vol. 3 (1969). Reprinted, pp. 156–163 in Quine (ed., 1981), Theories and Things, Harvard University Press, Cambridge, MA.
Related Topics
Resources
Document History
Note. The above material is taken from a project report on Charles Sanders Peirce's conceptions of inquiry and analogy. Online formatting of the original document and continuation of the initial project are currently in progress under the title Functional Logic : Inquiry and Analogy.
1995 • Oakland University • Inquiry and Analogy
Author:  Jon Awbrey  November 1, 1995 
Course:  Engineering 690, Graduate Project  Winter Term, January 1995 
Supervisors:  M.A. Zohdy and F. Mili  Oakland University 
 Version: Draft 3.25  Created: 01 Jan 1995  Relayed: 01 Nov 1995  Revised: 24 Dec 2001  Revised: 12 Mar 2004
2004 • Inquiry List • Functional Logic
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2004 • Ontology List • Functional Logic
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2004 • NKS Forum • Functional Logic
 http://web.archive.org/web/20131120210604/http://forum.wolframscience.com/archive/topic/254.html
 http://web.archive.org/web/20090302144746/http://forum.wolframscience.com/showthread.php?threadid=254
2004 • NKS Forum • Introduction to Inquiry Driven Systems
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