1. First foundations of mathematics
1.1. Introduction to the foundations of mathematics
Mathematics and theories
Mathematics is the study of systems of elementary objects, whose only nature
is to be exact, unambiguous (two objects are equal or different, related or not;
an operation gives an exact result...). Such systems are conceived independently
of our usual world, even if many of them can resemble (thus be used to describe)
diverse aspects of it.
Mathematics as a whole can be seen as «the science
of all possible worlds» of this kind (of exact objects).
Mathematics is split into diverse branches, implicit or explicit frameworks
of any mathematical work, that may be formalized as (axiomatic) theories.
Each theory is the study of a supposedly fixed system (world) of objects,
called its model. But each model of a theory may be just one of its
possible interpretations, among other equally legitimate models. For example,
roughly speaking, all sheets of paper are systems of material points, models
of the same theory of Euclidean plane geometry, but independent of each other. Foundations and developments
Each theory starts with a foundation, that is the data of a list of pieces of
description specifying what it knows or assumes of its model(s) (its kind or shape).
This includes a list of formulas (statements) called axioms, expressing the
required properties of models, i.e.
selecting its accepted models as the systems where the axioms are true,
from the whole range of possible systems where they can be interpreted.
Then, the study of a theory progresses by choosing some of its possible developments :
new concepts and information about its models, resulting from its given foundation,
and that we can add to it to form its next foundation.
In particular, a theorem of a theory, is a formula deduced from its axioms,
so that it is known as true in all its models. Theorems can be added to the list of
axioms of a theory without modifying its meaning.
Other possible developments (not yet chosen) can still be operated later, as the part of
the foundation that could generate them is preserved. Thus, the totality of possible
developments of a theory, independent of the order chosen to process them,
already forms a kind of «reality» that these developments explore
(before the Completeness theorem
will finally show how the range of possible theorems precisely reflects
the more interesting reality of the diversity of possible models).
There are possible hierarchies between theories, where some can
play a foundational role for others. For instance, the foundations of
several theories may have a common part forming a simpler theory,
whose developments are applicable to all.
A fundamental work
is to develop, from a simple initial basis, a more complete foundation
endowed with efficient tools opening more direct ways to
further interesting developments.
The cycle of foundations
Despite the simplicity of nature of mathematical objects, the general
foundation of all mathematics turns out to be quite complex
(though not as bad as a physics theory of everything). Indeed,
it is itself a mathematical study, thus a branch of mathematics,
called mathematical logic.
Like any other branch, it is made of definitions and theorems
about systems of objects. But as its object is the general form
of theories and systems they may describe, it provides the general
framework of all branches of mathematics... including itself.
And to provide the framework or foundation of each considered
foundation (unlike ordinary mathematical works that go forward from
an assumed foundation), it does not look like a precise starting point,
but a sort of wide cycle composed of easier and harder steps. Still
this cycle of foundations truly plays a foundational role for mathematics,
providing
rigorous frameworks and many useful concepts to diverse branches of
mathematics (tools, inspirations and answers to diverse philosophical questions).
(This is similar to dictionaries defining each word by other words, or to
another science of finite systems: computer programming. Indeed
computers can be simply used, knowing what you do but not why it works;
their working is based on software that was written in some language, then
compiled by other software, and on the hardware and processor whose design and
production were computer assisted. And this is much better than at the birth of this field.)
It is dominated by two theories:

Set theory describes the universe of «all mathematical
objects», from the simplest to the most complex such as infinite
systems (in a finite language). It can roughly be seen as one theory,
but in details it will have an unlimited diversity of possible variants
(not always equivalent to each other).

Model theory is the general theory of theories (describing their formalisms
as systems of symbols), and their possible models.
Each one is the natural framework to formalize the other: each set theory is formalized
as a theory described by model theory; the latter better comes as a development from
set theory (defining theories and systems as complex objects) than directly as a theory.
Both connections must be considered separately: both roles of set theory, as a
basis and an object of study for model theory, must be distinguished. But these
formalizations will take a long work to complete, especially for this following last piece:

Proof theory completes model theory by describing a possible formal
system of rules of proofs giving the theorems of any theory.
A theory is consistent if its theorems will never contradict each other.
Inconsistent theories cannot have any model, as the same statement cannot be
true and false on the same system.
Model theory and proof theory are essentially unique, giving a clear natural
meaning to the concepts of theory, theorems and consistency of each theory.
1.2. Variables, sets, functions and operations
Let us start mathematics by to introducing some simple concepts from
the founding cycle, which may seem selfsufficient. It is natural
to start with a set theory not fully formalized as an
axiomatic theory.
Let us first explain what is a set, then we will complete the
picture with more concepts and explanations on the context of
foundations (model theory) and its main subtleties (paradoxes).
Constants
A constant symbol is a symbol denoting a unique object,
called its value. Examples: 3, Ø, ℕ. Those of English
language are proper names and names with «the» (singular without
complement).
Free and bound variables
A variable symbol (or a variable), is a symbol
without a fixed value. Each possible interpretation gives it a
particular value and thus sees it as a constant.
It can be understood as limited by a box, whose inside has multiple
versions in parallel.
 From inside, the variable is seen as having a fixed value,
thus usable as a constant : it is called fixed.
 We call the variable free when we start going out and
find that this value is not uniquely determined as the only
possible one, and can thus vary.
 A variable is called bound when completely seen from
the «outside», where the diversity of its possible values is
considered as fully known (perceived), gathered and
ready to be processed as a whole.
The diverse «internal viewpoints», corresponding to the possible
fixed values, may be thought of as abstract «locations» in the
mathematical universe, while the succession of statuses of a symbol
(as a constant, a free variable or a bound variable), can be
seen as a first expression of the flow of time in mathematics: a
variable is bound when all the diverse "parallel locations inside
the box" (possible values) are past. All these places and
times are themselves purely abstract, mathematical entities.
Ranges and sets
The range of a variable, is the meaning it takes when seen
as bound: it is the «knowledge» of the totality of its possible or
authorized values (seen in bulk: unordered, ignoring their context),
that are called the elements of this range. This
«knowledge» is an abstract entity that can encompass infinities of
objects, unlike human thought. A variable has a range when it can be
bound, i.e. when an encompassing view over all its possible values
is given.
Any range of a variable is called a set.
Cantor defined a set as «a grouping into a whole of distinct
objects of our intuition or our thought». He explained to
Dedekind : «If the totality of elements of a multiplicity can be
thought of as «simultaneously existing», so that it can be
conceived as a «single object» (or «completed object»), I call it
a consistent multiplicity or a «set».» (We expressed this
«multiplicity» as that of values of a variable).
He described the opposite case as an «inconsistent multiplicity»
where «admitting a coexistence of all its elements leads to a
contradiction». But noncontradiction cannot suffice to
generally define sets: the noncontradiction of a statement does not
imply its truth (the opposite statement may be true but unprovable);
facts of noncontradiction can be themselves unprovable (incompleteness theorem);
and two separately consistent coexistences might contradict each
other (Irresistible
force paradox / Omnipotence
paradox).
A variable is said to range over a set, when it is bound
with this set as its range. Any number of variables can be
introduced ranging over a given set, independently of each other and of
other variables.
Systematically renaming a bound variable in all its box, into
another symbol not used in the same context (same box), with the
same range, does not change the meaning of the whole. In practice,
the same letter can represent several separate bound variables (with
separate boxes), that can take different values without conflict, as
no two of them are anywhere free together to compare their values.
The common language does this continuously, using very few variable
symbols («he», «she», «it»...)
Functions
A function is any object f behaving as a variable whose value
is determined by that of another variable called its argument; the
argument has a range called the domain of f and denoted
Dom f. Whenever its argument is fixed (gets a name, say
x, and a value in Dom f), f becomes a constant
(written f(x)).
In other words, f is made of the following data:
 A set called the domain of f, denoted Dom
f
 For each element x of Dom f,
an object written f(x), called the image of x
by f or value of f at x.
Operations
The notion of operation generalizes that of function, by
admitting a finite list of arguments (variables with given
respective ranges) instead of one. So, an operation gives a result (a value)
when all its arguments are fixed. The number n of arguments
of an operation is called its arity ; the operation is
called nary. It is called nullary if n=0
(it is a constant), unary if n=1 (it is a function),
binary if n=2, ternary if n=3...
Nullary operations are useless as their role is played by their
unique value; we shall see how to construct those with arity
> 1 by means of functions.
The value of a binary operation f on its fixed arguments
named x and y (i.e. its value when its arguments are
assigned the values of x and y), is denoted
f(x,y).
Generally, instead of symbols, the arguments are represented by the left and
right spaces in parenthesis, to be filled by any expression giving
them desired values.
1.3. Form of theories: notions, objects and metaobjects
The variability of the model
Each consistent theory assumes its model (interpretation) as fixed,
but this is usually a mere «choice» of one model in a wide (infinite)
range of other existing, equally legitimate models of the same
theory; the model becomes variable when viewed by model theory. But,
this «choice» and this «existence» of a model can be quite abstract.
In details, the proof
of the Completeness theorem, in the way it can work in all
cases, will effectively «specify» a model in the range of
possibilities, but this construction is not really explicit
(involving an infinity of steps, where each step depends on an
infinite knowledge). In these conditions, the assumption of fixation
of a model may be called nonsense, but nevertheless constitutes the
standard interpretation of mathematical theories.
Notions and objects
Each theory has its own list of notions, usually designated
by common names, that are the kinds of variables used by the theory
; each model (interpretation of the theory) interprets each notion as a
set that is the common
range of all variables of this kind. For example, Euclidean geometry
has the notions of «point», «straight line», «circle» and more. The
objects of a theory in a model, are all the possible values
of its variables (the elements of its notions) in this model.
Onemodel theory
When we discuss several theories T and systems M
that may be models of those T, we are in the framework of
model theory, with its notions of «theory» and «system» that are
the respective kinds of the variables T and M. But when
we focus the study on one theory (such as a set theory) with a
supposedly fixed model, the variables T and M become
fixed and disappear (they are not variables anymore, the choice of the
theory and the model becomes implicit). So, the notions of theory and
model disappear from the notions list too.
This fixation reduces the framework, from model theory, to that of
onemodel theory. A model of onemodel theory, is a system
[T,M] that combines a theory T with a model
M of T.
On the diversity of logical frameworks
Before giving a theory T, we must specify its logical
framework (its format, or grammar), that describes the admissible
forms of contents for T, what such contents mean about M,
and how their consequences can be deduced. This framework is given
by the choice of a precise version of onemodel theory, that describes
T and interprets its claims.
We shall first describe two of the main logical frameworks in parallel.
Theories in the most common framework of firstorder
logic, will be called here generic theories. Set
theory will be expressed in is own special framework. More
frameworks will be introduced in Part 3.
The most common logical frameworks except the special one
of set theory, will manage notions as types (usually in
finite number for each theory) classifying both variables and
objects: each object will belong to only one type, the one of
variables that can name it. For example, an object of Euclidean
geometry may be either a point or a straight line, but the same
object cannot be both a point and a straight line.
Examples of notions from various theories
Theory 
Kinds of objects (notions) 
Generic theory 
Pure elements classified by types 
Set theory 
Elements, sets, functions, operations,
relations, tuples... 
Model theory 
Theories, systems and their components
(listed next line) 
Onemodel theory

Objects, symbols, types, structures,
expressions (terms, formulas)... 
Arithmetic 
Natural numbers 
Linear Algebra 
Vectors, scalars... 
Geometry 
Points, staight lines, circles... 
Metaobjects
The notions of a onemodel theory T_{1}, normally
interpreted in [T,M], classify the components of T
(«type», «symbol», «formula»...), and those of M («object»,
and tools to interpret T there). But the same notions (even if from
a different version of onemodel theory) can be interpreted in
[T_{1}, [T,M]], by putting the prefix meta on them.
By its notion of «object», onemodel theory distinguishes the
objects of T in M among its own objects in [T,M],
that are the metaobjects. The above rule of use of the meta prefix
would let every object be a metaobject; but we will make a
vocabulary exception by only calling metaobject those which
are not objects: symbols, types (and other notions), structures,
expressions...
Set theory only knows the ranges of some of its own variables, seen
as objects (sets). But, seen by onemodel theory, every variable of
a theory has a range among notions, which are metaobjects only.
Components of theories
Once chosen a logical framework, the content of a theory (or its foundation,
i.e. its initial content, describing the form of its intended
models), consists in a choice of 3 successive lists of components,
where those in each list are used to build those of the next list:
 A list of abstract types to serve as the names of types;
 A language (vocabulary): list of structure
symbols, names of structures relating objects to form systems (see 1.4).
 A list of axioms (among ground formulas of the
theory, see 1.5.).
Settheoretical interpretation
Any generic theory (and its model, if considered) can be inserted
(translated) into set theory by converting its components into
components of set theory. Let us present both the generic method
which works for any generic theory, and the different (nongeneric)
method that is usually preferred for the case of geometry.
In all cases, abstract types become fixed variables (or new constant symbols)
whose values are sets called interpreted
types (the respective ranges of variables of each type). For geometry, both
abstract types «Point» and «Straight line» become fixed
variables P and L, respectively designating the set
of all points, and the set of all straight lines.
The use of variable symbols will be left intact, taking values among some objects of set
theory (but not all).
While some objects of geometry, such as straight lines, are usually interpreted as
sets (of points), the generic method only uses pure elements as objects (or we may be ambiguous by calling them elements even if they are not pure).
The generic method will also convert structure symbols into fixed variables.
The interpretations of types and structure symbols (their values as fixed variables)
will determine the model, as they are its main components. The model,
which thus varies with these variables, is itself an object of set theory. This
integrates all theories we need as parts of the same set theory, while
gathering all their models inside a common model of set theory. This is
why models of set theory will be called universes.
1.4. Structures of mathematical systems
The structures, interpreting the language of a theory
(values of structure symbols in a set theoretical interpretation), relate
the objects of diverse types to form the studied system. These
structures let objects of each type play diverse roles in the
system. According to these roles, objects may be interpreted as
complex objects, in spite of their basic nature of pure elements.
Generic theories admit 2 kinds of structures (and thus of structure
symbols): operators and predicates.
An operator is an operation between interpreted types.
On the side of the theory before interpretation, each operator
symbol comes with the data of its arity (or list of arguments seen
as places around the symbol), the type of each argument (which
will range over the interpreted type), and the unique type of all
its values (results of the operation).
The constant symbols (or constants) of a theory are its nullary operator
symbols.
Unary operators (that are functions) will be called here a functors
(this should not be confused with the concept of functor in category theory).
The list of types is completed by the Boolean type,
interpreted as the pair of elements 1 («true») and 0 («false»). A
variable of this type (outside the theory) is called a Boolean
variable.
A paraoperator is a generalized operator allowing the
Boolean type among its types of arguments and results.
A (logical) connective is a paraoperator with only Boolean arguments
and values.
A predicate is a paraoperator with Boolean values and at
least one argument but no Boolean one.
Structures of set theory
Let us start formalizing set theory with 3 primitive notions
(sorts of objects) : elements (all objects), sets and functions.
This formalization will be progressively developed as needed, with
other notions that may be seen either as primitive or derived from
the former, and other symbols contributing to give their roles to
all kinds of objects. But this formalization work requires to
ignore the above set theoretical interpretation of theories, as
both links between formalized generic theories and set theory
should not be confused (the set theoretical translation of
theories is not yet applied to set theory itself, this will be discussed
in 1.7).
One way for set theory to give sets their role is by the binary
predicate ∈ : for any element x and any set E, we
say that x is in E (or belongs to E, or is
an element of E, or that E contains x) and
write x ∈ E, to mean that x is among the
values of a variable with range E.
Functions f play their role by two operators: the domain
functor Dom, and the function evaluator, binary operator
that is implicit in the notation f(x), with arguments
f and x, giving the value of any function f
at any element x in Dom f.
About ZFC axiomatic set theory
The ZermeloFraenkel axiomatic set theory (ZF, or ZFC with the axiom
of choice) is a generic theory with only one type «set», one
structure symbol ∈ , and axioms. It implicitly assumes that every
object is a set, and thus a set of sets and so on, built over the
empty set.
Specialists of mathematical logic chose it for their need of a
powerful theory in an enlarged founding cycle, by which they can
prove many difficult formulas or their unprovability. Then, authors
of basic courses usually present set theory as a popularized or
implicit version of the ZFC theory, admitted as the standard
reference, as if this was necessary or obvious (as an intuititively
motivated axiomatic system, historically selected for its consistency and the
convenience of its results).
But for a start of mathematics, ZF(C) is not an ideal reference. Its
axioms (descriptions of the universe that must assume the framework
of model theory to make sense) would deserve more subtle and complex
justifications than usually assumed. Ordinary mathematics, using
many objects usually not seen as sets, are only inelegantly
formalized on this basis. As the roles of all needed objects can
anyway be indirectly played by sets, they did not require another
formalization, but remained cases of discrepancy between the
«theory» and the practice of mathematics.
Types in onemodel theory
As onemodel theory ignores the diversity of possible models, its notion of type
can be formalized ignoring the more general (set theoretical) notion of
«set of objects» (of which the interpreted types are particular cases), as
just one metanotion playing both roles of abstract types (in the theory)
and of interpreted types (components of the model) : these roles are
given by metafunctors, one from variables to types, and one from objects to
types. A larger range of notions, the classes, will be introduced in 1.7.
Structures in onemodel theory
Similarly, the role of «structures» (that is an operation between
interpreted types, with Boolean values if a predicate) can be
formalized by metastructures (similar to the function evaluator).
Unlike interpreted types (all named by abstract types), our notion
of structure in onemodel theory will be larger than that of values
of the symbols in the given language. For this, structures will be
another metatype with a metafunctor from symbols to structures.
However, this mere formalization would leave the exact extension of
this notion of structure undetermined.
Trying to conceive this range as that of «all operations between
interpreted types» would leave unknown the source of knowledge of
such a totality. This idea of totality will be formalized in set
theory as the powerset (2.5.), but its meaning would still depend on
the universe where it is interpreted (assumed to contain all wanted
operations), far from our present concern for onemodel theory.
Instead, we will fix in 1.5 the notion of structure as given by those
definable by expressions.
1.5. Expressions and definable structures
Terms and formulas
Given the first two layers of a theory (a list of types and a
language), an expression is a finite system of occurrences
of symbols, that will define a value for each possible data of a
model (system interpreting the given types and structure symbols,
ignoring axioms) and of an
interpretation of the free variables it contains (their values in
the model).
Any expression is either a term or a formula:
the values of terms will be objects, while formulas
will have boolean values.
A ground expression,
is an expression with no free variable (all its
variables are bound) so that its value only depends on the model.
The axioms of a theory are chosen among its ground formulas.
Let us sketch the general description of expressions (that will
be formalized in Part 3).
An occurrence of a symbol in an expression is a place where
it is written, for example «x + x» has two
occurrences of x and one of +.
Expressions may use symbols of the following kinds.
 Variables of each type (either free, or bound by the use of a
binder) ;
 Paraoperator
symbols:
 Structure symbols (operators and predicates, from the
language) ;
 One equality symbol per type (predicate with 2 arguments of
the same type) abusively all written = and interpreted in the
standard way ;
 Logical connectives ;
 Binders
(1.8.): the only ones in firstorder logic are the two
quantifiers (∀ and ∃, see 1.9.), but our set theory will have
more.
Expressions are built successively.
The first and simplest ones are made of just one symbol already
having a value by itself: constants and variables are the first terms; the
Boolean constants 1 and 0 are the simplest formulas.
The next expressions are then successively built as made of the
following data:
 A distinguished choice (occurrence) of a symbol (paraoperator
or binder) called the root of the expression;
 One or more variable symbols (to bind) if the root is a
binder;
 A list of occurrences of previously built expressions.
The root determines the type of values (thus decides if the
expression is a formula or a term) and the format of the list (the
number and types of entries). For paraoperator symbols, this format
is given by the list of arguments.
The list was empty for constants, that, as roots, formed expressions
alone. Other paraoperators and binders need a nonempty list, which
requires a choice of display convention:
 Most binary paraoperator symbols are displayed as one
character between both arguments, such as x+y
 Symbols with higher arities can be similarly displayed by
several characters delimiting the entries.

Functionlike displays, such as +(x,y), are more
usual for arities other than 2.

A few symbols «appear» only by their special way of putting
their arguments together (multiplication, exponentiation).

Parenthesis can be part of the notation of a
symbol (function evaluator, tuples...).
Parenthesis can also be used, for each expression or subexpression,
to distinguish the root by separating the
subexpressions, as in (x+y)^{n}.
Variable structures
Only few objects are usually named by the constant symbols in a
given language. Any other object can be named by another
symbol outside this language: a fixed variable. This may be
differently interpreted depending on the theory we consider to be in:
 As a simple variable symbol (allowed in expressions though
not «in the language» of the theory): we can form an
expression in the theory about all objects of one
type, by using and binding this variable.
 As a new constant symbol, added to the language, with a
specific name for one specific value: we get a richer language,
for another theory. The different possible values are seen as
corresponding to different models.
Trying to generalize this, from simple objects (identifiable with
all nullary operations that may exist between interpreted types),
to other structures (with nonzero arity), we get the concept of a
symbol of variable structure, but this escapes the above
list of symbols allowed in expressions. Thus, the status for
expressions using such a symbol must now be chosen between
 An extended logical framework accepting variable structure
symbols (such as secondorder logic, see Part 3);
 Again, an extended theory where this symbol is added to the langage.
 A special purpose : definitions of binders (1.11)
As a theory in firstorder logic cannot handle the full range of a
variable structure with nonzero arity (unless all its arguments
range over finite sets), it cannot express all properties of this
range. Still some properties can be known as follows: if a formula
with a symbol of variable structure (not defined) is formally
proven, then it is true for all structures it might mean, no matter
if they «can be found» or not. This concept of provable
universal truth will be used as a rule of proof for ordinary
variables (principle of Universal Introduction in 1.9) and in the
formulation of the set generation principle (1.11).
Structures defined by expressions
Any theory can produce structures (operators or predicates,
beyond those directly named in its language),
as the operations between interpreted types, defined by the
following data:
 An expression (operators are defined by terms, while
predicates are defined by formulas);
 A list of some of its free variables (maybe not all used) to be bound
by this definition in the role of arguments of the intended structure; other
free variables are called parameters;
 Fixed values of parameters.
Nullary operators (simple objects) are «defined» this way by the term made
of a variable symbol seen as parameter.
In a formalization of set theory, any function f
is synonymous with the
functor defined by the term «f(x)» with argument x
and
parameter f.
We can accept as a legitimate work inside the theory, to name such
a structure by a symbol of variable structure, meant as an
abbreviation of the expression with its parameters.
As the variability of the symbol abbreviates the one of parameters,
this variable structure can be bound in the theory as ranging over all
structures defined by a common expression with all
possible values of its parameters : this just abbreviates
the act of binding these parameters.
Let us now fix onemodel theory's notion of
structure, and thus those of operator and predicate,
as made of all those which can be reached in this way: defined
by any expression with any possible values of parameters. As
this involves the infinite set of all expressions, it escapes the
abilities of the studied theory (which can only use one expression
at a time) and is only accessible by the framework of onemodel
theory with its metanotion of expression. Still this does not
mean to exhaust the range of all operations (between interpreted
types) which may exist in the universe of a set theoretical framework,
as there may be undefinable structures.
Invariant structures
An invariant structure for a theory, is a structure defined without
parameters (thus a constant one).
Any structure named by a symbol in the language of a theory, is directly
defined by it without parameter, and thus invariant for this theory.
This distinction of invariant structures from other structures, generalizes
the distinction between constants and variables, both to cases of
nonzero arity, and to what is indirectly expressible by the theory
instead of directly named in its language.
Invariant structures not yet in the language can be named by
new symbols to be added there, preserving the deep meaning
of the theory (metanotions of structure, invariant structure,
provability...). Such rules to develop a theory will be
discussed in Part 3.
1.6. Logical connectives
We already saw the nullary connectives : the Boolean constants 0
(false) and 1 (true).
The binary connective of equality between Booleans is written ⇔ and
called equivalence: A ⇔ B is read «A
is equivalent to B».
Let us present other useful connectives, with their properties true
for all possible values of the Boolean variables (A, B,
C, that can be replaced by formulas).
Negation
The only useful unary connective is the negation ¬, that
exchanges Booleans (¬A is read «not A»):
It is often denoted by barring the root of its argument, forming
with it another symbol with the same format:
x ≠ y
x ∉ E
(A ⇎ B)
(A ⇎ B)

⇔ ¬(x=y)
⇔ ¬(x ∈ E)
⇔ ¬(A ⇔ B)
⇔ (A ⇔ ¬B))

(x is not equal to y)
(x is not an element of E)
(Inequivalence) 
Conjunctions, disjunctions
The conjunction ∧ means «and», being true only when both
arguments are true;
The disjunction ∨ means «or», being true except when both
arguments are false.
Each of them is :
Idempotent
(A ∧ A) ⇔ A
(A ∨ A) ⇔ A

Commutative
(B ∧ A) ⇔ (A ∧ B)
(B ∨ A) ⇔ (A ∨ B)

Associative
((A ∧ B) ∧ C) ⇔ (A
∧ (B ∧ C))
((A ∨ B) ∨ C) ⇔ (A ∨ (B
∨ C))

Distributive over the other
(A ∧ (B ∨ C)) ⇔ ((A
∧ B) ∨ (A ∧ C))
(A ∨ (B ∧ C)) ⇔ ((A ∨ B)
∧ (A ∨ C))

The symmetry between them comes from the fact they are exchanged by
negation:
(A ∨ B)
⇎ (¬A ∧ ¬B)
(A ∧ B) ⇎ (¬A ∨ ¬B)
Strings of conjunctions such as (A ∧ B ∧ C),
abbreviate any formula with more parenthesis such as ((A ∧ B)
∧ C), which are equivalent to each other thanks to
associativity ; and similarly for strings of disjunctions such as (A
∨ B ∨ C).
Asserting a conjunction of formulas amounts to successively
asserting all these formulas.
The inequivalence ⇎ is also called «exclusive or» because (A
⇎ B) can also be written ((A ∨ B) ∧ ¬(A
∧ B)).
Implication
The binary connective of implication ⇒ is defined as (A ⇒ B) ⇔ ((¬A)
∨ B). It can be read «A implies B», «A
is a sufficient condition for B», or «B is a
necessary condition for A». Being true except when A
is true and B is false, it expresses the truth of B
when A is true, but no more gives information on B
when A is false (as it is then true).
Moreover,
(A ⇒ B) ⇎
(A ⇒ B) ⇔ 
(A ∧ ¬B)
(¬B ⇒ ¬A) 
The formula ¬B ⇒ ¬A is called the contrapositive
of A ⇒ B.
The equivalence can also be redefined as
(A ⇔ B) ⇔ ((A ⇒ B) ∧ (B
⇒ A)).
Thus, a proof of A ⇔ B can be made of a proof of the
first implication (A ⇒ B), then a proof of the second
one (B ⇒ A), called the converse of (A
⇒ B).
The formula (A ∧ (A ⇒ B)) will be abbreviated
as A ∴ B, which reads «A therefore B».
It is equivalent to (A ∧ B), but indicating
that it is deduced from the truths of A and (A
⇒ B).
Negations transform the associativity and distributivity formulas of
conjunctions and disjunctions, into various formulas with
implications:
(A ⇒ (B ⇒ C)) ⇔ ((A ∧ B) ⇒ C)
(A ⇒ (B ∨ C))
⇔ ((A ⇒ B) ∨ C)
(A ⇒ (B ∧ C)) ⇔
((A ⇒ B) ∧ (A ⇒ C))
((A ∨ B) ⇒ C) ⇔
((A ⇒ C) ∧ (B ⇒ C))
((A ⇒ B) ⇒ C) ⇔
((A ∨ C) ∧ (B ⇒ C))
(A ∧ (B ⇒ C)) ⇔
((A ⇒ B) ⇒ (A ∧ C))
Finally,
((A ⇒ B) ∧ (A∧C)) ⇒ (B∧C)
((A ⇒ B) ∧ (A∨C)) ⇒ (B∨C)
Chains of implications and equivalences
In a different kind of abbreviation, any string of formulas
linked by ⇔ and/or ⇒ will mean the conjunction of all these
implications or equivalences between adjacent formulas:
(A ⇒ B
⇒ C) ⇔ ((A ⇒ B) ∧ (B ⇒ C)) ⇒
(A ⇒ C)
(A ⇔ B ⇔ C) ⇔ ((A ⇔ B) ∧ (B
⇔ C)) ⇒ (A ⇔ C)
0 ⇒ A ⇒ A ⇒ 1
(¬A) ⇔ (A ⇒ 0) ⇔ (A ⇔ 0)
(A ∧ 1) ⇔ A ⇔ (A ∨ 0) ⇔ (1 ⇒ A) ⇔ (A
⇔ 1)
(A ∧ B) ⇒ A
⇒ (A ∨ B)
Axioms of equality
For any objects (or abbreviations of terms) x, y,
any functor T and any unary predicate A,
x = y ⇒
x = y ⇒ 
x = x
T(x) = T(y)
(A(x) ⇔ A(y)) 
The last formula can also be written (A(x) ∧ x = y)
⇒ A(y), since the converse A(y) ⇒ A(x)
can be deduced either by its contrapositive (replacing A by
¬A) or by the symmetry of equality (x = y ⇒ y
= x) obtained by taking as A(z) the formula (z = x).
It also gives for all x, y, z, (x = y
∧ y = z) ⇒ x = z. The formula (x = y
∧ y = z) will be abbreviated as x = y = z.
Provability
A proof of a formula A in a firstorder theory T,
is a finite model of proof theory, connecting A to
some axioms of T.
We say that A is provable in T and write T⊢
A if there exists a proof of A in T.
Again in T, a refutation of a formula A is a proof of ¬A. If one exists (T⊢ ¬A), the formula A is called refutable (in T).
A formula is called undecidable (in T) if it is
neither provable nor refutable.
If a formula is both provable and refutable then all are, which
means that the theory is inconsistent: (A ∧
¬A) ⇔ 0
((T⊢ A)∧(T⊢ ¬A))⇔(T⊢ 0).
The theory T is called contradictory or inconsistent
if T⊢ 0, otherwise it is called consistent. In an
inconsistent theory, every formula is provable. Such a theory has no
model.
Without trying to formalize what a proof is, we shall just write
proofs naturally, usually as a succession of formulas, each visibly
true thanks to previous ones and the above properties of connectives
and equality. Natural language articulations may also appear,
especially when dealing with quantifiers
(1.9) and introducing symbols defined by expressions.
In particular, an equality between terms x = y
allows to replace any occurrence of x by y in any
expression without affecting the result; when a symbol is defined by
a term, both are equal, thus can be substituted to each other in any
expression. Axioms and other rules expressed with variable symbols
(under universal quantifiers, see 1.9) can then be used replacing
these variables by terms.
Provable
formulas with a known proof (either by humans or by
computers) can be differently named in usual language according to their
importance: a theorem is more important than a proposition; either of them
may be deduced from an otherwise less important lemma, and a corollary may be
easily deduced from it.
1.7. Classes in set theory
The unified framework of theories
Attempts to formalize onemodel theory in firstorder logic, would fail
to exclude infinitely large «expressions» and «proofs»: this needs
an axiom in secondorder logic, best expressible only after insertion into set theory (though this solution remains incomplete, as will be explained in Part 3).
As the components of its model [T, M] are named there by free
variables, their variability makes this the settheoretical expression
of model theory (which, together with the axiomatization of set theory,
will complete
the grand tour of the foundations of mathematics).
Now let T_{0} be the external copy of T, i.e. the theory
(integrated in the formalism of set theory but not part of its universe of objects) whose components k
(types, symbols, axioms) have copies as objects which are the truly finite
components of T. Formally, T_{0} is made of the k such that
«k» ∈ T, where the notation as a quote
«k» abbreviates a ground term of set theory describing k
as an object. By this correspondence, any (modeltheoretical) model
M of T is indirectly also a (settheoretical) model of T_{0}.
This gives a powerful framework for the interpretation of
T_{0} in M, encompassing both previous
(settheoretical and modeltheoretical) frameworks of interpretations
of theories in models. Namely, all works (expressions, proofs and
other developments) done in T_{0}, have copies as
objects in the system T (system of objects described by set
theory as having the formal property of «being a theory»);
meanwhile, the (set theoretical) model M of T_{0}
is formally seen as a «model of T», in the
modeltheoretical sense formalized inside the same settheoretical
framework, as it belongs to the same universe as T.
However, the power of this interpretation comes with a cost in legitimacy:
for an externally given theory T_{0} with infinitely many
components, we cannot directly define a corresponding T,
as a set cannot be formally defined as exactly made of the values of
a infinite list of terms (which are only metaobjects). We can work
starting from a T_{0} only if its infinities of components are
produced by some rules, for getting T as defined by the same
rules. Then, no matter if T_{0} is finite or not, the existence
of a model M of T, reflecting the consistency of T as
defined inside the universe, does not automatically result from the
consistency of T_{0} (as seen outside the universe).
These consequences of the completeness and incompleteness
theorems will be explained later.
Classes, sets and metasets
For any theory, a class is just a unary predicate A reinterpreted
as the set of objects where A is true, that is «the
class of the x such that A(x)».
In particular
for set theory, each set E is synonymous with the class of the x
such that x ∈ E (defined by the formula
x ∈ E with argument x and parameter E).
However, this involves two different interpretations of the concept of set,
that need to be distinguished as follows.
From now on, in the above unified framework, the theory to be used as
T_{0}, interpreted in the model M and studied
as an object T, will be set theory itself (expressible as a
generic theory as explained in 1.9 and 1.10). Thus, our above
use of set theoretical concepts as the framework describing
the surrounding universe, is now a copy of T_{0}
but with a different interpretation, that will be distinguished by carrying
the meta prefix. Set theoretical concepts in M can be nicely
reflected by their meta interpretation, but both should not be confused.
Instead of the generic representation of all objects of generic
theories as pure metaelements, the role of each object «set» of
set theory will usually be played by the class (metaset) of its elements;
similarly, the role of functions will be played by the corresponding functors.
This way, any set will be a class, while any class is a metaset of objects. But some
metasets of objects are not classes (they cannot be defined by any formula with
parameters); and some classes are not sets, such as the universe (class
of all objects, defined by 1), and the class of all sets, according to Russell's
paradox (1.8).
Definiteness classes
In set theory, all objects need to be accepted as «elements» that can
belong to sets and be operated by functions (to avoid illimited
divisions between sets of elements, sets of sets, sets of functions, mixed sets...).
This might be formalized by keeping 3 types where each set would
have a copy among elements (identified by a functor from sets to elements),
and the same for functions. But it would not suffice to our set theory,
that will need more notions beyond those of set and function. For this, our set
theory will use classes instead of types as its notions. In particular, the
notions of set and function will be classes named by predicate symbols:
Set = «is a set»
Fnc
= «is a function»
In generic theories, the syntactic correction of an expression (that is implicit in the
concept of «expression») ensures that it will take a definite value, for
every data of a model with an interpretation of its free variables there.
But in set theory, this may still depend on the values of its free variables.
So, an expression A (and any structure defined from it) will be called
definite, if it actually takes a value for the given values of its free variables
(arguments and parameters) in the model. This definiteness condition is
itself an everywhere definite predicate, expressed by a formula we shall
abbreviate here as dA, with the same free variables.
Classes are defined by definite unary predicates. The metadomain of any unary structure A, is the class defined by dA, with the same argument and parameters, called its class of definiteness.
Expressions should be only used where they are definite, which will be done rather naturally.
The definiteness condition of (x ∈ E) is Set(E). That of the function evaluator f(x) is (Fnc(f) ∧ x∈ Dom f).
But the definiteness of the last formula needs a justification, which will be given below.
Extended definiteness
A theory with partially definite structures can be formalized (translated) as a theory with one type and everywhere definite structures, keeping intact all expressions and their values wherever they are definite : models are translated one way by giving arbitrary values to indefinite structures (e.g. a constant value), and in the way back by ignoring those values. Thus, an expression with an indefinite subexpression may be declared definite if its final value does not depend on these extra values.
For all predicates A and B, let us give to A ∧ B and
A ⇒ B the same definiteness condition (dA ∧ (A ⇒ dB))
(breaking, for A ∧ B, the symmetry between A
and B, that needs not be restored). They will thus be seen definite (with
respective values 0 and 1) if A is false and B is not definite.
This makes definite the definiteness conditions themselves, as well as dA ∧ A and dA ⇒ A (extending A where it was not definite, by 0 and 1 respectively). This way, both formulas A ∧ (B ∧ C)
(A ∧ B) ∧ C have the same definiteness condition (dA ∧ (A ⇒ (dB ∧ (B ⇒ dC)))).
For any class A and any unary predicate B definite in all A, the class defined by the (everywhere definite) predicate A∧B, is called the subclass of A defined by B.
1.8. Binders in set theory
The syntax of binders
The last kind of symbols forming expressions is the binders (binding
symbols).
Such a symbol binds one (or more) variable(s) (say
x), on an expression F which may use x as a
free variable in addition to the free variables that are available (with
a value) outside. Thus, it separates the «inside» subexpression F
using x as free, from the «outside» where x is
bound. Applied to the data of the symbol x and the
expression F, it gives a value depending on the unary
structure defined by F with argument x (but cannot
generally give a whole faithful image of this unary structure, which
may be too complex to be fully recorded as a mere object).
The syntax differs between set theory and generic theories, which
manage the range differently. In generic theories, ranges are types,
implicit data of quantifiers. But binders of set theory make their
variable range over a set, that is an object designated by an
additional argument (a space for a term not using the bound variable).
An expression is ground if all its variables are bound
(their occurrences are contained by binders).
Let us review the main binders in set theory.
Definitions of functions by terms
The function definer ( ∋ ↦ ) binds a variable on a term,
following the syntax (E ∋ x ↦ t(x)),
where x is the variable, E is its range, and t(x)
is the term (here abbreviated as a unary predicate with possible
implicit parameters); it may be shortened as (x ↦
t(x)) when E is determined by the context.
It is definite if t(x) is definite for all x in E;
it takes then the functor defined by t and restricts its
definiteness class to E, to give it as a function with
domain E.
So it converts functors into functions, reversing the action
of the function evaluator that converted functions into
their role (meaning) as functors whose definiteness
classes were sets.
This uniformizes the functors (which were only indirectly available
to be used as functions by their defining term that could have
unlimited complexity) as a unique kind of objects.
In 1.10. we will formalize this tool and see it as a particular case
of a more general principle for set theory.
Relations and setbuilder symbol
A relation is an object similar to an operation but with Boolean values:
it acts as a predicate whose arguments range over sets. But this
does not need to be introduced as another kind of objects,
as sets will suffice to play these roles.
For any unary predicate A definite in a set E, the
subclass of E defined by A is a set (range of a
variable x introduced as ranging over E, so that it
can be bound, from which we select the values satisfying
A(x)), thus a subset of E, written
{x∈E  A(x)}
(set of all x in E such that A(x)): for
all y,
y ∈ {x∈E  A(x)}
⇔ (y ∈ E ∧ A(y))
The binder { ∈  }, is named the setbuilder: {x∈E  A(x)}
binds x with range E on A. It will be used as a
definer for unary relations on E, figured as subsets F
of E, evaluated by ∈ as predicates (x ∈ F)
with argument x. But these predicates are not only definite
in E but in the whole universe, giving 0 outside E whose
data is lost. This lack of operator Dom
does not matter, as the domain E is usually determined by
the context.
As the function definer (resp. the setbuilder) records the whole
structure defined by the given expression on the given set, it
suffices to define any other binder on the same expression with the
same domain, as made of a unary structure applied to its
result (that is a function, resp. a set).
Of course, if the class of all objects was a set then the set
builder could use it to also convert all classes into sets. But this
is not possible: the class of all sets cannot be a set (no set E
can ever contain all sets), as can be shown using the set builder
itself:
Theorem. For any set E there is a set F
such that F ∉ E.
Proof. F={x∈E  Set(x) ∧ x ∉ x}
⇒ (F ∈ F ⇔ (F ∈ E ∧ F ∉ F))
⇒ (F ∉ F ∴ F ∉ E). ∎
This will oblige us to keep the distinctions between sets and
classes.
1.9. Quantifiers
A quantifier is a binder taking a unary predicate (formula) and giving a
Boolean value.
In set theory, the full syntax for a quantifier Q binding a
variable x with range E on a unary predicate A,
is
Qx ∈ E, A(x)
where A(x) abbreviates the formula defining A,
whose free variables are x and possible parameters.
A shorter notation puts the domain as an index (Q_{E}x,
A(x)), or deletes it altogether (Qx, A(x))
when it may be kept implicit (unimportant, or fixed by the context, such
as a type in a generic theory).
The two main quantifiers (from which others will be defined later) are:
 The existential quantifier ∃, read as «There exists x
(in...) such that... »
 The universal quantifier ∀, read as «For all x (in...),... »).
Their interpretation can be defined in a set theoretical framework considering
A as a function, and treating its boolean values as objects:
(∀x, A(x))
⇔ A = (x ↦ 1)
(∃x, A(x)) ⇔ A ≠ (x ↦ 0)
(∀x, A(x)) ⇎ (∃x, ¬A(x))
In set theory, (∀x∈E, A(x)) ⇔ {x∈E
 A(x)} = E. The formula (∀x,1)
is always true. With classes,
(∃_{C } x, A(x))
(∀_{C } x, A(x))
∀x, (C(x)

⇔ (∃x, C(x) ∧ A(x))
⇔ ∃_{C∧A} x, 1
⇔ (∀x, C(x) ⇒ A(x))
⇔ (∃_{C } y, x=y))

Inclusion between classes
A class A is said to be included in a class B when ∀x,
A(x) ⇒ B(x). Then A is a
subclass of B, as ∀x, A(x) ⇔ (B(x)
∧ A(x)). Conversely, any subclass of B is
included in B.
The inclusion of A in B
implies for any predicate C (in cases of definiteness):
(∀_{B}
x, C(x)) ⇒ (∀_{A} x,
C(x))
(∃_{A} x, C(x)) ⇒ (∃_{B}
x, C(x))
(∃_{C }x, A(x)) ⇒ (∃_{C
}x, B(x))
(∀_{C }x, A(x)) ⇒ (∀_{C
}x, B(x))
Rules of proofs for quantifiers on a unary predicate
Existential Introduction. If we have terms t,
t′,… and a proof of (A(t) ∨ A(t′)
∨ …), then ∃x, A(x).
Existential Elimination. If ∃x, A(x),
then we can introduce a new free variable z with the
hypothesis A(z) (the consequences will be
true without restricting the generality).
These rules express the meaning of ∃ : going from t, … to
∃ then from ∃ to z, amounts to letting z represent
one of t, t′, … (without knowing which). They give
the same meaning to ∃_{C } as to its 2 above
equivalent formulas, bypassing (making implicit) the extended
definiteness rule for (C ∧ A) by focusing on the
case when C(x) is true and thus A(x)
is definite.
While ∃ appeared as the designation of an object, ∀ appears as a
deduction rule: ∀_{C }x, A(x)
means that its negation ∃_{C }x, ¬A(x)
leads to a contradiction.
Universal Introduction. If from the mere hypothesis C(x)
on a new free variable x we could deduce A(x),
then ∀_{C }x, A(x).
Universal Elimination. If ∀_{C }x,
A(x) and t is a term satisfying C(t),
then A(t).
Introducing then eliminating ∀ is like replacing x by t
in the initial proof.
Deductions can be made by these rules, reflecting formulas
((∀_{C }x, A(x))
∧ (∀_{C }x, A(x) ⇒ B(x)))

⇒ (∀_{C }x, B(x)) 
((∃_{C }x, A(x))
∧ (∀_{C }x, A(x) ⇒ B(x)))

⇒ (∃_{C }x, B(x)) 
(∀_{C }x, A(x))
∧ (∃_{C }x, B(x))) 
⇒ (∃_{C }x, A(x) ∧
B(x)) 
(∃_{A} x, ∀_{B}
y, R(x,y)) 
⇒ (∀_{B}y, ∃_{A} x,
R(x,y)) 
Status of open quantifiers in set theory
Set theory is translated to a generic theory by converting to
classes the domains of quantifiers:
(∃x∈E,
A(x)) → (∃x, x ∈ E ∧ A(x))
(∀x∈E, A(x)) → (∀x, x
∈ E ⇒ A(x))
Set theory only admits quantifiers over sets, called bounded
quantifiers, in its formulas (also called bounded formulas
for insistence) that define predicates and can be used in terms. But
its translated form as a generic theory allows quantifiers on
classes (or the universe), called open quantifiers.
Formulas with open quantifiers in set theory will be called statements.
Their use will be essentially restricted to declarations of truth of
ground definite statements. These will first be axioms, then theorems
deduced from them.
Open quantifiers in statements will usually be expressed as common
language articulations (naturally using the above rules of proofs)
between their bounded subformulas written in settheoretic symbols.
The setbuilder K = {x∈E A(x)}
was defined by a statement (∀x, x∈K ⇔
(x∈E ∧ A(x))) but 1.11 will
redefine it without open quantifier (except on its parameters).
1.10. Formalization of set theory
The inclusion predicate
The inclusion predicate ⊂ between two sets E and F,
is defined by E ⊂ F ⇔
(∀x∈E, x
∈ F).
It is read: E is included in F, or E
is a subset of F, or F includes E.
We always have E ⊂ E (as it means: ∀x, x
∈ E ⇒ x ∈ E).
Implications chains also
appear as inclusion chains:
(E ⊂ F ⊂ G) ⇔ (E ⊂ F
∧ F ⊂ G) ⇒ E ⊂ G.
Translating the definer into firstorder logic
The translation of set theory into a generic theory converts the
function definer into an infinity of operator symbols: for each term
t with one argument (and parameters), the whole expression (E
∋ x ↦ t(x)) is seen as the big name of a
distinct operator symbol, whose arguments are E and the
parameters of t. (Those where every subexpression of t
without any occurrence of x is the only occurrence of a
parameter, would suffice to define others). The same goes for the
set builder, which will come as a particular case in 1.11.
This way, the axioms list of set theory can be regarded as the
axioms list of the generic theory into which set theory is
converted. All axioms which depend on an expression (a term for the
definer, or a formula for the set builder) are schemas of axioms. (A
schema of claims, i.e. axioms or theorems, is an infinite list of
claims, usually obtained by replacing an extra structure symbol by
any possible defining expression).
First axioms
∀x,
∀_{Fnc} x, 
¬(Set(x) ∧ Fnc(x))
Set(Dom x) 
∀E,
∀(parameters),
∀_{Set}E, ∀_{Set}F, 
Fnc(E ∋ x ↦ t(x)) for any term t
E ⊂ F ⊂ E ⇒ E=F
(Axiom of Extensionality). 
The latter redefines equality between sets from their equivalence as
classes (letting elements in bulk): E ⊂ F ⊂ E
means that E and F have the same elements (∀x,
x ∈ E ⇔ x ∈ F) so that for any
predicate R,
(∀x ∈ F, R(x)) ⇔ (∀x
∈ E, R(x))
and similarly for ∃.
Axioms for functions. For any functor t (to be
replaced by all terms that can define it), we have the following
axioms, where the first one sums up the other 3 : for all values
of parameters of t, any set E included in the
definiteness class of t (this condition ∀x∈E, dt(x) is the definiteness condition for (E ∋ x ↦ t(x))), and all functions
f and g,
f = (E ∋ x ↦ t(x))
⇔ ( Dom f = E ∧ (∀x∈E, f(x)
= t(x)))
Dom (E ∋ x ↦ t(x)) = E
∀x ∈ E, (E ∋ y ↦ t(y))
(x) = t(x)
(Dom f = Dom g ∧ ∀x∈Dom f, f(x)
= g(x)) ⇒ f = g
A general principle for the formalization of set theory
For any kind of metaobjects indirectly expressible and usable like
objects in expressions, set theory will be enriched with tools to
directly present them as objects. Namely, classes behaving as sets
will be convertible into sets (1.11), and indirectly specified
elements will become directly specified (2.4). But when the indirect
expression of metaobjects (here, functors) may run over an
infinity of possible expressions (here, any term), another reason is
needed to see all these metaobjects as definite objects of a single
kind (functions): the reason here is that the domains of these
functors are sets, given as an argument to the definer. Otherwise,
there cannot be a class of all functors, nor of all classes: naively
trying to insert this in the same universe might lead to
contradictions by reasonings like the proof of Russell's paradox.
Metaobjects behaving as objects with another role beyond sets
and functions, will be represented as another kind of objects
(operations, relations, tuples), and the conversion tools from roles
(metaobjects) to objects will be completed by new conversion tools
from objects into their roles. But this can be done inside the same
set theory (just by developing it), as already present objects (sets
or functions) can be found to naturally play the roles of these new
objects. So, the new notions can be defined as classes of existing
objects (that will offer their expressible features to the new
objects), while the tools of interpretation and definition of objets
(converting objects into their roles of metaobjects and inversely)
are defined as abbreviations of some fixed expressions.
Then, the only needed functors of conversion between
objects playing the role of the same metaobject by different
methods (expressions), will relate the different objects of old
kinds that usefully represent in different ways the same object of
the new kind.
Formalization of operations and currying
The notion of nary operation, objects acting as nary
operators between n sets, would be formalized by:
 n domain functors (of little practical use);
 an (n+1)ary operator of evaluation (evaluator) written in filled form as
f(x_{1},…,x_{n}),
with arguments an nary operation f and its
n arguments x_{1},…,x_{n};
 an operation definer, binding n variables to their respective
ranges on a term.
The notion of operation can be represented as a class of functions,
in the following way called currying. The role of operation
definer (binding n variables) is played by the succession of
n uses of the function definer (one for each bound variable);
and similarly as an evaluator, n uses of the function
evaluator. For example (n=2), the binary operation f
defined by the term (binary predicate) t with arguments x
in E and y in F, may be formalized by
f ≈ (E ∋ x ↦
(F ∋ y ↦ t(x,y))) = g
f(x,y) = g(x)(y) = t(x,y)
The intermediate function g(x) = (F ∋ y
↦ t(x,y)) with argument y, sees x
as fixed and y as bound. But this breaks the symmetry between
arguments, and loses the data of F when E is empty but not the
other way round. A
formalization without these flaws will be possible using tuples
(2.1.).
The formalization of nary relations involves an (n+1)ary
predicate of evaluation, and a definer binding n variables
on a formula. We may either see nary relations as
particular cases of nary operations (representing
Booleans as objects), or see nary operations as
particular cases of (n+1)ary relations (see 2.3). And just
like operations, relations can be reduced to the unary case in 2
ways : by currying (with n−1 uses of the function definer
and 1 use of the setbuilder, as will be done in 2.3 with n=2),
or using tuples (2.1).
1.11. Set generation principle
Bounded quantifiers give sets their fundamental role as ranges of
bound variables, unknown by the predicate ∈ which only lets them
play a role of classes. Technically, the bounded quantifier (∃ ∈ , )
suffices to define the predicate ∈ as
x ∈ E ⇔
(∃y∈E, x=y)
but is not definable from it in return in the set theoretical formalism, as the inverse definition
involves an open quantifier.
Philosophically, the perception of a set as a
class (ability to classify each object as belonging to it or not) does not
provide its full perception as a set (the perspective over all its
elements as coexisting).
Set generation principle. For any class C (defined
by a given bounded formula with parameters), if the formula (∀x,C(x)
⇒ A(x)) expressing ∀_{C } on
an undefined unary predicate A (an extra symbol of predicate used ignoring
the possibility to replace it by a formula, as mentioned in 1.5) is proven
equivalent to a bounded formula (here abbreviated as (Qx,
A(x))
like a quantifier), then C is a set that can be named by a new
operator symbol K to be added to the language of set
theory, with arguments the (common) parameters of C and Q,
and axiom :
(For all accepted values of parameters), Set(K)
∧ (∀x∈K, C(x)) ∧ (Qx, x
∈ K).
This equivalence between Q and ∀_{C } is equivalently
expressible as the following list of 3 statements, where the quantifier Q* defined by (Q*x,
A(x)) ⇎ (Qx,¬A(x)) will be
equivalent to ∃_{C}:
(1) ∀x, (C(x) ⇔ Q*y, x=y)
(in fact we just need ∀x, C(x) ⇒ Q*y,
x=y)
(2) Qx, C(x)
(3) For all (undefined symbols of) unary predicates A
and B, (∀x, A(x) ⇒ B(x))
⇒ ((Qx, A(x)) ⇒ (Qx, B(x))).
Indeed these 3 properties are already known consequences of «Q=∀_{C
}». Conversely,
((2) ∧ (3)) ⇒ ((∀_{C }x, A(x))
⇒ Qx,A(x))
((1) ∧ ∃_{C }x, A(x)) ⇒ ∃y,
(Q*x, x=y) ∧ (∀x, x=y
⇒ A(x)) ∴ ((3) ⇒ Q*x,A(x))
∎
(3) will often be immediate, by lack of any troubling occurrence
of A in Q (inside a negation, an equivalence, or left of a ⇒),
leaving us to verify (1) and (2).
Here are examples of such operator symbols (the first column is the
generic abbreviation while others are the effective examples, and
denoting D=Dom f) :
K 
{y ∈ EB(y)} 
⋃E 
Im f 
⌀ 
{y} 
{y,z} 
dK 
∀x∈E, dB(x) 
Set(E) ∧ ∀x∈E, Set(x)

Fnc(f) 
1

1

1

C(x) 
x∈E ∧ B(x) 
∃y∈E, x∈ y 
∃y∈D, f(y)=x 
0

x=y 
x=y ∨ x=z 
Qx, A(x) 
∀x∈E, B(x) ⇒ A(x) 
∀y∈E, ∀x∈y, A(x) 
∀x∈D, A(f(x))

1 
A(y) 
A(y) ∧ A(z) 
Q*x, A(x) 
∃x∈E, B(x) ∧ A(x) 
∃y∈E, ∃x∈y, A(x) 
∃x∈D, A(f(x)) 
0

A(y) 
A(y) ∨ A(z) 
The definition of the set K={x∈E  B(x)},
that was only expressed as a class, can also be written as the
particular case of the above mentioned axiom, i.e.
Set(K) ∧ (∀x∈K,
x∈E ∧ B(x)) ∧ (∀x∈E,
B(x) ⇒ x ∈ K)
or more shortly as
Set(K) ∧ K ⊂ E ∧ (∀x
∈ E, x ∈ K ⇔ B(x))
with which the proof of Russell's paradox would be written
F={x∈E  Set(x)
∧ x∉x} ⇒ ((∀x∈E, x∈F ⇔ (Set(x) ∧ x∉x)) ∧ (F∈F
⇎ (Set(F) ∧ F∉F)))
⇒ F ∉ E
The functor ⋃ is the union symbol, and its axioms form the axiom
of union.
The set Imf of values of f(x)
when x ranges over Dom f,
is called the image of f.
We define the predicate f:E→F as
(f:E→F) ⇔ (Fnc(f) ∧ Set(F)
∧ Domf = E ∧ Imf ⊂ F)
that reads «f is a function from E to F ». A
set F such that Imf ⊂ F
(i.e. ∀x ∈ Dom f, f(x)
∈ F), is called a target set of f.
The more precise (Fnc(f) ∧ Dom f=E ∧ Imf
= F) will be denoted f:E ↠ F (f
is a surjection, or surjective function from E
to F, or function from E onto F).
The empty set ⌀ is the only set without element, and is
included in any set E (⌀ ⊂ E).
Thus, (E=⌀ ⇔ E ⊂ ⌀ ⇔ ∀x∈E, 0), and
thus (E ≠ ⌀; ⇔ ∃x∈E,1).
This constant symbol ⌀ ensures the existence of a set; for any set
E we also get ⌀ = {x∈E  0}.
As (Dom f=⌀ ⇔ Imf=⌀) and
(Dom f=Dom g=⌀ ⇒ f=g), the only
function with domain ⌀ is called the empty function.
We can redefine ∃ from the above in two ways: (∃x∈E,
A(x)) ⇔ {x∈E  A(x)} ≠ ⌀
⇔ (1 ∈ Im(E∋x ↦ A(x))).
For all x, {x,x}={x}. Such a set
with only one element is called a singleton.
For all x, y we have {x, y}={y,
x}. If x ≠ y, the set {x, y}
with 2 elements x and y is called a pair.
Our set theory will later be completed with more symbols and axioms,
either necessary (as here) or optional (opening a diversity of
possible set theories).
Philosophical aspects of the foundations of
mathematics
To complete our initiation
to the foundations of mathematics, the following pages of
philosophical complements (from this one to Concepts of truth in
mathematics), will present an overview on some of the deepest
features of the foundations of mathematics: their philosophical and
intuitive aspects (much of which may be implicitly understood but
not well explained by specialists, as such philosophical issues are
not easily seen as proper objects of scientific works). This
includes
 How, while independent of our time, the universe of
mathematics is still subject to a flow of its own time ;
 The deep meaning of the difference between sets and classes,
in relation to that time; thus, the deep reason for the use of bounded
quantifiers in set theory.
 The justification of the set
generation principle
These things are not necessary for Part 2 (Set Theory, continued)
except to explain the deep meaning and consequences of the fact that
the set exponentiation or power set (2.6) is not justifiable by the
set generation principle. But they will be developed and justified
in more details in Part 3 (Model Theory).
Intuitive representation and abstraction
Though mathematical systems «exist» independently of any particular
sensation, we need to represent them in some way (in words, formulas
or drawings). Diverse ways can be used, that may be equivalent
(giving the same results) but with diverse degrees of relevance
(efficiency) that may depend on purposes. Ideas usually first appear
as more or less visual intuitions, then are expressed as formulas
and literal sentences for careful checking, processing and
communication. To be freed from the limits of a specific form of
representation, the way is to develop other forms of representation,
and exercise to translate concepts between them. The mathematical
adventure itself is full of plays of conversions between forms of
representation.
Platonism vs Formalism
In this diversity of approaches to mathematics (or each theory), two
philosophical views are traditionally distinguished.
 The Platonic view (also called idealistic)
focuses on the worlds or systems to study, seen as preexisting
mathematical realities to be explored (or remembered, according
to Plato). This is the approach of intuition that smells the
global order of things before formalizing them.
 The formalistic view focuses on language, rigor
(syntactic rules) and dynamical aspects of a theory, starting
from its foundation (formal expression), and following the rules
of development.
Philosophers usually present them as opposite, incompatible belief
systems, candidate truths on the real nature of mathematics.
However, both views instead turn out to be necessary and
complementary aspects of math foundations. Let us explain how.
Of course, human thought having no infinite abilities, cannot
fully operate in any realistic way, but only in a way roughly
equivalent to formal reasonings developed from some foundations ;
this work of formalization can prevent the possible errors of
intuition.
But a purely formalistic view cannot hold either because
 The clarity and selfsufficiency of any possible foundation
(any starting position with formal development rules), remain
relative: any starting point had to be chosen more or less
arbitrarily, taken from and motivated by a larger perspective
over mathematical realities; it must be defined in some
intuitive, presumably meaningful way, implicitly admitting its
own foundation, since any try to specify the latter would lead
to a path of endless regression, whose realistic preexistence
would have to be admitted.
 Most of the time, works are only partially formalized: we use
semiformal proofs, with just enough rigor to give the feeling
that a full formalization is possible, yet not fully written; an
intuitive vision of a problem may seem clearer than a formal
argument.
Another reason for their reconciliation, is that they are not in any
global dispute to describe the whole of mathematics, but their
shares of relevance depends on specific theories under
consideration.
The form of mathematical theories
The main useful logical frameworks for mathematical theories,
from the weakest (less expressive) to the strongest (most
expressive), except set theory, will be:
 Algebraic theories;
 Firstorder logic
 Duality theories (that is a fuzzy range of theories with some
common features);
 Secondorder logic;
 Higherorder logic;
We described the general form of mathematical theories in sections
1.1,
1.3,
1.4,
1.5,
1.6,
1.8,
1.9 for the two
most important frameworks : firstorder logic, and the framework of set
theory (which is specific, with definiteness classes, and binders depending
on sets). The relation between both escapes the above hierarchical
order as we have irreversible correspondences between them in both
ways (not the inverse of each other):
 A natural inclusion of all firstorder theories into set
theory, viewing their possible models as objects in a common
model (universe) of set theory (1.3, 1.4). This is the usual
view of ordinary mathematics, studying many systems as "sets
with relations or operations such that...", with possible
connections between them.
 Another procedure (sections 1.9, 1.10, with a more restricted
interest to specialists of mathematical logic) converts set
theory into firstorder logic.
Let us sum up our description: once chosen a formalism, a theory is
specified by its content (vocabulary and axioms), as follows. Every
theory is made of 3 kinds of components. The latter 2 kinds of
components are finite systems made from the previous kind :
 A list of types, whose translations into set theory
are names of sets. For example, geometry can be seen
with 2 types: «points» and «lines».
 A list of structure symbols. These symbols aim to
designate structures, that is connections between objects with
specific types. They give their roles to the objects of each
type in connection with those of other types. In firstorder
theories, a structure is either
 An operation between a list of variables with
respectively specified types (which aim to specify the types
of their values), with values of also one specified type.
The number of arguments of an operation is called its arity.
 Constant are the nullary operations in this list (it has
no argument).
 A relation, that is an operation with value «true»
or «false».
Also, nary operations f may be seen as
particular (n+1)ary relations (y=f(x_{1},...,
x_{n})), those true for a unique value of y
for any values of x_{1},..., x_{n}.
 A list of axioms. Each axiom is a ground formula : a
system of occurrences of symbols among structure symbols,
equality (=), logical connectives (1.6) and quantifiers (∀and ∃,
1.9); these formulas are supposed to be true when these symbols
are interpreted in a given system.
But for having any interest for most practical purposes, a
theory should be such that we cannot build from this, any
of the 4th kind of components:
 A contradiction of a theory, is a system of formulas
based on its axioms, forming a proof of the formula 0 (False), as explained in 1.6.
Realistic vs. axiomatic theories in mathematics and other
sciences
Interpretations of the word «theory» may vary between mathematical
and nonmathematical uses (in ordinary language and other sciences),
in two ways.
Theories may differ by their object and nature:
 Pure mathematical theories, are mathematical theories
considered for the pure sake of mathematics, without any
nonmathematical intentions.
On the contrary, theories outside
mathematics, try to describe some real systems (fields of
observation, parts of the outside world, that are not purely
mathematical systems). They may be of 2 sorts:
 Applied mathematical theories are also mathematical
theories (i.e. expressed in rigorous ways) but the mathematical
systems they describe are conceived as idealizations of aspects
of given realworld systems (neglecting other aspects); insofar
as it is accurate, this idealization (reduction to mathematics)
also allows for correct deductions within accepted margins of
error.
 Nonmathematical theories describe qualitative
(nonmathematical) aspects of the world. For example, usual
descriptions of chemistry involve drastic approximations,
recollecting from observations some seemingly arbitrary effects
whose deduction from quantum physics is usually out of reach of
direct calculations.
Theories may also differ by whether Platonism or formalism best
describes their intended meaning :
A realistic theory aims to
describe a fixed system given from an independent reality,
so that any of its ground formulas (statements) will be either
definitely true or definitely false as determined by this system
(but the truth of a nonmathematical statement may be ambiguous,
i.e. illdefined for the given real system). From this intention,
the theory will be built by providing an initial list of
formulas called axioms : that is a hopefully true
description of the intended system as currently known or guessed.
Thus, the theory will be true if all its axioms are indeed true on
the intended system. In this case, its logical consequences
(theorems, deduced from axioms) will also be true on the intended
model.
This is usually well ensured in pure maths, but may be speculative
in other fields. In realistic theories outside pure mathematics,
the intended reality is usually a contingent one among alternative
possibilities, that (in applied mathematics) are equally possible
from a purely mathematical viewpoint. If a theory (axioms list)
does not fit a specific reality that pure mathematics cannot
suffice to identify, this can be hopefully discovered by comparing
its predictions (logical consequences) with observations : the
theory is called falsifiable.
An axiomatic theory is a theory given with an axioms
list that means to define the selection of its models
(systems it describes), as the class of all systems where these
axioms are true. This may keep an unlimited diversity of models,
that remain equally real and legitimate interpretations. By this
definition of what «model» means, the truth of the axioms of the
theory is automatic on each model (it holds by definition and is
thus not questionable). All theorems (deduced from axioms) are
also true in each model.
In pure mathematics, the usual features of both possible roles of
theories (realistic and axiomatic) automatically protect them from
the risk to be «false» as long as the formal rules are respected.
Nonrealistic theories outside pure mathematics (where the
requirement of truth of theorems is not always strict, so that the
concept of axiom loses precision) may either describe classes of
real systems, or be works of fiction describing imaginary or
possible future systems. But this distinction between real and
imaginary systems does not exist in pure mathematics, where all
possible systems are equally real. Thus, axiomatic theories of pure
mathematics aim to describe a mathematical reality that is existing
(if the theory is consistent) but generally not unique.
Different models may be nonequivalent, in the sense that
undecidable formulas may be true or false depending on the model.
Different consistent theories may «disagree» without conflict, by
being all true descriptions of different systems, that may equally
«exist» in a mathematical sense without any issue of «where they
are».
For example Euclidean geometry, in its role of first physical
theory, is but one in a landscape of diverse geometries that are
equally legitimate for mathematics, and the real physical space is
more accurately described by the nonEuclidean geometry of General
Relativity. Similarly, biology is relative to a huge number of
random choices silently accumulated by Nature on Earth during
billions of years.
Realistic and axiomatic theories both appear in pure mathematics, in
different parts of the foundations of mathematics, as will be
presented in the section on the truth concepts in
mathematics.
But let us first explain the presence of a purely mathematical flow
of time (independent of our time) in model theory and set theory.
Time in model theory
The time order between interpretations of expressions
Given a model, expressions do not receive their interpretations all
at once, but only the ones after the others, because these
interpretations depend on each other, thus must be calculated after
each other. This time order of interpretation between expressions,
follows the hierarchical order from subexpressions to expressions
containing
them.
Take for example, the formula xy+x=3. In order for it
to make sense, the variables x and y must take a
value first. Then, xy takes a value, obtained by multiplying
the values of x and y. Then, xy+x
takes a value based on the previous ones. Then, the whole formula
(xy+x=3) takes a Boolean value (true or false).
But this value depends on those of the free variables x and
y. Finally, taking for example the ground formula ∀x,
∃y, xy+x=3, its Boolean value (which is false
in the world of real numbers), «is calculated from» those taken by
the previous formula for all possible values of x and y,
and therefore comes after them.
A finite list of formulas in a theory may be interpreted by a single
big formula containing them all. This only requires to successively
integrate (or describe) all individual formulas from the list in the
big one, with no need to represent formulas as objects (values of a
variable). This big formula comes (is interpreted) after them all,
but still belongs to the same theory. But for only one formula to
describe the interpretation of an infinity of formulas (such as all
possible formulas, handled as values of a variable), would require
to switch to the framework of onemodel theory.
The metaphor of the usual time
I can speak of «what I told about at that time»: it has a sense if
that past saying had one, as I got that meaning and I remember it.
But mentioning «what I mean», would not itself inform on what it is,
as it might be anything, and becomes absurd in a phrase that
modifies or contradicts this meaning («the opposite of what I'm
saying»). Mentioning «what I will mention tomorrow», even if I knew
what I will say, would not suffice to already provide its meaning
either: in case I will mention «what I told about yesterday» (thus
now) it would make a vicious circle; but even if the form of my
future saying
ensured that its meaning will exist tomorrow, this would still not
provide it today. I might try to speculate on it, but the actual
meaning of future statements will only arise once actually expressed
in context. By lack of interest to describe phrases without their
meaning, we should rather restrict our study to past expressions,
while just "living" the present ones and ignoring future ones.
So, my current universe of the past that I can describe today,
includes the one of yesterday, but also my yesterday's comments
about it and their meaning. I can thus describe today things outside
the universe I could describe yesterday. Meanwhile I neither learned
to speak Martian nor acquired a new transcendental intelligence, but
the same language applies to a broader universe with new objects. As
these new objects are of the same kinds as the old ones, my universe
of today may look similar to that of yesterday; but from one
universe to another, the same expressions can take different
meanings.
Like historians, mathematical theories can only «at every given
time» describe a universe of past mathematical objects, while this
interpretation itself «happens» in a mathematical present outside
this universe.
Even if describing «the universe of all mathematical objects»
(model of set theory), means describing everything, this
«everything» that is described, is only at any time the current
universe, the one of our past ; our act of interpreting
expressions there, forms our present beyond this past. And then,
describing our previous act of description, means adding to this
previous description (this «everything» described) something else
beyond it.
As a onemodel
theory T' describes a theory T with a model M,
the components (notions and structures)
of the model [T,M] of T', actually fall into 3
categories:
 The components of T and its developments as a formal
system (abstract types, structure symbols, expressions, axioms,
proofs from axioms), that aim to describe the model but remain
outside it and independent of it.
 The components of M (interpretations of types and
structure symbols)
 The interpretation (attribution of values) of all expressions
of T in M, for any values of their free
variables.
This last part of [T,M] is a mathematical construction
determined by the combination of both systems T and M
but it is not directly contained in them : it is built after
them.
So, the model [T,M] of T', encompassing the
present theory T with the interpretation of all its formulas
in the present universe M of past objects, is the next universe
of the past, which will come as the infinity of all current
interpretations (in M) of formulas of T will become
past.
Or can it be otherwise ? Would it be possible for a theory T
to express or simulate the notion of its own formulas and
compute their values ?
As explained
in 1.7, some theories (such as model theory, and set theory
from which it can be developed) are actually able to describe
themselves: they can describe in each model a system looking like
a copy of the same theory, with a notion of "all its formulas"
(including objects that are copies of its own formulas). However
then, according to the Truth Undefinability
theorem, no single formula (invariant predicate) can ever
give the correct boolean values to all object copies of ground
formulas, in conformity with the values of these formulas in the
same model.
The Berry paradox
This famous paradox is the idea of "defining" a natural number n
as "the smallest number not definable in less than twenty words".
This would define in 10 words a number... not definable in less than
20 words. But this does not bring a contradiction in mathematics
because it is not a mathematical definition. By making it more
precise, we can form a simple proof of the truth undefinability
theorem (but not a fully rigorous one):
Let us assume a fixed choice of a theory T describing a set
ℕ of natural numbers as part of its model M.
Let H be the set of formulas of T with one free
variable intended to range over this ℕ, and shorter than (for example)
1000 occurrences of symbols (taken from the finite list of symbols
of T, logical symbols and variables).
Consider the formula of T' with one free variable n
ranging over ℕ, expressed as
∀F∈H, F(n) ⇒
(∃k<n, F(k))
This formula cannot be false on more than one number per formula in
H, which are only finitely many (an explicit bound of their number
can be found). Thus it must be true on some numbers.
If it was equivalent to some formula B∈H, we would get
∀n∈ℕ, B(n) ⇔ (∀F∈H,
F(n) ⇒ (∃k<n, F(k)))
⇒ (∃k<n, B(k))
contradicting the existence of a smallest n on which B is true.
The number 1000 was picked in case translating this formula into
T was complicated, ending up in a big formula B, but still in
H. If it was so complicated that 1000 symbols didn't suffice, we could
try this reasoning starting from a higher number. Since the existence of an
equivalent formula in H would anyway lead to a contradiction,
no number we might pick can ever suffice to find one. This shows the
impossibility to translate such formulas of T' into equivalent formulas of
T, by any method much more efficient than the kind of mere
enumeration suggested above.
This infinite time between theories, will develop as an endless
hierarchy of infinities.
Achilles runs after a turtle; whenever he crosses the distance to
it, the turtle takes a new length ahead.
Seen from a height, a vehicle gone on a horizontal road approaches
the horizon.
Particles are sent in accelerators closer and closer to the speed of
light.
Can they reach their ends ?
Each example can be seen in two ways:
 the «closed» view, sees a reachable end;
 the «open» view ignores this end, but only sees the movement
towards it, never reaching it.
And in each example, a physical measure of the «cost» to
approach and eventually reach the targeted end, decides its «true»
interpretation, according to whether this cost would be finite or
infinite, which may differ from the first guess of a naive
observer.
But the world of mathematics, free from all physical costs and
where objects only play conventional roles, can accept both
interpretations.
Each generic theory is «closed», as it can see its model (the ranges
of its variables) as a whole (that is a set in its set theoretical
formulation): by its use of binders over types (or classes), it
«reaches the end» of its model, and thus sees it as «closed». But
any possible framework for it (onemodel theory and/or set theory)
escapes this whole.
As explained in 1.7, set theory has multiple possible models : from
the study of a given universe of sets, we can switch to that of a
larger one with more sets (that we called metasets), and new
functions between the new sets.
As this can be repeated endlessly, we need an «open» theory
integrating each universe described by a theory, as a part (past) of
a later universe, forming an endless sequence of growing realities,
with no view of any definite totality. This role of an open theory
will be played by set theory itself, with the way its expressions only bind
variables on sets (1.8).
Time in set theory
The expansion of the set theoretical universe
Given two universes U⊂U', the universe U will
be called standard in U', or a subuniverse of U',
if its interpretation of set theoretical structures (values they give for all values
of arguments inside U) coincides with their metainterpretation (that of
U'). Precisely, let us require the preservation of the following data:
 The content of every set (every set coincides with the metaset of the
same elements): not only ∈ is preserved, but every set in U is
interpreted by U' as included in U (this is not a direct
consequence: if not requiring the subuniverse to be a set nor a class,
a counterexample would be given by internal
set theory).
 The function evaluator and the domain functor (1.4)
 The function definer and the set builder (1.8, translated as
infinite lists of operator symbols in firstorder logic in 1.10
and 1.11);
 The power set (introduced in 2.5).
 Thus also, any other structure defined from the above by
expressions and bounded formulas, such as finiteness (definable
from the power set): part 3 will show the existence of nonstandard
universes with a different interpretation of finiteness, thus
having as «set of integers» a nonstandard
model of arithmetic.
Thus, as structures in U' are fixed, U only needs to be
specified as a metasubset or class in U'. Let us call it a small
subuniverse if it is more precisely a set (U∈U').
If we have 3 universes U ⊂ U' ⊂ U"
where U' is standard in U", then we
have the equivalence:
(U is standard in U') ⇔ (U
is standard in U").
Thus the idea to consider the standardness of a universe as an
absolute property, independent of the external universe in which it
is described... provided that this external universe is itself standard.
This does not formally define standardness as an absolute concept
(which is impossible), but suggests that such a concept
may make ideal sense.
Let us call standard multiverse any collection (range) of
standard universes, where any 2 of them are small subuniverses
of a third one. Let us say that the set theoretical universe
expands when it ranges over a standard multiverse.
From any standard multiverse M, we can rebuild an
external universe containing all its universes, defined as their union
U=⋃M, where they are all standard. Indeed, any
expression with free variables in U takes its meaning from at
least one U∈M containing the values of all these
variables, and thus where the expression can be interpreted. This
U is still another specific standard universe, but it cannot
belong itself to M, as its presence there would contradict the
concept of multiverse which does not admit any biggest element. So,
no single standard multiverse can ever contain all possible standard
universes.
We can understand the intended sense of set theory as of a different
kind than that of generic theories, in this way :
 Interpretations of a generic theory require to fix a model, in
which its variables and expressions may take values;
 Set theory aims to locally give to its expressions with fixed values
of the free variables, their standard interpretation, independently of
a standard universe containing them, which may keep expanding.
Unlike standard universes, not all nonstandard universes can be small
subuniverses of some larger universe (itself nonstandard),
as extensions may be unable to preserve the power set operators.
We may also have a multiverse of nonstandard universes looking like
a standard multiverse (its members are small subuniverses of each
other), but whose union U (with the same structures, letting
these universes appear standard), no more behaves as
a good universe, as it no more satisfies the axiom
schema of specification over formulas with open
quantifiers (which is a necessary quality for a universe to be a small
subuniverse of another one).
Namely, there may be a set E∈U
and a formula A such that {x∈E∀_{U} y,
A(x,y)}∉U.
Two universes will be called compatible if they can both
be seen as subuniverses of a common larger universe. All
standard universes are compatible with each other. So when 2
universes are incompatible, at least one of them is nonstandard ;
they may be both parts of a common larger universe, only by
representing there at least one of them as nonstandard.
Can a set contain itself ?
Let us call a set reflexive if it contains itself.
By the proof
of Russell's paradox [1.8], the class (Set(x) ∧ x
∉ x) of nonreflexive sets, cannot coincide with a subset F
of any set E, since this F would then be a nonreflexive set
outside E, giving a contradiction. But can
reflexive sets exist ? this is undecidable; here is why.
From a universe containing reflexive sets, we can just remove them all:
these sets cannot be rebuilt from the data of their elements
(since each one has at least an element removed from the universe,
namely itself), but for the rest to still constitute a universe
(model of set theory), we need to manage the case of all other sets
that contained one (and similarly with functions):
 Either reduce them to pure elements
 Or eliminate them too (and so on for other sets that contained
the latter).
Another way is to progressively rebuild the universe while avoiding them:
each set appears at some time, formed as a collection of previously
accepted or formed objects. Any set formed this way, must have had
a first coming time: it could not be available yet when it first
came as a collection of already available objects, thus it cannot be reflexive.
As the reflexivity of a set is independent of context, a union of
universes each devoid of reflexive sets, cannot contain one either.
On the other hand, universes with reflexive sets can be created as
follows:
Riddle. What is the difference between
 a universe with a pure element x and a set y
such that x ∈ y ∧ y ∉ y,
 and a universe with a set x and a pure element y
such that x ∈ x ∧ y ∉ x ?
Answer: the role of the set containing x but not y,
played by y in the former universe, is played by x
in the latter.
The absence of reflexive sets, is a special case of the axiom of
foundation (or regularity), to which the above arguments of
undecidability, will naturally extend. Its formulation will be based
on the concept of well founded relation, that will follow the
detailed study of Galois connections. But this axiom is just as
useless as the sets it excludes.
When the universe expands, the values of statements (firstorder
formulas, admitting open quantifiers) may change.
Of course, if a statement is formally provable from given axioms
then it remains true in all universes satisfying these axioms;
similarly if it is refutable (i.e. its negation is provable, so
that it is false in all universes). But set theory does not give sense
(a Boolean value) to undecidable ground
statements, and similar nonground statements (with open quantifiers
and given values of free variables), as any given value would be relative
to how things go «here and now» : if a universal statement (∀x,
A(x) for a bounded formula A) is true «here», it
might still become false (an x where A is false might be
found) «elsewhere».
But if the value of an indefinite statement is relative to how things go
«here», then the actual variability of this value between places (to
motivate its indefiniteness status) remains relative to how things turn
out to go «elsewhere». Namely, it is relative to a given range of
possible coexisting «places» (universes) where the statement may
be interpreted, that is a multiverse. But to coexist, these universes
need the framework of a common larger universe U containing
them all. In fact, the mere data of U suffices to essentially
define a multiverse as that of «all universes contained in U».
Or rather, 2 multiverses,
depending on whether we admit all universes it contains, or only the
standard ones.
A standard multiverse, as defined above. There, the
variability of an existential statement (∃x, A(x))
for a bounded formula A, means the existence of universes
U, U' ⊂U such that ∀x∈U,
¬A(x) but ∃x∈U', A(x).
That is, A(x) only holds at some x outside
U. We can get a U' such that U∈U'
by taking any universe containing both U and the old U'.
In particular, (∃x, A(x)) is also true in U
(we may call this statement «ultimately true»). Intuitively, the
x where A is true are out of reach of the theory : they
cannot be formally expressed by terms, and their existence cannot be
deduced from the given existence axioms (satisfied by U).
But since (∃x, A(x)) was not definitely true
for the initially considered universe U actually unknown and
expanding, its chances may be poor to become definitely true for U
which is just another axiomatically described universe, that is
unknown as well. So, when a statement aimed for U is indefinite, it
may be varying when U expands, but it may also be that the
very question whether it indeed varies (that can be translated as a
question on U), remains itself an indefinite question as
well. Just more truths can be determined for U than for U
by giving more axioms to describe U than we gave for U.
The incompleteness
theorem will imply that a formalization of this description of U
(as the union of a standard multiverse, whose universes satisfy given axioms)
is already such a stronger axiomatization, but also that neither this nor any
other axiomatic theory trying to describe U (as some kind of
ultimate standard universe), can ever decide (prove or refute) all ground
statements in U; in particular, the question of the variability of a ground
statement in the expanding U cannot be always decided either.
A multiverse of «all universes» no matter if they are
standard or not. The completeness
theorem will show that for any generic theory, the interpretation
of the indefiniteness of a ground formula as variability of its boolean
value in this multiverse, coincides with their formal
undecidability. Strange things may happen there for an undecidable
(∃x,A(x)), as the universes where it is true
and those where it is false may be incompatible :
 A universe U where it is true might not contain any of those
where it is false as a subuniverse : {x∈U
¬A(x)} may not have any metasubset behaving as a
good universe;
 A universe where it is false might not be a small subuniverse
of any another one where it is true.
 It might be only true in nonstandard universes.
Intuitively, different possible universes with different properties
do not necessarily "follow each other" in time, but can belong to
separate and incompatible growth paths, some of which may
be considered more realistic than others.
So, while the formal undecidability of a ground statement makes
it automatically variable in any "multiverse of all universes", this still
does not say how it goes for standard multiverses. In conclusion,
the indefiniteness of statements should only be treated by avoidance,
as a mere expression of ignorance towards the range of acceptable
universes, partially selected by axioms, where they may be interpreted.
Interpretation of classes
Classes in an expanding universe
Unlike objects which can be compared by an equality symbol (that can be
used in formulas), the metarelation of equality between classes is as
indefinite as the open ∀ since both concepts are definable from each other:
 The equality of classes A and B would be
defined by ∀x, A(x) ⇔ B(x);
 The statement (∀x, A(x))
means A = 1 (the universe, class of all objects).
Like with open quantifiers, this indefiniteness leaves us with both concepts
of provable equality (or proven equality), and provable inequality,
according to whether the statement of this equality (∀x,
A(x) ⇔ B(x)) is provable or refutable.
Each universe U interprets each class C as a metaset of
objects P={x∈U C(x)}, and sees it
as a set when P ∈ U. This condition, that C has
the same elements in U as an object (set) P also in
U, is expressed by set theory in U as
∃P,∀x, C(x) ⇔ x ∈ P
or equivalently∃E,∀x, C(x)
⇒ x ∈ E
since from such an E we can restore
P as P={x∈E C(x)}.
Otherwise (if P ∉ U), this P is
arising to existence with U and will exist as a set in
future universes (those which see U as a set).
From the perspective of an expanding universe, a class
C (given as a formula with parameters), «is a set» (equal to P) if the
part P = {x∈U C(x)} that this formula
defines in each U (formally depending on U),
turns out to remain constant (the same set) during the expansion of U.
More precisely, it is known as a set
(proven equal to P) if we could prove this independence,
i.e. refute the possibility for any object x outside the current universe
(but existing in a larger universe),
to ever satisfy C(x). On the other hand, a class C is
not considered a set, if it remains eventually able to contain «unknown»
or «not yet existing» objects (in another universe), that would belong to some
future value of P, making P vary during the growth of U.
In a given expansion of U, the interpretation of the formal condition
for C to be a set (∃E,∀x, C(x) ⇒ x
∈ E) in the union U of these U,
means that in this growth, «there is a time after which P will
stay constant». Compared to our last criterion to distinguish sets among
classes in an expanding universe (the constancy of P), this one ignores any past
variations, to focus on the latest ones (those between the largest universes,
with size approaching that of the U where it is interpreted).
But the ideally intended standard multiverse, that is the range of U,
would have to be itself a class instead of a set. Thus, both perspectives
(a constant vs. a variable universe) alternatively encompass each other,
endlessly along the expansion. Meanwhile, a
class defined by some special formula may alternatively gain and
lose the status of set ; but if in some growth range,
«P perpetually alternates between variability and constancy», then it
would ultimately not be constant there, thus C would not be
a set. So the alternation of its status would end... if we stopped checking
it at wrong places. But how ?
Concrete examples
A set: Is there any dodo left on Mauritius ? As this
island is well known and regularly visited since their supposed
disappearance, no surviving dodos could still have gone unnoticed,
wherever they may hide. Having not found any, we can conclude
there are none. This question, expressed by a bounded quantifier,
has an effective sense and an observable answer.
A set resembling a class: Bertrand Russell raised this
argument about theology: «If I were to suggest that between
the Earth and Mars there is a china teapot revolving about the
sun..., nobody would be able to disprove my assertion [as] the
teapot is too small to be revealed even by our most powerful
telescopes. But if I were to go on to say that, since my assertion
cannot be disproved, it is intolerable presumption on the part of
human reason to doubt it, I should rightly be thought to be
talking nonsense.» The question is clear, but on a too large space,
making the answer practically inaccessible. (An 8m telescope has
a resolution power of 0.1 arcsec, that is 200m on the moon surface)
A class: the extended statement, «there is a teapot orbiting
some star in the universe» loses all meaning: not only the size of
the universe is unknown, but Relativity theory
sees the remote events from which we did not receive light yet, as
not having really happened for us yet either.
A metaobject: how could God «exist», if He is a
metaobject, while «existence» can only qualify
objects? Did apologists properly conceive their own thesis
on God's «existence» ? But what are the objects
of their faith and their worship ? Each monotheism rightly
accuses each other of only worshiping objects (sin of idolatry):
books, stories, beliefs, teachings, ideas, attitudes, feelings,
places, events, miracles, healings, errors, sufferings, diseases,
accidents, natural disasters (declared God's Will), hardly more
subtle than old statues, not seriously checking (by fear of God)
any hints of their supposed divinity.
A universal event: the redemptive sacrifice of the Son of
God. Whether it would have been theologically equivalent for it to
have taken place not on Earth but in another galaxy or in God's
plans for the Earth in year 3,456, remains unclear.
Another set reduced to a class... The class F of
girls remains incompletely represented by sets: the set of those
present at that place and day, those using this dating site and
whose parameters meet such and such criteria, etc. Consider the
predicates B of beauty in my taste, and C of
suitability of a relationship with me. When I try to explain that
«I can hardly find any pretty girl in my taste (and they are often
unavailable anyway)», i.e.
(∀_{F} x, C(x)
⇒ B(x)) ∧ {x∈ F  B(x)}≈Ø,
the common reaction is: «Do you think that beauty is the only thing
that matters ?», i.e.
What,(∀x ∈ F, C(x)
⇔ B(x)) ????
then «If you find a pretty girl but stupid or with bad character,
what will you do ?». Formally : (∃x ∈ F, B(x)
⇏ C(x) !!!). And to conclude with a claim of pure
goodness: «I am sure you will find !», ( « ∃ ∃ x ∈ F,
C(x)). Not forgetting the necessary
condition to achieve this: «You must change your way of thinking».
... by the absence of God...: F would have immediately
turned into a set by the existence of anybody on Earth able to
receive a message from God, as He would obviously have used this
chance to make him email me the address my future wife (or the other
way round).
... and of any substitute: a free, open and efficient online
dating system, as would be included in my project trustforum.net, could give the
same result. But this requires finding programmers willing to
implement it. But the class of programmers is not a set either,
especially as the purpose of the project would conflict with the
religious moral priority of saving God's job from competitors
so as to preserve His salary of praise.
Let Q* be the abbreviation as a quantifier symbol,
of a bounded formula that uses an extra unary predicate symbol.
Assume that ¬(Q*y,0), and let C(x)
defined as (Q*y, y = x).
The hypothesis of the set generation principle means that
we have a proof of (Q* ⇔ ∃_{C}).
Let E be the range of all values ever taken by the
argument y of R(y) when interpreting
Q*y, R(y). This range may depend
on implicit parameters of Q*y but does not
depend on R. It must be a set because this formula
only has definite, fixed means (variables bound to given sets,
fixed parameters) to provide these values. We may also take
as E another set that includes this range, such as any fixed
universe (seen as a set in a larger universe) containing the values
of all parameters, so that the formula can be interpreted there.
For any x, the value C(x)
of Q* on the predicate (y ↦ (y = x)),
can only differ (be true) from its (false) value on (y ↦ 0),
if both predicates differ inside E, i.e. if x
belongs to E : C(x) ⇔
((Q*y, y = x) ⇎ (Q*y,0))
⇒ (∃y∈E, y=x ⇎ 0) ⇔ x
∈ E
thus C is a set. ∎
For classes satisfying the condition of the set generation principle
(being indirectly as usable as sets in the role of domains of
quantifiers), are they also indirectly as usable as sets in the role
of domains of functions (before using this principle) ? Namely, is
there for each such class a fixed formalization (bounded formulas
with limited complexity) playing the roles of definers and
evaluators for functions having these classes as domains ? The
answer would be yes, but we shall not develop the justifications here.
Concepts of truth in mathematics
Let us review 4 distinct concepts of «truth» for a mathematical
formula, from the simplest to the most subtle.
We first saw the relative truth, that is the value of a
formula interpreted in a supposedly given model (like an implicit
free variable, ignoring any difficulty to specify any example). In
this sense, a given formula may be as well true or false depending
on the model, and on the values of its free variables there.
Provability
Then comes the quality of being relatively true in all models of a given
axiomatic theory, which coincides with provability in this theory,
i.e. deduction from its axioms by the rules of firstorder logic. Namely,
there are known formal systems of proof for firstorder
logic, with known proof verification algorithms, universally applicable to
any firstorder theory while keeping this quality (ability to prove exactly
all universally true formulas).
This remarkable property of firstorder logic, together with the
fact that all mathematics is expressible there (what is not
directly there can be made so by insertion into set theory, itself
formalized as a firstorder theory), gives this framework a
central importance in the foundations of mathematics : it
reconciles Platonism and formalism, while giving a clear, natural
sense to the concepts of «proof», «theorem» and «consistency».
Different systems can do this job but all such formalisms, when
correct, are equivalent to each other : any proof according to one is
automatically convertible into a proof according to any other.
The completeness
theorem ensuring this, first expressed as stating the
existence of a model of any consistent firstorder theory, will be
proven by constructing these models out of the infinite set of all
ground expressions in a language constructed from the theory
(the language of the theory plus more symbols extracted from its
axioms). As the set of all ground expressions in a language can
itself be constructed from this language together with the set ℕ
of natural numbers, the validity of this theorem only depends on the
axiom of infinity, that is the existence of ℕ as an actual infinity,
sufficient for all theories (ignoring the diversity of infinities in set
theory).
However, these are only theoretical properties, assuming a
computer with unlimited (potentially infinite) available time and
resources, able to find proofs of any size. Not only the precise size of
a proof may depend on the particular formalism, but even some
relatively simple formulas may only have «existing» proofs that «cannot be
found» in practice as they would be too long, even bigger than the number of atoms
in the visible physical Universe (as illustrated by Gödel's
speedup theorem).
Within limited resources, there may be no way to distinguish whether a
formula is truly unprovable or a proof has only not yet been found.
To include their case, the universal concept of provability (existence of a proof)
has to be defined in the abstract. Namely, it can be expressed as a formula of firstorder arithmetic
(the firstorder theory of natural numbers with operations of
addition and multiplication), made of one existential quantifier
that is unbounded in the sense of arithmetic (∃_{ℕ} p,
) followed by a formula where all quantifiers are bounded, i.e. with
finite range (∀x < (...), ...). For example, p may
be an encoding of the proof, or the time needed by a proof searching
algorithm to find it.
However, once given an arithmetical formula known to be a correct
expression of the provability predicate (while all such formulas are
provably equivalent to each other), it still needs to be interpreted.
Arithmetic truths
This involves the third concept of mathematical
truth, that is the realistic
truth in firstorder arithmetic. This is the ideally meant
interpretation of arithmetic: the interpretation of ground formulas
of firstorder arithmetic in «the true set ℕ of all, and only all,
really finite natural numbers», called the standard model of
arithmetic. But any axiomatic formalization of arithmetic in
firstorder logic is incomplete, in both following senses of the question:
 Due to the incompleteness
theorem, the set of all real truths of arithmetic (formulas
true in ℕ) cannot be exhaustively produced by any algorithm (using
unlimited resources but a finite amount of initial information). Thus,
they cannot be all logical consequences of any algorithmically produced
axiomatic theory either (since logical deduction from given axioms is
algorithmic).
 Even when abstractly considering to take all real truths as axioms,
it still would not suffice to determine the model, as it cannot exclude
nonstandard
models. (This last form of incompleteness does not have any
name because it equally affects the firstorder description of any
infinite system, according to the LöwenheimSkolem
theorem, and is thus unremarkable.)
This incompleteness affects the provability predicate itself, though
only on one side, as follows.
On the one hand, if the formula p(A) of provability
of a formula A, is true, then it is provable: a proof of p(A)
can in principle be produced by the following method in 2
steps:
 Find a proof of A (as it is assumed to exist);
 Process it by some automatic converter able to formally
convert any proof of A into a proof that a proof of A
exists.
On the other hand, it is not always refutable when false : no matter
the time spent seeking in vain a proof of a given unprovable formula,
we might still never be able to formally refute the possibility to
finally find a proof by searching longer, because of the risk for a formula
to be only provable by unreasonably long proofs.
In lack of any possible fixed ultimate algorithm to produce all truths of
arithmetic, we can be interested with partial solutions: algorithms
producing endless lists of ground arithmetic formulas with both qualities
 Infallible (stays included in the set of truths, describing
the standard model of arithmetic);
 Large (compared by inclusion with other algorithmically
producible sets of truths).
A natural method to progress in the endless (nonalgorithmic) search
for better and better algorithms for the second quality without breaking
the first, consists in developing formalizations of set theory describing
larger and larger universes beyond the infinity of ℕ, where properties
of ℕ can be deduced as particular cases. Indeed, if a set theory T'
requires its universe to contain, as a set, a model U of a
set theory T, then the arithmetic formula of the consistency
of T will be provable in T' but not in T,
while all arithmetic theorems of T remain provable in T'
if T' describes U as standard.
Set theoretical truths
The above can be read as an indispensability argument for our last
concept of truth, which is the truth of set theoretical statements.
To progress beyond logical deduction from already accepted ones, more
set theoretical axioms need to be introduced, motivated by some
Platonist arguments for a real existence of some standard universes where they
are true; the validity of such arguments needs to be assessed in intuitive,
not purely formal ways, precisely in order to do better than any predefined
algorithm. Arguments for a given axiomatic set theory, lead to
arithmetic conclusions :
 The formal consistency of this set theory;
 The arithmetic theorems in its framework
Both conclusions should not be confused :
 1. cannot come as a direct particular case of 2. (unless it is
wrong) even though it must be true for 2. to be consistent and thus
of any interest;
 the reason for the truth of 2. refers to the existence of a
standard model of this theory, while 1. only means that
nonstandard models exist.
But as the objects of these conclusions are mere properties of finite systems
(proofs), their meaning stays unaffected by any ontological assumptions
about infinities, including the finitist ontology (denying the reality of any
actual infinity, whatever such a philosophy might mean). It sounds hard to
figure out, then, how their reliability can be meaningfully challenged by
philosophical disputes on the «reality» of abstractions beyond them
(universes), just because they were motivated by these abstractions.
But then, the claim of consistency (1.), with the mere
existence of ℕ, suffice to let models of this theory really
exist (nonstandard ones, but working the same as standard ones).
For logical deduction from set theoretical axioms to be a good arithmetic truth
searching algorithm, these axioms must be :
 Sane = keeps accepting some standard universes (to keep the
output infallible);
 Strong = rejects "small" standard universes = sets a high
minimum "size" on the hierarchy of its subuniverses
(to make the output large).
But for a collection of such axioms to keep these qualities when put
together in a common theory, they need to be compatible,
in the sense that their conjunction remains sane. Two such statements
might be incompatible, either if one of them limits the size of the
universe (thus it shouldn't), or if each statement (using both kinds of open
quantifiers when written in prenex
form) endlessly alternates between truth and falsity when the
universe expands, in such a way that they would no more be true together in any
standard universe beyond a certain size (their conjunction must not
limit the size of the universe either). The question is, on what sort of big standard
universes might good axioms more naturally be true together ?
A standard universe U' might be axiomatically described
as very big by setting it a little bigger than another very big
one U, but the size of this U would need a
different description (as it cannot be proven to satisfy the same
axioms as U' without contradiction), but of what kind ?
Describing U as also a little
bigger than a third universe and so on, would require the axioms to keep
track of successive differences. This would rapidly run into inefficient
complications with incompatible alternatives, with no precise reason to
prefer one version against others.
The natural solution, both for philosophical elegance and the efficiency
and compatibility of axioms, is to focus on the opposite case, of universes
described as big by how much bigger they are than any smaller one (like how
we conceived
a ultimate universe as the union of a standard multiverse) :
axioms must be
 Open
= describing universes where eternity is a very long time
especially towards the end (= open universes).
It is also convenient because such descriptions are indeed
expressible by axioms interpreted inside the universe, with no
need of any external object. Indeed, if a property was only
expressible using an external object (regarding this universe as a
set), we could replace it by describing instead our universe as
containing a subuniverse of this kind (without limiting its size
beyond it), and why not also endlessly many subuniverses of this
kind, forming a standard multiverse: stating that every object is
contained in such a subuniverse. This is axiomatically expressible
using objects outside each of these subuniverses, but inside our
big one; and such axioms will fit all 3 above qualities.
Finally, the properly understood meaning of set theory is neither
axiomatic nor realistic, but a sort of fuzzy intermediate between
both: its axioms aim to approach all 3 qualities (strong and open but still
sane) selecting universes with the corresponding 3 qualities
(big and open but still standard), but these qualities are all fuzzy to interpret,
and any specific axioms list (resp. universe) only aims to approach them,
while this quest can never end.
Fortunately, rather simple theories such as ZF, already satisfy these
qualities up to a very high degree, describing much larger realities than
usually needed. This is how a Platonic view of set theory (seeing the
universe of all mathematical objects as a fixed, exhaustive reality) can
work as a good approximation, though it cannot be an exact, absolute fact.
Alternative logical frameworks
The description we made of the foundations of mathematics
(firstorder logic and set theory), is essentially just an
equivalent clarified expression of the widely accepted ones (a
different introduction to the same mathematics). In section 3 will
be presented other logical frameworks that are either restricted
versions of firstorder logic, or anyway naturally expressible in
set theory. But other, more radically different frameworks
(concepts of logic and/or sets), called nonclassical
logic, might be considered. Examples:
 Some logicians developed the «intuitionistic logic», which
lets formulas keep a possible indefiniteness as we mentioned for
open quantifiers, but treated as a modification of the pure
Boolean logic (the rejection of the excluded middle, where ¬(¬A)
does not imply A), without any special mention of
quantifiers as the source of this uncertainty. Or it might be
seen as a formal confusion between truth and provability. In
this framework, {0}∪ ]0,1] ⊂ [0,1], without equality. I could
not personally find any interest in this formalism but only
heard that theoretical computer scientists found it useful.
 When studying measure
theory (which mathematically defines probabilities in
infinite sets), I was inspired to interpret its results as
simpler statements on another concept of set, with the following
intuitive property. Let x be a variable randomly
taken in [0,1], by successively flipping a coin for each of its
(infinity of) binary digits. Let E be the domain of x,
set of all random numbers in [0,1]. It is nonempty
because such random numbers can be produced. Now another
similarly random number, with the same range (y ∈ E)
but produced independently of x, does not have any
chance to be equal to x. Thus, ∀x ∈ E,∀y
∈ E, x ≠ y. This way, x ∈ E
is no more always equivalent to ∃y ∈ E, x
= y.
We will keep classical logic in all following sections, ignoring
such alternatives.
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