Combinatory logic is a notation to eliminate the need for quantified variables in mathematical logic. It was introduced by Moses Schönfinkel and Haskell Curry, and has more recently been used in computer science as a theoretical model of computation and also as a basis for the design of functional programming languages. It is based on combinators which were introduced by Schönfinkel in 1920 with the idea of providing an analogous way to build up functions—and to remove any mention of variables—particularly in predicate logic. A combinator is a higher-order function that uses only function application and earlier defined combinators to define a result from its arguments.

In mathematics

Combinatory logic was originally intended as a 'pre-logic' that would clarify the role of quantified variables in logic, essentially by eliminating them. Another way of eliminating quantified variables is Quine's predicate functor logic. While the expressive power of combinatory logic typically exceeds that of first-order logic, the expressive power of predicate functor logic is identical to that of first order logic (Quine 1960, 1966, 1976). The original inventor of combinatory logic, Moses Schönfinkel, published nothing on combinatory logic after his original 1924 paper. Haskell Curry rediscovered the combinators while working as an instructor at Princeton University in late 1927. In the late 1930s, Alonzo Church and his students at Princeton invented a rival formalism for functional abstraction, the lambda calculus, which proved more popular than combinatory logic. The upshot of these historical contingencies was that until theoretical computer science began taking an interest in combinatory logic in the 1960s and 1970s, nearly all work on the subject was by Haskell Curry and his students, or by Robert Feys in Belgium. Curry and Feys (1958), and Curry ''et al.'' (1972) survey the early history of combinatory logic. For a more modern treatment of combinatory logic and the lambda calculus together, see the book by Barendregt, which reviews the models Dana Scott devised for combinatory logic in the 1960s and 1970s.

In computing

In computer science, combinatory logic is used as a simplified model of computation, used in computability theory and proof theory. Despite its simplicity, combinatory logic captures many essential features of computation. Combinatory logic can be viewed as a variant of the lambda calculus, in which lambda expressions (representing functional abstraction) are replaced by a limited set of ''combinators'', primitive functions without free variables. It is easy to transform lambda expressions into combinator expressions, and combinator reduction is much simpler than lambda reduction. Hence combinatory logic has been used to model some non-strict functional programming languages and hardware. The purest form of this view is the programming language Unlambda, whose sole primitives are the S and K combinators augmented with character input/output. Although not a practical programming language, Unlambda is of some theoretical interest. Combinatory logic can be given a variety of interpretations. Many early papers by Curry showed how to translate axiom sets for conventional logic into combinatory logic equations (Hindley and Meredith 1990). Dana Scott in the 1960s and 1970s showed how to marry model theory and combinatory logic.

** Summary of lambda calculus **

Lambda calculus is concerned with objects called ''lambda-terms'', which can be represented by
the following three forms of strings:
*
*
*
where is a variable name drawn from a predefined infinite set of
variable names, and and are lambda-terms.
Terms of the form are called ''abstractions''. The variable ''v'' is
called the formal parameter of the abstraction, and is the ''body''
of the abstraction. The term represents the function which, applied
to an argument, binds the formal parameter ''v'' to the argument and then
computes the resulting value of — that is, it returns , with
every occurrence of ''v'' replaced by the argument.
Terms of the form are called ''applications''. Applications model
function invocation or execution: the function represented by is to be
invoked, with as its argument, and the result is computed. If
(sometimes called the ''applicand'') is an abstraction, the term may be
''reduced'': , the argument, may be substituted into the body of
in place of the formal parameter of , and the result is a new lambda
term which is ''equivalent'' to the old one. If a lambda term contains no
subterms of the form then it cannot be reduced, and is said to
be in normal form.
The expression represents the result of taking the term and replacing all free occurrences of in it with . Thus we write
:
By convention, we take as shorthand for (i.e., application is left associative).
The motivation for this definition of reduction is that it captures
the essential behavior of all mathematical functions. For example,
consider the function that computes the square of a number. We might
write
:The square of ''x'' is
(Using "" to indicate multiplication.) ''x'' here is the formal parameter of the function. To evaluate the square for a particular
argument, say 3, we insert it into the definition in place of the
formal parameter:
:The square of 3 is
To evaluate the resulting expression , we would have to resort to
our knowledge of multiplication and the number 3. Since any
computation is simply a composition of the evaluation of suitable
functions on suitable primitive arguments, this simple substitution
principle suffices to capture the essential mechanism of computation.
Moreover, in lambda calculus, notions such as '3' and '' can be
represented without any need for externally defined primitive
operators or constants. It is possible to identify terms in lambda calculus, which, when suitably interpreted, behave like the
number 3 and like the multiplication operator, q.v. Church encoding.
Lambda calculus is known to be computationally equivalent in power to
many other plausible models for computation (including Turing machines); that is, any calculation that can be accomplished in any
of these other models can be expressed in lambda calculus, and
vice versa. According to the Church-Turing thesis, both models
can express any possible computation.
It is perhaps surprising that lambda-calculus can represent any
conceivable computation using only the simple notions of function
abstraction and application based on simple textual substitution of
terms for variables. But even more remarkable is that abstraction is
not even required. ''Combinatory logic'' is a model of computation
equivalent to lambda calculus, but without abstraction. The advantage
of this is that evaluating expressions in lambda calculus is quite complicated
because the semantics of substitution must be specified with great care to
avoid variable capture problems. In contrast, evaluating expressions in
combinatory logic is much simpler, because there is no notion of substitution.

** Combinatory calculi **

Since abstraction is the only way to manufacture functions in the
lambda calculus, something must replace it in the combinatory
calculus. Instead of abstraction, combinatory calculus provides a
limited set of primitive functions out of which other functions may be
built.

** Combinatory terms **

A combinatory term has one of the following forms:
The primitive functions are ''combinators'', or functions that, when seen as lambda terms, contain no free variables.
To shorten the notations, a general convention is that , or even , denotes the term . This is the same general convention (left-associativity) as for multiple application in lambda calculus.

** Reduction in combinatory logic **

In combinatory logic, each primitive combinator comes with a reduction rule of the form
:
where ''E'' is a term mentioning only variables from the set . It is in this way that primitive combinators behave as functions.

** Examples of combinators **

The simplest example of a combinator is I, the identity
combinator, defined by
:(I ''x'') = ''x''
for all terms ''x''. Another simple combinator is K, which
manufactures constant functions: (K ''x'') is the function which,
for any argument, returns ''x'', so we say
:((K ''x'') ''y'') = ''x''
for all terms ''x'' and ''y''. Or, following the convention for
multiple application,
:(K ''x'' ''y'') = ''x''
A third combinator is S, which is a generalized version of
application:
:(S ''x y z'') = (''x z'' (''y z''))
S applies ''x'' to ''y'' after first substituting ''z'' into
each of them. Or put another way, ''x'' is applied to ''y'' inside the
environment ''z''.
Given S and K, I itself is unnecessary, since it can
be built from the other two:
:((S K K) ''x'')
:: = (S K K ''x'')
:: = (K ''x'' (K ''x''))
:: = ''x''
for any term ''x''. Note that although ((S K K)
''x'') = (I ''x'') for any ''x'', (S K K)
itself is not equal to I. We say the terms are extensionally equal. Extensional equality captures the
mathematical notion of the equality of functions: that two functions
are ''equal'' if they always produce the same results for the same
arguments. In contrast, the terms themselves, together with the
reduction of primitive combinators, capture the notion of
''intensional equality'' of functions: that two functions are ''equal''
only if they have identical implementations up to the expansion of primitive
combinators. There are many ways to
implement an identity function; (S K K) and I
are among these ways. (S K S) is yet another. We
will use the word ''equivalent'' to indicate extensional equality,
reserving ''equal'' for identical combinatorial terms.
A more interesting combinator is the fixed point combinator or Y combinator, which can be used to implement recursion.

** Completeness of the S-K basis **

S and K can be composed to produce combinators that are extensionally equal to ''any'' lambda term, and therefore, by Church's thesis, to any computable function whatsoever. The proof is to present a transformation, ''T''nbsp; which converts an arbitrary lambda term into an equivalent combinator.
''T''nbsp;may be defined as follows:
# ''T'''x'' => ''x''
# ''T''''E''₁ ''E''₂) => (''T'''E''₁''T'''E''₂
# ''T'''λx''.''E'' => (K ''T'''E'' (if ''x'' does not occur free in ''E'')
# ''T'''λx''.''x'' => I
# ''T'''λx''.''λy''.''E'' => ''T'λx''.''T'λy''.''E'' (if ''x'' occurs free in ''E'')
# ''T'''λx''.(''E''₁ ''E''₂)=> (S ''T'''λx''.''E''₁''T'''λx''.''E₂'' (if ''x'' occurs free in ''E''₁ or ''E''₂)
Note that ''T''nbsp;as given is not a well-typed mathematical function, but rather a term rewriter: Although it eventually yields a combinator, the transformation may generate intermediary expressions that are neither lambda terms nor combinators, via rule (5).
This process is also known as ''abstraction elimination''. This definition is exhaustive: any lambda expression will be subject to exactly one of these rules (see Summary of lambda calculus above).
It is related to the process of ''bracket abstraction'', which takes an expression ''E'' built from variables and application and produces a combinator expression in which the variable x is not free, such that 'x'''E x'' = ''E'' holds.
A very simple algorithm for bracket abstraction is defined by induction on the structure of expressions as follows:
# 'x'''y'' := K ''y''
# 'x'''x'' := I
# 'x''''E₁'' ''E₂'') := S('x'''E₁'')('x'''E₂'')
Bracket abstraction induces a translation from lambda terms to combinator expressions, by interpreting lambda-abstractions using the bracket abstraction algorithm.

** Conversion of a lambda term to an equivalent combinatorial term **

For example, we will convert the lambda term ''λx''.''λy''.(''y'' ''x'') to a
combinatorial term:
:''T'''λx''.''λy''.(''y'' ''x''):: = ''T'λx''.''T'λy''.(''y'' ''x'') (by 5)
:: = ''T'''λx''.(S_''T''[''λy''.''y''''T''[''λy''.''x''.html" style="text-decoration: none;"class="mw-redirect" title="'λy''.''y''.html" style="text-decoration: none;"class="mw-redirect" title="'λx''.(S ''T''[''λy''.''y''">'λx''.(S ''T''[''λy''.''y''''T''[''λy''.''x''">'λy''.''y''.html" style="text-decoration: none;"class="mw-redirect" title="'λx''.(S ''T''[''λy''.''y''">'λx''.(S ''T''[''λy''.''y''''T''[''λy''.''x''] (by 6)
:: = ''T''[''λx''.(S I ''T''[''λy''.''x''])] (by 4)
:: = ''T''[''λx''.(S I (K ''T''[''x'']))] (by 3)
:: = ''T''[''λx''.(S I (K ''x''))] (by 1)
:: = (S ''T'''λx''.(S I)''T'''λx''.(K ''x'') (by 6)
:: = (S (K (S I)) ''T'''λx''.(K ''x'') (by 3)
:: = (S (K (S I)) (S ''T'''λx''.K''T'''λx''.''x'') (by 6)
:: = (S (K (S I)) (S (K K) ''T'''λx''.''x'') (by 3)
:: = (S (K (S I)) (S (K K) I)) (by 4)
If we apply this combinatorial term to any two terms ''x'' and ''y'' (by feeding them in a queue-like fashion into the combinator 'from the right'), it
reduces as follows:
: (S (K (S I)) (S (K K) I) x y)
:: = (K (S I) x (S (K K) I x) y)
:: = (S I (S (K K) I x) y)
:: = (I y (S (K K) I x y))
:: = (y (S (K K) I x y))
:: = (y (K K x (I x) y))
:: = (y (K (I x) y))
:: = (y (I x))
:: = (y x)
The combinatory representation, (S (K (S I)) (S (K K) I)) is much
longer than the representation as a lambda term, ''λx''.''λy''.(y x). This is typical. In general, the ''T''nbsp;construction may expand a lambda
term of length ''n'' to a combinatorial term of length
Θ(''n''^{3}).

** Explanation of the ''T''nbsp;transformation **

The ''T''nbsp;transformation is motivated by a desire to eliminate
abstraction. Two special cases, rules 3 and 4, are trivial: ''λx''.''x'' is
clearly equivalent to I, and ''λx''.''E'' is clearly equivalent to
(K ''T'''E'' if ''x'' does not appear free in ''E''.
The first two rules are also simple: Variables convert to themselves,
and applications, which are allowed in combinatory terms, are
converted to combinators simply by converting the applicand and the
argument to combinators.
It is rules 5 and 6 that are of interest. Rule 5 simply says that to convert a complex abstraction to a combinator, we must first convert its body to a combinator, and then eliminate the abstraction. Rule 6 actually eliminates the abstraction.
''λx''.(''E''₁ ''E''₂) is a function which takes an argument, say ''a'', and
substitutes it into the lambda term (''E''₁ ''E''₂) in place of ''x'',
yielding (''E''₁ ''E''₂)'x'' : = ''a'' But substituting ''a'' into (''E''₁ ''E''₂) in place of ''x'' is just the same as substituting it into both ''E''₁ and ''E''₂, so
: (''E''₁ ''E''₂)'x'' := ''a''= (''E''₁'x'' := ''a''''E''₂'x'' := ''a''
: (''λx''.(''E''₁ ''E''₂) ''a'') = ((''λx''.''E''₁ ''a'') (''λx''.''E''₂ ''a''))
::::: = (S ''λx''.''E''₁ ''λx''.''E''₂ ''a'')
::::: = ((S ''λx''.''E₁'' ''λx''.''E''₂) ''a'')
By extensional equality,
: ''λx''.(''E''₁ ''E''₂) = (S ''λx''.''E''₁ ''λx''.''E''₂)
Therefore, to find a combinator equivalent to ''λx''.(''E''₁ ''E''₂), it is
sufficient to find a combinator equivalent to (S ''λx''.''E''₁ ''λx''.''E''₂), and
: (S ''T'''λx''.''E''₁''T'''λx''.''E''₂
evidently fits the bill. ''E''₁ and ''E''₂ each contain strictly fewer
applications than (''E''₁ ''E''₂), so the recursion must terminate in a lambda
term with no applications at all—either a variable, or a term of the
form ''λx''.''E''.

** Simplifications of the transformation **

** η-reduction **

The combinators generated by the ''T''nbsp;transformation can be made
smaller if we take into account the ''η-reduction'' rule:
: ''T'''λx''.(''E'' ''x'')= ''T'''E'' (if ''x'' is not free in ''E'')
''λx''.(''E'' x) is the function which takes an argument, ''x'', and
applies the function ''E'' to it; this is extensionally equal to the
function ''E'' itself. It is therefore sufficient to convert ''E'' to
combinatorial form.
Taking this simplification into account, the example above becomes:
: ''T'''λx''.''λy''.(''y'' ''x''): = ...
: = (S (K (S I)) ''T'''λx''.(K ''x'')
: = (S (K (S I)) K) (by η-reduction)
This combinator is equivalent to the earlier, longer one:
: (S (K (S I)) K ''x y'')
: = (K (S I) ''x'' (K ''x'') ''y'')
: = (S I (K ''x'') ''y'')
: = (I ''y'' (K ''x y''))
: = (''y'' (K ''x y''))
: = (''y x'')
Similarly, the original version of the ''T''nbsp;transformation
transformed the identity function ''λf''.''λx''.(''f'' ''x'') into (S (S (K S) (S (K K) I)) (K I)). With the η-reduction rule, ''λf''.''λx''.(''f'' ''x'') is
transformed into I.

** One-point basis **

There are one-point bases from which every combinator can be composed extensionally equal to ''any'' lambda term. The simplest example of such a basis is where:
: X ≡ ''λx''.((xS)K)
It is not difficult to verify that:
: X (X (X X)) =^{β} K and
: X (X (X (X X))) =^{β} S.
Since is a basis, it follows that is a basis too. The Iota programming language uses X as its sole combinator.
Another simple example of a one-point basis is:
: X' ≡ ''λx''.(x K S K) with
: (X' X') X' =^{β} K and
: X' (X' X') =^{β} S
In fact, there exist infinitely many such bases.

** Combinators B, C **

In addition to S and K, Schönfinkel's paper included two combinators which are now called B and C, with the following reductions:
: (C ''f'' ''g'' ''x'') = ((''f'' ''x'') ''g'')
: (B ''f'' ''g'' ''x'') = (''f'' (''g'' ''x''))
He also explains how they in turn can be expressed using only S and K:
: B = (S (K S) K)
: C = (S (S (K (S (K S) K)) S) (K K))
These combinators are extremely useful when translating predicate logic or lambda calculus into combinator expressions. They were also used by Curry, and much later by David Turner, whose name has been associated with their computational use. Using them, we can extend the rules for the transformation as follows:
# ''T'''x'' ⇒ ''x''
# ''T''''E₁'' ''E₂'') ⇒ (''T'''E₁''''T'''E₂''
# ''T'''λx''.''E'' ⇒ (K ''T'''E'' (if ''x'' is not free in ''E'')
# ''T'''λx''.''x'' ⇒ I
# ''T'''λx''.''λy''.''E'' ⇒ ''T'λx''.''T'λy''.''E'' (if ''x'' is free in ''E'')
# ''T'''λx''.(''E₁'' ''E₂'')⇒ (S ''T'''λx''.''E₁''''T'''λx''.''E₂'' (if ''x'' is free in both ''E₁'' and ''E₂'')
# ''T'''λx''.(''E₁'' ''E₂'')⇒ (C ''T'''λx''.''E₁''''T'''E₂'' (if ''x'' is free in ''E₁'' but not ''E₂'')
# ''T'''λx''.(''E₁'' ''E₂'')⇒ (B ''T'''E₁''''T'''λx''.''E₂'' (if ''x'' is free in ''E₂'' but not ''E₁'')
Using B and C combinators, the transformation of
''λx''.''λy''.(''y'' ''x'') looks like this:
: ''T'''λx''.''λy''.(''y'' ''x''): = ''T'λx''.''T'λy''.(''y'' ''x'')
: = ''T'''λx''.(C_''T''[''λy''.''y''''x'').html" style="text-decoration: none;"class="mw-redirect" title="'λy''.''y''.html" style="text-decoration: none;"class="mw-redirect" title="'λx''.(C ''T''[''λy''.''y''">'λx''.(C ''T''[''λy''.''y''''x'')">'λy''.''y''.html" style="text-decoration: none;"class="mw-redirect" title="'λx''.(C ''T''[''λy''.''y''">'λx''.(C ''T''[''λy''.''y''''x'') (by rule 7)
: = ''T''[''λx''.(C I ''x'')]
: = (C I) (η-reduction)
: = $\backslash mathbf\_$ (traditional canonical notation : $\backslash mathbf\_\; =\; \backslash mathbf$)
: = $\backslash mathbf\text{'}$ (traditional canonical notation: $\backslash mathbf\text{'}\; =\; \backslash mathbf$)
And indeed, (C I ''x'' ''y'') does reduce to (''y'' ''x''):
: (C I ''x'' ''y'')
: = (I ''y'' ''x'')
: = (''y'' ''x'')
The motivation here is that B and C are limited versions of S.
Whereas S takes a value and substitutes it into both the applicand and
its argument before performing the application, C performs the
substitution only in the applicand, and B only in the argument.
The modern names for the combinators come from Haskell Curry's doctoral thesis of 1930 (see B, C, K, W System). In Schönfinkel's original paper, what we now call S, K, I, B and C were called S, C, I, Z, and T respectively.
The reduction in combinator size that results from the new transformation rules
can also be achieved without introducing B and C, as demonstrated in Section 3.2 of.

= CL_{K} versus CL_{I} calculus

= A distinction must be made between the CL_{K} as described in this article and the CL_{I} calculus. The distinction corresponds to that between the λ_{K} and the λ_{I} calculus. Unlike the λ_{K} calculus, the λ_{I} calculus restricts abstractions to:
::''λx''.''E'' where ''x'' has at least one free occurrence in ''E''.
As a consequence, combinator K is not present in the λ_{I} calculus nor in the CL_{I} calculus. The constants of CL_{I} are: I, B, C and S, which form a basis from which all CL_{I} terms can be composed (modulo equality). Every λ_{I} term can be converted into an equal CL_{I} combinator according to rules similar to those presented above for the conversion of λ_{K} terms into CL_{K} combinators. See chapter 9 in Barendregt (1984).

** Reverse conversion **

The conversion ''L''nbsp;from combinatorial terms to lambda terms is
trivial:
: ''L''''I = ''λx''.''x''
: ''L''''K = ''λx''.''λy''.''x''
: ''L''''C = ''λx''.''λy''.''λz''.(''x'' ''z'' ''y'')
: ''L''''B = ''λx''.''λy''.''λz''.(''x'' (''y'' ''z''))
: ''L''''S = ''λx''.''λy''.''λz''.(''x'' ''z'' (''y'' ''z''))
: ''L''''E₁'' ''E₂'')= (''L'''E₁''''L'''E₂''
Note, however, that this transformation is not the inverse
transformation of any of the versions of ''T''nbsp;that we have seen.

** Undecidability of combinatorial calculus **

A normal form is any combinatory term in which the primitive combinators that occur, if any, are not applied to enough arguments to be simplified. It is undecidable whether a general combinatory term has a normal form; whether two combinatory terms are equivalent, etc. This is equivalent to the undecidability of the corresponding problems for lambda terms. However, a direct proof is as follows:
First, the term
: Ω = (S I I (S I I))
has no normal form, because it reduces to itself after three steps, as
follows:
: (S I I (S I I))
: = (I (S I I) (I (S I I)))
: = (S I I (I (S I I)))
: = (S I I (S I I))
and clearly no other reduction order can make the expression shorter.
Now, suppose N were a combinator for detecting normal forms,
such that
:$(\backslash mathbf\; \backslash \; x)\; =\; \backslash begin\; \backslash mathbf,\; \backslash text\; x\; \backslash text\; \backslash \backslash \; \backslash mathbf,\; \backslash text\; \backslash end$
:(Where and represent the conventional Church encodings of true and false, ''λx''.''λy''.''x'' and ''λx''.''λy''.''y'', transformed into combinatory logic. The combinatory versions have and .)
Now let
: ''Z'' = (C (C (B N (S I I)) Ω) I)
now consider the term (S I I ''Z''). Does (S I I ''Z'') have a normal
form? It does if and only if the following do also:
: (S I I ''Z'')
: = (I ''Z'' (I ''Z''))
: = (''Z'' (I ''Z''))
: = (''Z'' ''Z'')
: = (C (C (B N (S I I)) Ω) I ''Z'') (definition of ''Z'')
: = (C (B N (S I I)) Ω ''Z'' I)
: = (B N (S I I) ''Z'' Ω I)
: = (N (S I I ''Z'') Ω I)
Now we need to apply N to (S I I ''Z'').
Either (S I I ''Z'') has a normal form, or it does not. If it ''does''
have a normal form, then the foregoing reduces as follows:
: (N (S I I ''Z'') Ω I)
: = (K Ω I) (definition of N)
: = Ω
but Ω does ''not'' have a normal form, so we have a contradiction. But
if (S I I ''Z'') does ''not'' have a normal form, the foregoing reduces as
follows:
: (N (S I I ''Z'') Ω I)
: = (K I Ω I) (definition of N)
: = (I I)
: = I
which means that the normal form of (S I I ''Z'') is simply I, another
contradiction. Therefore, the hypothetical normal-form combinator N
cannot exist.
The combinatory logic analogue of Rice's theorem says that there is no complete nontrivial predicate. A ''predicate'' is a combinator that, when applied, returns either T or F. A predicate N is ''nontrivial'' if there are two arguments ''A'' and ''B'' such that N ''A'' = T and N ''B'' = F. A combinator N is ''complete'' if and only if N''M'' has a normal form for every argument ''M''. The analogue of Rice's theorem then says that every complete predicate is trivial. The proof of this theorem is rather simple.

** Applications **

** Compilation of functional languages **

David Turner used his combinators to implement the SASL programming language.
Kenneth E. Iverson used primitives based on Curry's combinators in his J programming language, a successor to APL. This enabled what Iverson called tacit programming, that is, programming in functional expressions containing no variables, along with powerful tools for working with such programs. It turns out that tacit programming is possible in any APL-like language with user-defined operators.

** Logic **

The Curry–Howard isomorphism implies a connection between logic and programming: every proof of a theorem of intuitionistic logic corresponds to a reduction of a typed lambda term, and conversely. Moreover, theorems can be identified with function type signatures. Specifically, a typed combinatory logic corresponds to a Hilbert system in proof theory.
The K and S combinators correspond to the axioms
:AK: ''A'' → (''B'' → ''A''),
:AS: (''A'' → (''B'' → ''C'')) → ((''A'' → ''B'') → (''A'' → ''C'')),
and function application corresponds to the detachment (modus ponens) rule
:MP: from ''A'' and ''A'' → ''B'' infer ''B''.
The calculus consisting of AK, AS, and MP is complete for the implicational fragment of the intuitionistic logic, which can be seen as follows. Consider the set ''W'' of all deductively closed sets of formulas, ordered by inclusion. Then $\backslash langle\; W,\backslash subseteq\backslash rangle$ is an intuitionistic Kripke frame, and we define a model $\backslash Vdash$ in this frame by
:$X\backslash Vdash\; A\backslash iff\; A\backslash in\; X.$
This definition obeys the conditions on satisfaction of →: on one hand, if $X\backslash Vdash\; A\backslash to\; B$, and $Y\backslash in\; W$ is such that $Y\backslash supseteq\; X$ and $Y\backslash Vdash\; A$, then $Y\backslash Vdash\; B$ by modus ponens. On the other hand, if $X\backslash not\backslash Vdash\; A\backslash to\; B$, then $X,A\backslash not\backslash vdash\; B$ by the deduction theorem, thus the deductive closure of $X\backslash cup\backslash $ is an element $Y\backslash in\; W$ such that $Y\backslash supseteq\; X$, $Y\backslash Vdash\; A$, and $Y\backslash not\backslash Vdash\; B$.
Let ''A'' be any formula which is not provable in the calculus. Then ''A'' does not belong to the deductive closure ''X'' of the empty set, thus $X\backslash not\backslash Vdash\; A$, and ''A'' is not intuitionistically valid.

See also

* Applicative computing systems * B, C, K, W system * Categorical abstract machine * Combinatory categorial grammar * Explicit substitution * Fixed point combinator * Graph reduction machine * Lambda calculus and Cylindric algebra, other approaches to modelling quantification and eliminating variables * SKI combinator calculus * Supercombinator * ''To Mock a Mockingbird''

** References **

Further reading

* * * * * * * * Reprinted as Chapter 23 of Quine's ''Selected Logic Papers'' (1966), pp. 227–235 * Schönfinkel, Moses, 1924,

Über die Bausteine der mathematischen Logik

" translated as "On the Building Blocks of Mathematical Logic" in ''From Frege to Gödel: a source book in mathematical logic, 1879–1931'', Jean van Heijenoort, ed. Harvard University Press, 1967. . The article that founded combinatory logic. * Smullyan, Raymond, 1985. ''To Mock a Mockingbird''. Knopf. . A gentle introduction to combinatory logic, presented as a series of recreational puzzles using bird watching metaphors. *--------, 1994. ''Diagonalization and Self-Reference''. Oxford Univ. Press. Chapters 17–20 are a more formal introduction to combinatory logic, with a special emphasis on fixed point results. *Sørensen, Morten Heine B. and Paweł Urzyczyn, 1999.

Lectures on the Curry–Howard Isomorphism.

' University of Copenhagen and University of Warsaw, 1999. * .

External links

*Stanford Encyclopedia of Philosophy:

Combinatory Logic

by Katalin Bimbó.

1920–1931 Curry's block notes.

*Keenan, David C. (2001)

*Rathman, Chris, "ttp://www.angelfire.com/tx4/cus/combinator/birds.html Combinator Birds. A table distilling much of the essence of Smullyan (1985).

Drag 'n' Drop Combinators.

(Java Applet)

Binary Lambda Calculus and Combinatory Logic.

Combinatory logic reduction web server

{{authority control Combinatory logic Category:Lambda calculus Category:Logic in computer science

In mathematics

Combinatory logic was originally intended as a 'pre-logic' that would clarify the role of quantified variables in logic, essentially by eliminating them. Another way of eliminating quantified variables is Quine's predicate functor logic. While the expressive power of combinatory logic typically exceeds that of first-order logic, the expressive power of predicate functor logic is identical to that of first order logic (Quine 1960, 1966, 1976). The original inventor of combinatory logic, Moses Schönfinkel, published nothing on combinatory logic after his original 1924 paper. Haskell Curry rediscovered the combinators while working as an instructor at Princeton University in late 1927. In the late 1930s, Alonzo Church and his students at Princeton invented a rival formalism for functional abstraction, the lambda calculus, which proved more popular than combinatory logic. The upshot of these historical contingencies was that until theoretical computer science began taking an interest in combinatory logic in the 1960s and 1970s, nearly all work on the subject was by Haskell Curry and his students, or by Robert Feys in Belgium. Curry and Feys (1958), and Curry ''et al.'' (1972) survey the early history of combinatory logic. For a more modern treatment of combinatory logic and the lambda calculus together, see the book by Barendregt, which reviews the models Dana Scott devised for combinatory logic in the 1960s and 1970s.

In computing

In computer science, combinatory logic is used as a simplified model of computation, used in computability theory and proof theory. Despite its simplicity, combinatory logic captures many essential features of computation. Combinatory logic can be viewed as a variant of the lambda calculus, in which lambda expressions (representing functional abstraction) are replaced by a limited set of ''combinators'', primitive functions without free variables. It is easy to transform lambda expressions into combinator expressions, and combinator reduction is much simpler than lambda reduction. Hence combinatory logic has been used to model some non-strict functional programming languages and hardware. The purest form of this view is the programming language Unlambda, whose sole primitives are the S and K combinators augmented with character input/output. Although not a practical programming language, Unlambda is of some theoretical interest. Combinatory logic can be given a variety of interpretations. Many early papers by Curry showed how to translate axiom sets for conventional logic into combinatory logic equations (Hindley and Meredith 1990). Dana Scott in the 1960s and 1970s showed how to marry model theory and combinatory logic.

= CL

= A distinction must be made between the CL

Proof: By reductio ad absurdum. Suppose there is a complete non trivial predicate, say N. Because N is supposed to be non trivial there are combinators ''A'' and ''B'' such that :(N ''A'') = T and :(N ''B'') = F. :Define NEGATION ≡ ''λx''.(if (N ''x'') then ''B'' else ''A'') ≡ ''λx''.((N ''x'') ''B'' ''A'') :Define ABSURDUM ≡ (Y NEGATION) Fixed point theorem gives: ABSURDUM = (NEGATION ABSURDUM), for :ABSURDUM ≡ (Y NEGATION) = (NEGATION (Y NEGATION)) ≡ (NEGATION ABSURDUM). Because N is supposed to be complete either: # (N ABSURDUM) = F or # (N ABSURDUM) = T * Case 1: F = (N ABSURDUM) = N (NEGATION ABSURDUM) = (N ''A'') = T, a contradiction. * Case 2: T = (N ABSURDUM) = N (NEGATION ABSURDUM) = (N ''B'') = F, again a contradiction. Hence (N ABSURDUM) is neither T nor F, which contradicts the presupposition that N would be a complete non trivial predicate. Q.E.D.From this undecidability theorem it immediately follows that there is no complete predicate that can discriminate between terms that have a normal form and terms that do not have a normal form. It also follows that there is no complete predicate, say EQUAL, such that: :(EQUAL ''A B'') = T if ''A'' = ''B'' and :(EQUAL ''A B'') = F if ''A'' ≠ ''B''. If EQUAL would exist, then for all ''A'', ''λx.''(EQUAL ''x A'') would have to be a complete non trivial predicate.

See also

* Applicative computing systems * B, C, K, W system * Categorical abstract machine * Combinatory categorial grammar * Explicit substitution * Fixed point combinator * Graph reduction machine * Lambda calculus and Cylindric algebra, other approaches to modelling quantification and eliminating variables * SKI combinator calculus * Supercombinator * ''To Mock a Mockingbird''

Further reading

* * * * * * * * Reprinted as Chapter 23 of Quine's ''Selected Logic Papers'' (1966), pp. 227–235 * Schönfinkel, Moses, 1924,

Über die Bausteine der mathematischen Logik

" translated as "On the Building Blocks of Mathematical Logic" in ''From Frege to Gödel: a source book in mathematical logic, 1879–1931'', Jean van Heijenoort, ed. Harvard University Press, 1967. . The article that founded combinatory logic. * Smullyan, Raymond, 1985. ''To Mock a Mockingbird''. Knopf. . A gentle introduction to combinatory logic, presented as a series of recreational puzzles using bird watching metaphors. *--------, 1994. ''Diagonalization and Self-Reference''. Oxford Univ. Press. Chapters 17–20 are a more formal introduction to combinatory logic, with a special emphasis on fixed point results. *Sørensen, Morten Heine B. and Paweł Urzyczyn, 1999.

Lectures on the Curry–Howard Isomorphism.

' University of Copenhagen and University of Warsaw, 1999. * .

External links

*Stanford Encyclopedia of Philosophy:

Combinatory Logic

by Katalin Bimbó.

1920–1931 Curry's block notes.

*Keenan, David C. (2001)

*Rathman, Chris, "ttp://www.angelfire.com/tx4/cus/combinator/birds.html Combinator Birds. A table distilling much of the essence of Smullyan (1985).

Drag 'n' Drop Combinators.

(Java Applet)

Binary Lambda Calculus and Combinatory Logic.

Combinatory logic reduction web server

{{authority control Combinatory logic Category:Lambda calculus Category:Logic in computer science