TL; DR
これが Iota による HelloWorld です。注目すべきなのは、このプログラムはたった一個の組み込み関数 i だけで作られているということです。
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ラムダ計算とは
Iota によるプログラミングのためにはラムダ計算の知識が必要不可欠です。ラムダ計算についてはすでに素晴らしい記事があるので、ここではざっくりと説明していきます。
ラムダ計算は計算模型の一種です。計算模型とは、噛み砕いて説明すれば「如何にして計算を行うか？」を表現したものです。現代のコンピュータが「チューリングマシン」をもとに作られていることは有名な話ですが、このチューリングマシンも計算模型の一種です。
ただしラムダ計算はチューリングマシンとは全く違った方法で計算を実現します。ラムダ計算による計算は以下のように記述されます。
$$
\lambda\text{[引数]}.\text{[返り値]}
$$
具体例として、「受け取った引数をそのまま返す関数」はこのように書けます。
$$
\lambda x.x
$$
また、「受け取った自然数に 1 を足して返す関数」はこのようになります。
$$
\lambda x.x + 1
$$
ただし純粋なラムダ計算には "+" や "-" のような演算もなければ "1" や "2" といった自然数もないので、これらは別途定義する必要があります。これについては後で説明します。
こうして表記した関数の右側に引数を置きます。
$$
(\lambda x.x + 1)\ 4 = 5
$$
「受け取った自然数に 1 を足して返す関数」に 4 を渡したので、結果は $4 + 1 = 5$ となります。
また、関数に関数を渡すこともできます。こんな感じです。
$$
(\lambda f.f\ 7)(\lambda x.x + 1)
$$
この式においては $\lambda f.f\ 7$ が関数に、$\lambda x.x + 1$ が引数に当たります。よって計算結果はこのようになります。
\begin{align*}
& (\lambda f.f\ 7)(\lambda x.x + 1) \\
=\ & (\lambda x.x + 1)\ 7 \\
=\ & 8
\end{align*}
Python で再現するとこんな感じです。
result = (lambda f: f(7))(lambda x: x + 1)
print(result) # 8
最初は少し混乱すると思いますが、すぐ慣れます。
カリー化
今のままでは引数が一個の関数しか作れないので、「$n$ と $m$ の和を求める関数」などが作れません。そこでカリー化という考え方を用います。先に結論からお見せすると「$n$ と $m$ の和を求める関数」はこのようになります。
$$
\lambda n. \lambda m. n + m
$$
これ、何が起きているかわかるでしょうか。試しにこの関数に "3" を渡してみます。
$$
(\lambda n. \lambda m. n + m)\ 3 = \lambda m. 3 + m
$$
$\lambda n. \lambda m. n + m$ という式に 3 が渡された結果、「引数 $m$ に 3 を足した値を返す関数」である $\lambda m. 3 + m$ が返ってきました。これにさらに 5 を渡してみましょう。
$$
(\lambda m. 3 + m)\ 5 = 8
$$
無事に $3 + 5 = 8$ が求まりました。今やったことを Python で表現するとこんな感じになります。
result = (lambda n: lambda m: n + m)(3)(5)
print(result) # 8
このように、一引数関数しかなくても「事実上の多引数関数」は作れるのです。これを関数のカリー化といいます。
ただし $\lambda n. \lambda m. n + m$ という書き方は少し冗長なので、普通は $\lambda nm. n + m$ と、あたかも二引数関数であるかのような書き方をします。
ラムダ計算によるプログラミング
ではこんなものでどのようにプログラミングを行うのでしょうか。それを考える前に、そもそも「プログラムとは何ぞや？」ということについて考えます。
プログラムの代表例として、Linux の基本的なコマンドをいくつか見ていきましょう。まずは echo です。
$ echo hoge
hoge
echo というプログラムに "hoge" という文字列を渡したところ、画面には "hoge" という文字列が表示されました。
次に bc です。
$ echo "3+9" | bc
12
bc に "3+9" という文字列を渡したところ、計算結果を表す "12" という文字列が返ってきました。
最後に sed です。
$ echo "hello, world" | sed "s/hello/goodbye/"
goodbye, world
"hello, world" という文字列を変形した "goodbye, world" という文字列が表示されています。
さて今あげた三つの例には「文字列を受け取り、文字列を返す」という共通点がありました。つまり「プログラム」とは、極限まで単純化すれば「文字列から文字列への写像」なのです。
先ほど「現代的コンピュータの基礎となっているもの」としてチューリングマシンを挙げましたが、これなどまさに「文字列を受け取って文字列を返すもの」の最たる例です。チューリングマシンはテープに書き込まれた文字を入力として受け取り、それを所定の動作に従って書き換えたものが出力に当たるからです。
そういうわけで、ラムダ計算でのプログラミングを実現するにはチューリングマシンのように文字列を処理する仕組みが必要になります。一体どうすればよいのでしょうか？
チャーチエンコーディング
ラムダ計算においては、文字列を自然数の列として扱います。例えば "hello" という文字列の場合、まずはこれを
{
文字 'h' を表す自然数, 文字 'e' を表す自然数, ...
}
といった具合に表します。文字に対する自然数の割り当てとして ASCII コードを用いれば、"hello" は {104, 101, 108, 108, 111} と表現されます。
しかしここで一つの問題が立ち現れます。先ほどこんなことを言っていたのを覚えているでしょうか。
ただし純粋なラムダ計算には "+" や "-" のような演算もなければ "1" や "2" といった自然数もないので、これらは別途定義する必要があります。これについては後で説明します。
ラムダ計算には自然数という概念はありません。というか、ラムダ計算には「一つのラムダ式を受け取って一つのラムダ式を返すラムダ式」しかありません。先ほどは $\lambda x.x + 1$ のような式を作っていましたが、あれはただの方便です。
しかし、こんなラムダ式でも自然数を表す方法は存在するのです。その代表例がアロンゾ・チャーチによるチャーチエンコーディングです。これは具体例を見ていただくのが早いでしょう。
\begin{align*}
0 &= \lambda fx.x \\
1 &= \lambda fx.fx \\
2 &= \lambda fx.f(fx) \\
\vdots
\end{align*}
このように、チャーチエンコーディングでは自然数 $N$ を「$f$ と $x$ を受け取り、『$x$ に $f$ を $N$ 回適用したもの』を返す関数」と表します。
なんだか狐につままれたような感じですが、これでうまくいくのです。詳細は先ほどの記事にもありますが、この自然数に対し足し算でも掛け算でも、階乗すらも計算することができます。
スコットエンコーディング
そんな感じで自然数は表せました。しかしこれだけではダメです。さきほど「"hello" という文字列は {104, 101, 108, 108, 111} という自然数のリストで表現される」とお話ししました。つまり、「自然数」を表現する方法に加えて「リスト」を表現する方法も必要になります。これを実現するのがデイナ・スコットによるスコットエンコーディングです。スコットエンコーディングでは以下のような関数を定めます。
\begin{align*}
\mathrm{emptyList} &= \lambda fxy.x \\
\mathrm{cons} &= \lambda abf.fab \\
\mathrm{car} &= \lambda p.p(\lambda xy.x) \\
\mathrm{cdr} &= \lambda p.p(\lambda xy.y)
\end{align*}
LISP をやったことがある方は見覚えのある名前だと思います。まず $\mathrm{cons}$ は二つの引数を組み合わせて一組の「ペア」を作る関数になります。つまり、$\mathrm{cons}\ b\ a$ で「a と b を組み合わせたペア」になります。これを用いて以下のようにリストを定義します。
\begin{align*}
\{\} &= \mathrm{emptyList} = \lambda fxy.x \\
\{a\} &= \mathrm{cons}\ a\ \{\} \\
\{b, a\} &= \mathrm{cons}\ b\ (\mathrm{cons}\ a\ \{\}) \\
\{c, b, a\} &= \mathrm{cons}\ c\ (\mathrm{cons}\ b\ (\mathrm{cons}\ a\ \{\})) \\
&\vdots
\end{align*}
このように、$\mathrm{cons}\ \text{追加する要素}\ \text{追加先のリスト}$ としてリストに要素を追加し続けることができるのです。
また $\mathrm{car}$ と $\mathrm{cdr}$ ですが、これはそれぞれ「リストの先頭要素を取り出す関数」と「リストから先頭要素を除いたリストを取り出す関数」です。実際に計算してみるとわかるのですが、$\mathrm{car}(\mathrm{cons}\ c\ (\mathrm{cons}\ b\ (\mathrm{cons}\ a\ \{\})))$ は $c$ になり、$\mathrm{cdr}(\mathrm{cons}\ c\ (\mathrm{cons}\ b\ (\mathrm{cons}\ a\ \{\})))$ は $\mathrm{cons}\ b\ (\mathrm{cons}\ a\ \{\})$ となります。
ラムダ計算の処理手順
さてこれで文字列を「自然数のリスト」として表現する手立てが整いました。ラムダ計算によるプログラムは以下のような処理手順になります。
- 入力文字列を自然数のリスト（を表現したラムダ式）に変換する。これを $L$ と置く。
- プログラムにあたるラムダ式 $P$ に $L$ を渡し、$P\ L$ を求める。
- $P\ L$ を自然数のリストと解釈し、文字列に戻して出力する。
例えば、以下のラムダ式が「プログラム」であるとします。
$$
\lambda x.x
$$
これに入力文字列 "hogehoge" を食わせます。
$$
\lambda x.x\ (\text{"hogehoge" という文字列を表現したラムダ式})
$$
$\lambda x.x$ は入力をそのまま返す関数でしたから、これは結局文字列 "hogehoge" を表現したラムダ式が返ってくることになります。つまり、これはラムダ式による echo の実装 になります。
別の例も見てみましょう。
$$
\lambda x.(\text{"Hello, World!" という文字列を表現したラムダ式})
$$
このプログラムは「引数の内容には一切関係なく "Hello, World!" という文字列を返す関数」になります。つまり、こちらは HelloWorld の実装になります。
このような仕組みによりラムダ計算で「文字列を受け取って文字列を返す」ことが可能になりました。実際、ラムダ計算はチューリング完全であることが証明されています。つまりラムダ式をうまく設計してやれば、任意のチューリングマシンを模倣することが可能になるのです。
SKI コンビネータ
ラムダ計算はとても単純な決まり事のみでチューリング完全性を達成していたわけですが、さらに単純化することもできます。実は、任意のラムダ式は以下の三つの式の組み合わせのみで表現できることが知られているのです。
\begin{align*}
I &= \lambda x.x \\
K &= \lambda xy.x \\
S &= \lambda xyz.xz(yz)
\end{align*}
よってこの $S$, $K$, $I$ の組み合わせもチューリング完全です。この三つをまとめて SKI コンビネータといいます。
「コンビネータ」とは「自由変数を含まないラムダ式」という意味です。自由変数とは、ざっくりと言えば「引数に入っていない変数」のことです。こちらのラムダ式をご覧ください。
$$
\lambda x.fx
$$
このラムダ式は $x$ を受け取って $f x$ を返します。しかしこの $f$ は引数に入っていないので正体不明です。この $f$ のような変数を自由変数と言います。また、自由変数ではない変数は束縛変数と言います。つまり $x$ は束縛変数です。
実は任意のラムダ式 $x$, $y$ に対し $SKxy = y$ が成り立ちます。したがって、$SKx$ は「実質的に $I$ と同じ」といえます（このことを専門的には「外延的に等しい」といいます）。なので $S$ と $K$ だけでもチューリング完全です。
ιコンビネータ
さらに、SKI コンビネータはもっと単純化することもできます。まずは $\iota$1 コンビネータを定義します。
\begin{align*}
\iota &= \lambda f.fSK \\
&= \lambda f.f(\lambda xyz.xz(yz))(\lambda xy.x)
\end{align*}
この $\iota$ ですが、なんとこれ一つで $S$, $K$, $I$ の全てを表せます。
\begin{align*}
I &= \iota\iota \\
K &= \iota(\iota(\iota\iota)) \\
S &= \iota(\iota(\iota(\iota\iota))) \\
\end{align*}
記事冒頭で「たった一個の組み込み関数 i」だけで HelloWorld をしていましたが、この i が $\iota$ だったんですね。
このように Iota 言語は「たった一つの関数のみでチューリング完全性を達成する」という離れ業を成し遂げています。この Iota のように、「極めて少ない構成要素のみでチューリング完全性を達成する」ことをチューリング陥穽 (Turing turpit) と言います。
ただし一つ補足しておきます。この「チューリング陥穽」という言葉の元ネタはアラン・パリスの Epigrams on Programming（プログラミングにおける警句集）なのですが、そこではこのように記されています。
54. Beware of the Turing tar-pit in which everything is possible but nothing of interest is easy.
（全てが可能だが、その一方で重要なことは何一つ簡単にはできない「チューリング陥穽」に気をつけろ。）
つまり「チューリング陥穽」という言葉自体は残念ながら誉め言葉とは言えなさそうです。
実装
今回は C++ で実装していきます。実はあること（後述）に目をつぶれば実装は一瞬で終わります。
そもそもラムダ式とは何だったかというと、「ラムダ式を受け取ってラムダ式を返す関数」でした。よって C++ によるラムダ式の実装はこれだけです。
class lambda final : std::function<lambda(lambda)> {
using std::function<lambda(lambda)>::function;
public:
using std::function<lambda(lambda)>::operator();
};
これだけで $S$ も $K$ も $I$ も作れます。
#include <functional>
class lambda final : std::function<lambda(lambda)> {
using std::function<lambda(lambda)>::function;
public:
using std::function<lambda(lambda)>::operator();
};
lambda I = [](lambda x) {
return x;
};
lambda K = [](lambda x) {
return [x](lambda y) {
return x;
};
};
lambda S = [](lambda x) {
return [x](lambda y) {
return [x, y](lambda z) {
return x(z)(y(z));
};
};
};
また、チャーチエンコーディングの実装はこんな感じになります。
lambda church_encode(unsigned n)
{
return [n](lambda f) {
return [n, f](lambda x) {
for (unsigned i = 0; i < n; ++i) {
x = f(x);
}
return x;
};
};
}
unsigned church_decode(lambda n)
{
unsigned decoded = 0;
n(
[&decoded](lambda _){ ++decoded; return _; }
)(
I /* ここは別に何でもいい */
);
return decoded;
}
int main()
{
std::cout << church_decode(church_encode(42)) << std::endl; /* 42 */
}
チャーチエンコーディングによる自然数 $N$ の定義は「$f$ と $x$ を受け取り、『$x$ に $f$ を $N$ 回適用したもの』を返す関数」でしたから、$f$ には「適当な変数をインクリメントする関数」、$x$ にはなんでもいいので適当なラムダ式を渡してやればデコードが可能になります。このままサクサク実装していけば完成・・・
・・・と言いたいところですが、このままではある大問題が発生してしまいます。
「評価戦略」
突然ですが、このラムダ式の計算結果は何になるでしょう。
$$
\lambda x.xx\ (\lambda x.xx)
$$
実際に展開してみましょう。
\begin{align*}
\lambda x.xx\ (\lambda x.xx) &= \lambda x.xx\ (\lambda x.xx) \\
&= \lambda x.xx\ (\lambda x.xx) \\
&= \lambda x.xx\ (\lambda x.xx) \\
& \vdots
\end{align*}
見ての通り、このラムダ式の展開は永遠に終わりません。こういうのを専門的には「正規形が存在しない」といいます。
ちなみに $\lambda x.xx$ は U コンビネータ、$\lambda x.xx\ (\lambda x.xx) (= UU)$ は $\Omega$ コンビネータと呼ばれます。
ではこれを踏まえたうえで、こちらのラムダ式の計算結果はどうなるでしょうか？
$$
(\lambda xy.y)\ (\lambda x.xx\ (\lambda x.xx))\ I
$$
少し見づらいので、$\lambda x.xx\ (\lambda x.xx)$ を $\Omega$ と置きましょう。するとこうなってしまいます。
$$
(\lambda xy.y)\ \Omega\ I = I
$$
なんと、$\Omega$ は永遠に展開が終わらない式であったのにもかかわらず、それを含む式はきちんと計算結果が出てきました。これはすなわち、どうせ $\Omega$ は使わないのだから、そもそも展開する必要もなかったということです。
ところが C++ で実装する場合はこうも行きません。
int main()
{
[](lambda x) { return [](lambda y) { return y; }; }
(
/* こいつの展開は永遠に終わらない */
[](lambda x) { return x(x); }([](lambda x) { return x(x); })
)
(
I
);
/* Command terminated */
}
専門的には、C++ は正格評価という評価戦略を用いています。これはどういうことかというと、まず引数の評価を最後まで終わらせて、そのあとで関数に渡すということです。さきほどは「どうせ $\Omega$ は使わないのだから、そもそも展開する必要もなかった」という話をしましたが、C++ の立場からすれば関数の中で引数が使われるかどうかなんて関係ありません。使う使わないに関わらず、まずは引数をすべて評価してしまうのです。なので、本来であれば評価する必要のない引数まで評価し続けてしまい、メモリを食い尽くして異常終了してしまうわけです。
ところが世の中には正格評価ではない評価戦略、非正格評価をする言語もあります。その代表例が関数型言語 Haskell です。
main = do print $ fst ('a', 1 `div` 0) -- 'a'
このコードは文字 'a' と 1 ÷ 0 のペアを作り、その先頭要素を画面に出力します。つまり画面には 'a' と表示されます。
1 ÷ 0 だなんていかにもエラーが発生しそうな計算です。実際、Haskell でも 1 ÷ 0 を出力しようとすればエラーになります。
main = do print $ 1 `div` 0 -- Main: divide by zero
ところが先ほどの例ではエラーになりません。これはなぜかというと、画面に表示したいのは ('a', 1 `div` 0) の先頭要素のみであるため、逆に言えばそれ以外の要素はどうせ使わないからです。このように Haskell 等の言語では、値が実際に必要になるまで評価が行われません。これを非正格評価と言います。つまりラムダ式を正しく計算するには非正格評価を行わなければならなかったのです。
しかし正格・非正格はあくまでも言語レベルで定められていることなので、「C++ を使う！」と決めてしまったならば非正格評価を行うことは決してできません。それでは C++ でラムダ式を処理することは不可能なのでしょうか？
いいえ、C++ でも非正格評価を模倣することはできます。このようにするのです。
class lambda final : std::function<lambda(lambda)> {
using std::function<lambda(lambda)>::function;
private:
/* C++ 「本来」の呼び出し。正格評価にあたる。 */
lambda pass_by_value(lambda arg) const
{
return std::function<lambda(lambda)>::operator()(arg);
}
public:
/* 正格評価による呼び出しを無名関数で包むことで遅延させる。 */
lambda operator()(lambda arg) const
{
return [arg, *this](lambda _) {
return pass_by_value(arg).pass_by_value(_);
};
}
friend unsigned church_decode(lambda);
};
/* （中略） */
unsigned church_decode(lambda n)
{
unsigned decoded = 0;
n(
[&decoded](lambda _){ ++decoded; return _; }
)(
I /* ここは別に何でもいい */
).pass_by_value(
I /* ここも別に何でもいい */
);
return decoded;
}
C++ 本来の正格評価には pass_by_value という名前をつけておき、private 指定することで隠蔽します。そして非正格評価の模倣に当たる部分が operator() です。ここでは引数 arg を実際に渡してしまうのではなく、「arg を渡す」という動作をする関数を返します。これにより arg が実際に関数に渡されるのを遅延させることができるのです。
ただしプログラムである以上いつかは画面に何かを表示しなければならないので、関数の呼び出しを永遠に遅延させ続けるわけにはいきません。具体的には「チャーチエンコーディングされた整数をデコードするとき」と「スコットエンコーディングされたリストをデコードするとき」の二つはどうしても pass_by_value による正格評価が必要になります。そこでこれらデコード関数だけは特別に friend 指定しておくわけです。
この手法により非正格評価を再現することが可能になります。このコードを見てください。
int main()
{
lambda foo =
[](lambda x) { return [](lambda y) { return y; }; }
(
/* こいつが永遠に展開されてしまうこともない */
[](lambda x) { return x(x); }([](lambda x) { return x(x); })
)
(
church_encode(42)
);
std::cout << church_decode(foo) << std::endl; /* 42 */
}
さっきまでは関数呼び出しの前に引数を評価していたので異常終了してしまいましたが、今回は無事に必要な引数だけが実際に評価されました。
Hello, World!
以上のような方策を用いることで C++ でもラムダ計算の処理系を実装できます。スコットエンコーディング等の実装の詳細は省略しますが、ここまでくれば何も難しいことは必要ありません。完成品がこちらになります。
それでは満を持して HelloWorld していきます。先ほどもお見せしましたが、HelloWorld に当たるプログラムはこんなラムダ式です。
$$
\lambda x.(\text{"Hello, World!" という文字列を表現したラムダ式})
$$
まずはこのラムダ式を $S$, $K$, $I$ の三つのみで表現します。具体的な変換アルゴリズムはやはりこちらの記事に記されているので、今回は変換結果だけお借りします。
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ここまでくればあとは簡単です。$\iota$ と $S$, $K$, $I$ の関係はこのように↓なっていたので、
\begin{align*}
I &= \iota\iota \\
K &= \iota(\iota(\iota\iota)) \\
S &= \iota(\iota(\iota(\iota\iota))) \\
\end{align*}
この等式に従って機械的に変換すればおしまいです。それが記事冒頭でお見せしたあのコードになります。あとはこれを C++ ソースコードに貼り付けて完成です。
iota_hello.cpp
/* Download from https://github.com/reika727/LambdaCpp !!! */
#include "lambda-expression.hpp"
#include <string>
#include <vector>
#include <algorithm>
#include <iostream>
using namespace lambda::combinators;
int main()
{
/* プログラム本体に当たる部分 */
const lambda::expression program = i(i(i( /* ... 中略 ... */ )));
/* program への引数。ただどうせ使われないので内容は何でもいい */
std::string foo = "HOGE HOGE FUGA FUGA!!!";
/* プログラムの処理結果をデコードしたものがここに入る */
std::vector<char> result;
/* 実行 */
lambda::run_on_integer_sequence(foo.begin(), foo.end(), program, std::back_inserter(result));
/* 結果を文字列として表示 */
for (auto ch : result) {
std::cout << ch;
}
std::cout << std::endl;
}
こちらのプログラムですが、コンパイルには二時間半かかりました。
$ time g++ iota_hello.cpp --std=c++17 && time ./a.out
real 154m21.342s
user 153m46.597s
sys 0m33.498s
Hello, World!
real 3m52.844s
user 3m50.942s
sys 0m1.679s
プログラム自体も、ただの HelloWorld のくせに 3 MB 近くあります。
$ ls -lh a.out
-rwxr-xr-x 1 reika727 reika727 2.8M Mar 22 10:47 a.out
ちょっと深い話
ここからはすこし、いやかなりマニアックなお話です。
0 と 1 による表記
この Iota という言語は実は 0 と 1 だけで記述することができます。
まずこのような文法を考えます。
iota = "0" | "1" iota iota
ここで "0" は $\iota$ 一個に、"1" は 右側のもの二つをまとめる括弧にあたります。といってもわけがわからないと思うので具体例を見てみましょう。"1100100" という文字列から上の文法にしたがって構文木を作るとこのようになります。
1
/ \
1 1
/ \ / \
0 0 0 0
つまり、"1100100" という文字列は $((\iota\iota)(\iota\iota))$ という式に当たるのです。
別の例も見てみましょう。"1010100" はこのような構文木になります。
1
/ \
0 1
/ \
0 1
/ \
0 0
よって、この文字列は $(\iota(\iota(\iota\iota)))$ という式に当たります。
チャーチ・チューリングの提唱
いったん話かわります。
古くから数学の世界にはある一つの問いがありました。それは、そもそも「計算」とはいかなることなのか？という問いです。そこで、この「計算」という行為を厳密に定めようという動きがありました。そして二十世紀ごろ、「計算」という行為のモデル化（計算模型）が立てつづけに考案されました。μ 再帰関数、ラムダ計算、チューリングマシンなどです。この三つは全く別々の人たちにより考案され、しかも一見するとそれぞれが全く違った方法で計算を行うのにもかかわらず、なんとこれらはすべて全く等しい表現能力を持つことが証明されたのです。つまり、これら計算模型のどれか一つで解ける問題は他の計算模型でも解けますし、逆にどれか一つで解けない問題は他のどの計算模型にも解けないことが明らかになったのです。
言い方を変えれば、これらの計算模型を超える能力を持つ計算模型は誰にも思いつけなかったとも言えます。そこで、「『μ 再帰関数で計算できること』を『計算可能である』ことの定義にしちゃっていいんじゃね？」という提案がなされました。これがチャーチ・チューリングの提唱です。
「チャーチ・チューリングの提唱」はあくまでも「提唱」であって「定理」ではないことに注意してください。つまりチャーチ・チューリングの提唱は何者かによって証明された事実ではなく、単なる提案です。
さて Iota の話に戻ってきます。先ほどもお話ししたように $\iota$ はチューリング完全ですから、チャーチ・チューリングの提唱を受け入れるならば Iota は任意のアルゴリズムを記述できることになります。
それに加えて、さきほどお見せしたように任意の Iota プログラムは 0 と 1 のみで表記することが可能です。ここから言えることは、任意のアルゴリズムに対し一意な自然数を割り振ることが可能であるということです。Iota プログラムとして有効な文字列は "0" 一文字のみの文字列か "1" から始まる文字列のみのため、割り振られる自然数がかぶることもありません。
Jot
最後に Iota の姉妹に当たる Jot 言語を軽く紹介します。Jot 言語も Iota 言語と同じく任意のアルゴリズムに自然数を割り振れるのですが、Iota とは違って 0 と 1 からなる任意の文字列（空文字列も含む）が有効なプログラムになります。
0 と 1 からなる文字列 $w$ に対し、$w$ の「翻訳」を $[w]$ と表記することにします。すると Jot 言語はこのように定められます。
\begin{align*}
[] &\rightarrow I \\
[w0] &\rightarrow [w]SK (= \iota [w]) \\
[w1] &\rightarrow S(K[w])
\end{align*}
また、翻訳途中で "1" に遭遇したときにはこのようなショートカットができる場合があります。つまり "1" は直後の項二つをまとめる効果があります。
\begin{align*}
[w1001] &\rightarrow S(K[w100]) \\
&\rightarrow S(K([w10]SK)) \\
&\rightarrow S(K([w\color{red}{1}]\color{blue}{SK}SK)) \\
&\rightarrow S(K([w]\color{blue}{(SK)}SK)) \\
\because S(K([w1]SKSK)) &\rightarrow S(K(S(K[w])SKSK)) \\
&\rightarrow S(K((K[w])K(SK)SK)) \\
&\rightarrow S(K([w](SK)SK)) \\
\end{align*}
この法則を利用すると以下のような公式が成り立ちます。
\begin{align*}
[w11100] &\rightarrow [w111]SKSK \\
&\rightarrow [w](SKSK) \\
&\rightarrow [w]K
\end{align*}
\begin{align*}
[w11111000] &\rightarrow [w11111]SKSKSK \\
&\rightarrow [w](SKSKSK) \\
&\rightarrow [w]S
\end{align*}
先ほども書いたように $S$, $K$ の組み合わせはチューリング完全であり、また上記の法則より $S$, $K$ の組み合わせで表現できる任意の式は必ず 1 から始まる列で表せることになります。したがって、この Jot 言語も Iota 言語と同じく任意のアルゴリズムに自然数を割り振ることができるのです。美しいですね～。
おわりに
計算機科学の世界は本当に摩訶不思議です。一体何を食べてたらこんなこと思いつくんでしょうか・・・
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ギリシャ文字の一種で、「イオタ」と読みます。 ↩