## 2014-06-29

### Implicit value lifting

Jakub Marian's notation without variables has a definition I call “the fork rule”:
$(f\star g)\ x = f\ x\star g\ x$It is also made clear that if either $f$ or $g$ is a constant, the constant should be preserved. For instance, the following has to hold:
$({\large\iota}+1)\ 2 = {\large\iota}\ 2+1\ 2 = 2 + 1 = 3$where $\large\iota$ is the identity function. Obviously, the thing we need to sort out is $1\ 2=1$.

My first idea was that all constants should be turned into constant functions. Essentially, “1” becomes a function that always yields the value 1 (but not the function 1). However, I realised that this was unsatisfactory. Of minor importance was the fact that it felt weird to never have access to the underlying object. But the main point is that I want to generalise the ideas of constants and constant functions to elements and single-element sets. If every constant were a function, it would also need to be a set, and a zip list, and every other similar structure we want to use. There would have to be some order to the wrapping of all of these structures, but there is no natural order.

So instead I say this: values can be implicitly lifted when applied to a function that expects an applicative functor. As an introduction, the applicative functor $f : \text{Type} \rightarrow \text{Type}$ has definitions for these functions:
\begin{aligned} \text{fmap}\ &: (a\rightarrow b)\rightarrow f\ a\rightarrow f\ b \\ \text{pure}\ &: a\rightarrow f\ a \\ {<}{\ast}{>}\ &: f\ (a\rightarrow b)\rightarrow f\ a\rightarrow f\ b \end{aligned}So $f$ acts like a wrapper on other types, an idea played on by this functor/applicative/monad introduction. We won't need monads here (yet), but they are related.

For this post, we're only interested in $\text{pure}$. For $\text{Set}$, $\text{pure}\ a = \{a\}$, and for types $(t\rightarrow)$ (functions from arbitrary type $t$), $\text{pure}\ a = \lambda x.a$. So there we have our singleton set and constant function connected. (Note for functional programmers: sets are indeed functors in maths, since any things of the same type in maths can be equated. Mathematicians don't care for such worthless notions as computability.)

To address $1\ 2 = 1$, we'll write it out with an explicit application operator, . So, we consider $1\mathbin2$.  has type $(a\rightarrow b)\rightarrow a\rightarrow b$, so we're hoping that $1$ fits $a\rightarrow b$ and $2$ fits $a$. $2$ does indeed fit $a$ (anything does), so we need $1$ to fit $\mathbb{R}\rightarrow b$. It doesn't. But it does fit $b$, and $(\mathbb{R}\rightarrow)$ is an applicative functor. So we transform $1\mathbin2$ into $\text{pure}\ 1\mathbin2$, which is $(\lambda x.1)\ 2$, which is $1$. Yay!

So we can now use constants where functions were wanted, elements where sets were wanted and values where maybes were wanted. That seems enough for this post.