The three approches are:
-* Rethinking the list monad;
-* Montague's PTQ treatment of DPs as generalized quantifiers; and
-* Refunctionalizing zippers (Shan: zippers are defunctionalized continuations);
+[[!toc]]
Rethinking the list monad
-------------------------
To construct a monad, the key element is to settle on a type
-constructor, and the monad naturally follows from that. I'll remind
+constructor, and the monad naturally follows from that. We'll remind
you of some examples of how monads follow from the type constructor in
a moment. This will involve some review of familair material, but
it's worth doing for two reasons: it will set up a pattern for the new
For instance, take the **Reader Monad**. Once we decide that the type
constructor is
- type 'a reader = fun e:env -> 'a
+ type 'a reader = env -> 'a
then we can deduce the unit and the bind:
- runit x:'a -> 'a reader = fun (e:env) -> x
+ let r_unit (x : 'a) : 'a reader = fun (e : env) -> x
-Since the type of an `'a reader` is `fun e:env -> 'a` (by definition),
-the type of the `runit` function is `'a -> e:env -> 'a`, which is a
+Since the type of an `'a reader` is `env -> 'a` (by definition),
+the type of the `r_unit` function is `'a -> env -> 'a`, which is a
specific case of the type of the *K* combinator. So it makes sense
that *K* is the unit for the reader monad.
Since the type of the `bind` operator is required to be
- r_bind:('a reader) -> ('a -> 'b reader) -> ('b reader)
+ r_bind : ('a reader) -> ('a -> 'b reader) -> ('b reader)
We can deduce the correct `bind` function as follows:
- r_bind (u:'a reader) (f:'a -> 'b reader):('b reader) =
+ let r_bind (u : 'a reader) (f : 'a -> 'b reader) : ('b reader) =
We have to open up the `u` box and get out the `'a` object in order to
feed it to `f`. Since `u` is a function from environments to
-objects of type `'a`, we'll have
+objects of type `'a`, the way we open a box in this monad is
+by applying it to an environment:
.... f (u e) ...
This subexpression types to `'b reader`, which is good. The only
-problem is that we don't have an `e`, so we have to abstract over that
-variable:
+problem is that we invented an environment `e` that we didn't already have ,
+so we have to abstract over that variable to balance the books:
fun e -> f (u e) ...
This types to `env -> 'b reader`, but we want to end up with `env ->
-'b`. The easiest way to turn a 'b reader into a 'b is to apply it to
+'b`. Once again, the easiest way to turn a `'b reader` into a `'b` is to apply it to
an environment. So we end up as follows:
- r_bind (u:'a reader) (f:'a -> 'b reader):('b reader) = f (u e) e
+ r_bind (u : 'a reader) (f : 'a -> 'b reader) : ('b reader) = f (u e) e
And we're done.
+[This bind is a condensed version of the careful `let a = u e in ...`
+constructions we provided in earlier lectures. We use the condensed
+version here in order to emphasize similarities of structure across
+monads.]
+
The **State Monad** is similar. We somehow intuit that we want to use
the following type constructor:
- type 'a state = 'store -> ('a, 'store)
+ type 'a state = store -> ('a, store)
So our unit is naturally
- let s_unit (x:'a):('a state) = fun (s:'store) -> (x, s)
+ let s_unit (x : 'a) : ('a state) = fun (s : store) -> (x, s)
And we deduce the bind in a way similar to the reasoning given above.
First, we need to apply `f` to the contents of the `u` box:
- let s_bind (u:'a state) (f:'a -> ('b state)):('b state) =
+ let s_bind (u : 'a state) (f : 'a -> 'b state) : 'b state =
But unlocking the `u` box is a little more complicated. As before, we
need to posit a state `s` that we can apply `u` to. Once we do so,
Abstracting over the `s` and adjusting the types gives the result:
- let s_bind (u:'a state) (f:'a -> ('b state)):('b state) =
- fun (s:state) -> let (a, s') = u s in f a s'
+ let s_bind (u : 'a state) (f : 'a -> 'b state) : 'b state =
+ fun (s : store) -> let (a, s') = u s in f a s'
The **Option Monad** doesn't follow the same pattern so closely, so we
won't pause to explore it here, though conceptually its unit and bind
looks like this:
type 'a list = ['a];;
- l_unit (x:'a) = [x];;
+ l_unit (x : 'a) = [x];;
l_bind u f = List.concat (List.map f u);;
Recall that `List.map` take a function and a list and returns the
But where is the reasoning that led us to this unit and bind?
And what is the type `['a]`? Magic.
-So let's take a *completely useless digressing* and see if we can
-gain some insight into the details of the List monad. Let's choose
-type constructor that we can peer into, using some of the technology
-we built up so laboriously during the first half of the course. I'm
-going to use type 3 lists, partly because I know they'll give the
-result I want, but also because they're my favorite. These were the
-lists that made lists look like Church numerals with extra bits
-embdded in them:
+So let's indulge ourselves in a completely useless digression and see
+if we can gain some insight into the details of the List monad. Let's
+choose type constructor that we can peer into, using some of the
+technology we built up so laboriously during the first half of the
+course. We're going to use type 3 lists, partly because we know
+they'll give the result we want, but also because they're the coolest.
+These were the lists that made lists look like Church numerals with
+extra bits embdded in them:
empty list: fun f z -> z
list with one element: fun f z -> f 1 z
list with two elements: fun f z -> f 2 (f 1 z)
list with three elements: fun f z -> f 3 (f 2 (f 1 z))
-and so on. To save time, we'll let the Ocaml interpreter infer the
+and so on. To save time, we'll let the OCaml interpreter infer the
principle types of these functions (rather than deducing what the
types should be):
Finally, we're getting consistent principle types, so we can stop.
These types should remind you of the simply-typed lambda calculus
types for Church numerals (`(o -> o) -> o -> o`) with one extra bit
-thrown in (in this case, and int).
+thrown in (in this case, an int).
So here's our type constructor for our hand-rolled lists:
So an `('a, 'b) list'` is a list containing elements of type `'a`,
where `'b` is the type of some part of the plumbing. This is more
-general than an ordinary Ocaml list, but we'll see how to map them
-into Ocaml lists soon. We don't need to grasp the role of the `'b`'s
+general than an ordinary OCaml list, but we'll see how to map them
+into OCaml lists soon. We don't need to fully grasp the role of the `'b`'s
in order to proceed to build a monad:
- l'_unit (x:'a):(('a, 'b) list) = fun x -> fun f z -> f x z
+ l'_unit (x : 'a) : ('a, 'b) list = fun x -> fun f z -> f x z
No problem. Arriving at bind is a little more complicated, but
exactly the same principles apply, you just have to be careful and
systematic about it.
- l'_bind (u:('a,'b) list') (f:'a -> ('c, 'd) list'): ('c, 'd) list' = ...
+ l'_bind (u : ('a,'b) list') (f : 'a -> ('c, 'd) list') : ('c, 'd) list' = ...
Unfortunately, we'll need to spell out the types:
- l'_bind (u: ('a -> 'b -> 'b) -> 'b -> 'b)
- (f: 'a -> ('c -> 'd -> 'd) -> 'd -> 'd)
+ l'_bind (u : ('a -> 'b -> 'b) -> 'b -> 'b)
+ (f : 'a -> ('c -> 'd -> 'd) -> 'd -> 'd)
: ('c -> 'd -> 'd) -> 'd -> 'd = ...
It's a rookie mistake to quail before complicated types. You should
argument a function expecting an `'a`. Once that argument is applied
to an object of type `'a`, we'll have what we need. Thus:
- .... u (fun (x:'a) -> ... (f a) ... ) ...
+ .... u (fun (a : 'a) -> ... (f a) ... ) ...
In order for `u` to have the kind of argument it needs, we have to
adjust `(f a)` (which has type `('c -> 'd -> 'd) -> 'd -> 'd`) in
alias `'d` to `'b`, and provide `(f a)` with an argument of type `'c
-> 'b -> 'b`. Thus:
- l'_bind (u: ('a -> 'b -> 'b) -> 'b -> 'b)
- (f: 'a -> ('c -> 'b -> 'b) -> 'b -> 'b)
+ l'_bind (u : ('a -> 'b -> 'b) -> 'b -> 'b)
+ (f : 'a -> ('c -> 'b -> 'b) -> 'b -> 'b)
: ('c -> 'b -> 'b) -> 'b -> 'b =
- .... u (fun (x:'a) -> f a k) ...
+ .... u (fun (a : 'a) -> f a k) ...
-[Excercise: can you arrive at a fully general bind for this type
+[Exercise: can you arrive at a fully general bind for this type
constructor, one that does not collapse `'d`'s with `'b`'s?]
As usual, we have to abstract over `k`, but this time, no further
adjustments are needed:
- l'_bind (u: ('a -> 'b -> 'b) -> 'b -> 'b)
- (f: 'a -> ('c -> 'b -> 'b) -> 'b -> 'b)
+ l'_bind (u : ('a -> 'b -> 'b) -> 'b -> 'b)
+ (f : 'a -> ('c -> 'b -> 'b) -> 'b -> 'b)
: ('c -> 'b -> 'b) -> 'b -> 'b =
- fun (k:'c -> 'b -> 'b) -> u (fun (x:'a) -> f a k)
+ fun (k : 'c -> 'b -> 'b) -> u (fun (a : 'a) -> f a k)
You should carefully check to make sure that this term is consistent
with the typing.
l'_bind (fun f z -> f 1 (f 2 z))
(fun i -> fun f z -> f i (f (i+1) z)) ~~> <fun>
-Sigh. Ocaml won't show us our own list. So we have to choose an `f`
-and a `z` that will turn our hand-crafted lists into standard Ocaml
+Sigh. OCaml won't show us our own list. So we have to choose an `f`
+and a `z` that will turn our hand-crafted lists into standard OCaml
lists, so that they will print out.
-# let cons h t = h :: t;; (* Ocaml is stupid about :: *)
-# l'_bind (fun f z -> f 1 (f 2 z))
- (fun i -> fun f z -> f i (f (i+1) z)) cons [];;
-- : int list = [1; 2; 2; 3]
+ # let cons h t = h :: t;; (* OCaml is stupid about :: *)
+ # l'_bind (fun f z -> f 1 (f 2 z))
+ (fun i -> fun f z -> f i (f (i+1) z)) cons [];;
+ - : int list = [1; 2; 2; 3]
Ta da!
-Just for mnemonic purposes (sneaking in an instance of eta reduction
-to the definition of unit), we can summarize the result as follows:
+To bad this digression, though it ties together various
+elements of the course, has *no relevance whatsoever* to the topic of
+continuations...
+
+Montague's PTQ treatment of DPs as generalized quantifiers
+----------------------------------------------------------
+
+We've hinted that Montague's treatment of DPs as generalized
+quantifiers embodies the spirit of continuations (see de Groote 2001,
+Barker 2002 for lengthy discussion). Let's see why.
+
+First, we'll need a type constructor. As you probably know,
+Montague replaced individual-denoting determiner phrases (with type `e`)
+with generalized quantifiers (with [extensional] type `(e -> t) -> t`.
+In particular, the denotation of a proper name like *John*, which
+might originally denote a object `j` of type `e`, came to denote a
+generalized quantifier `fun pred -> pred j` of type `(e -> t) -> t`.
+Let's write a general function that will map individuals into their
+corresponding generalized quantifier:
+
+ gqize (x : e) = fun (p : e -> t) -> p x
+
+This function wraps up an individual in a fancy box. That is to say,
+we are in the presence of a monad. The type constructor, the unit and
+the bind follow naturally. We've done this enough times that we won't
+belabor the construction of the bind function, the derivation is
+similar to the List monad just given:
+
+ type 'a continuation = ('a -> 'b) -> 'b
+ c_unit (x : 'a) = fun (p : 'a -> 'b) -> p x
+ c_bind (u : ('a -> 'b) -> 'b) (f : 'a -> ('c -> 'd) -> 'd) : ('c -> 'd) -> 'd =
+ fun (k : 'a -> 'b) -> u (fun (x : 'a) -> f x k)
+
+How similar is it to the List monad? Let's examine the type
+constructor and the terms from the list monad derived above:
type ('a, 'b) list' = ('a -> 'b -> 'b) -> 'b -> 'b
- l'_unit x = fun f -> f x
+ l'_unit x = fun f -> f x
l'_bind u f = fun k -> u (fun x -> f x k)
-To bad this digression, though it ties together various
-elements of the course, has *no relevance whatsoever* to the topic of
-continuations.
+(We performed a sneaky but valid eta reduction in the unit term.)
+
+The unit and the bind for the Montague continuation monad and the
+homemade List monad are the same terms! In other words, the behavior
+of the List monad and the behavior of the continuations monad are
+parallel in a deep sense. To emphasize the parallel, we can
+instantiate the type of the list' monad using the OCaml list type:
+
+ type 'a c_list = ('a -> 'a list) -> 'a list
+
+Have we really discovered that lists are secretly continuations? Or
+have we merely found a way of simulating lists using list
+continuations? Both perspectives are valid, and we can use our
+intuitions about the list monad to understand continuations, and vice
+versa (not to mention our intuitions about primitive recursion in
+Church numerals too). The connections will be expecially relevant
+when we consider indefinites and Hamblin semantics on the linguistic
+side, and non-determinism on the list monad side.
+
+Refunctionalizing zippers
+-------------------------
+
+Manipulating trees with monads
+------------------------------
+
+This thread develops an idea based on a detailed suggestion of Ken
+Shan's. We'll build a series of functions that operate on trees,
+doing various things, including replacing leaves, counting nodes, and
+converting a tree to a list of leaves. The end result will be an
+application for continuations.
+
+From an engineering standpoint, we'll build a tree transformer that
+deals in monads. We can modify the behavior of the system by swapping
+one monad for another. (We've already seen how adding a monad can add
+a layer of funtionality without disturbing the underlying system, for
+instance, in the way that the reader monad allowed us to add a layer
+of intensionality to an extensional grammar, but we have not yet seen
+the utility of replacing one monad with other.)
+
+First, we'll be needing a lot of trees during the remainder of the
+course. Here's a type constructor for binary trees:
+
+ type 'a tree = Leaf of 'a | Node of ('a tree * 'a tree)
+
+These are trees in which the internal nodes do not have labels. [How
+would you adjust the type constructor to allow for labels on the
+internal nodes?]
+
+We'll be using trees where the nodes are integers, e.g.,
+
+
+<pre>
+let t1 = Node ((Node ((Leaf 2), (Leaf 3))),
+ (Node ((Leaf 5),(Node ((Leaf 7),
+ (Leaf 11))))))
+
+ .
+ ___|___
+ | |
+ . .
+_|__ _|__
+| | | |
+2 3 5 .
+ _|__
+ | |
+ 7 11
+</pre>
+
+Our first task will be to replace each leaf with its double:
+
+<pre>
+let rec treemap (newleaf:'a -> 'b) (t:'a tree):('b tree) =
+ match t with Leaf x -> Leaf (newleaf x)
+ | Node (l, r) -> Node ((treemap newleaf l),
+ (treemap newleaf r));;
+</pre>
+`treemap` takes a function that transforms old leaves into new leaves,
+and maps that function over all the leaves in the tree, leaving the
+structure of the tree unchanged. For instance:
+
+<pre>
+let double i = i + i;;
+treemap double t1;;
+- : int tree =
+Node (Node (Leaf 4, Leaf 6), Node (Leaf 10, Node (Leaf 14, Leaf 22)))
+
+ .
+ ___|____
+ | |
+ . .
+_|__ __|__
+| | | |
+4 6 10 .
+ __|___
+ | |
+ 14 22
+</pre>
+
+We could have built the doubling operation right into the `treemap`
+code. However, because what to do to each leaf is a parameter, we can
+decide to do something else to the leaves without needing to rewrite
+`treemap`. For instance, we can easily square each leaf instead by
+supplying the appropriate `int -> int` operation in place of `double`:
+
+<pre>
+let square x = x * x;;
+treemap square t1;;
+- : int tree =ppp
+Node (Node (Leaf 4, Leaf 9), Node (Leaf 25, Node (Leaf 49, Leaf 121)))
+</pre>
+
+Note that what `treemap` does is take some global, contextual
+information---what to do to each leaf---and supplies that information
+to each subpart of the computation. In other words, `treemap` has the
+behavior of a reader monad. Let's make that explicit.
+
+In general, we're on a journey of making our treemap function more and
+more flexible. So the next step---combining the tree transducer with
+a reader monad---is to have the treemap function return a (monadized)
+tree that is ready to accept any `int->int` function and produce the
+updated tree.
+
+\tree (. (. (f2) (f3))(. (f5) (.(f7)(f11))))
+<pre>
+\f .
+ ____|____
+ | |
+ . .
+__|__ __|__
+| | | |
+f2 f3 f5 .
+ __|___
+ | |
+ f7 f11
+</pre>
+
+That is, we want to transform the ordinary tree `t1` (of type `int
+tree`) into a reader object of type `(int->int)-> int tree`: something
+that, when you apply it to an `int->int` function returns an `int
+tree` in which each leaf `x` has been replaced with `(f x)`.
+
+With previous readers, we always knew which kind of environment to
+expect: either an assignment function (the original calculator
+simulation), a world (the intensionality monad), an integer (the
+Jacobson-inspired link monad), etc. In this situation, it will be
+enough for now to expect that our reader will expect a function of
+type `int->int`.
+
+<pre>
+type 'a reader = (int->int) -> 'a;; (* mnemonic: e for environment *)
+let reader_unit (x:'a): 'a reader = fun _ -> x;;
+let reader_bind (u: 'a reader) (f:'a -> 'c reader):'c reader = fun e -> f (u e) e;;
+</pre>
+
+It's easy to figure out how to turn an `int` into an `int reader`:
+
+<pre>
+let int2int_reader (x:'a): 'b reader = fun (op:'a -> 'b) -> op x;;
+int2int_reader 2 (fun i -> i + i);;
+- : int = 4
+</pre>
+
+But what do we do when the integers are scattered over the leaves of a
+tree? A binary tree is not the kind of thing that we can apply a
+function of type `int->int` to.
+
+<pre>
+let rec treemonadizer (f:'a -> 'b reader) (t:'a tree):('b tree) reader =
+ match t with Leaf x -> reader_bind (f x) (fun x' -> reader_unit (Leaf x'))
+ | Node (l, r) -> reader_bind (treemonadizer f l) (fun x ->
+ reader_bind (treemonadizer f r) (fun y ->
+ reader_unit (Node (x, y))));;
+</pre>
+
+This function says: give me a function `f` that knows how to turn
+something of type `'a` into an `'b reader`, and I'll show you how to
+turn an `'a tree` into an `'a tree reader`. In more fanciful terms,
+the `treemonadizer` function builds plumbing that connects all of the
+leaves of a tree into one connected monadic network; it threads the
+monad through the leaves.
+
+<pre>
+# treemonadizer int2int_reader t1 (fun i -> i + i);;
+- : int tree =
+Node (Node (Leaf 4, Leaf 6), Node (Leaf 10, Node (Leaf 14, Leaf 22)))
+</pre>
+
+Here, our environment is the doubling function (`fun i -> i + i`). If
+we apply the very same `int tree reader` (namely, `treemonadizer
+int2int_reader t1`) to a different `int->int` function---say, the
+squaring function, `fun i -> i * i`---we get an entirely different
+result:
+
+<pre>
+# treemonadizer int2int_reader t1 (fun i -> i * i);;
+- : int tree =
+Node (Node (Leaf 4, Leaf 9), Node (Leaf 25, Node (Leaf 49, Leaf 121)))
+</pre>
+
+Now that we have a tree transducer that accepts a monad as a
+parameter, we can see what it would take to swap in a different monad.
+For instance, we can use a state monad to count the number of nodes in
+the tree.
+
+<pre>
+type 'a state = int -> 'a * int;;
+let state_unit x i = (x, i+.5);;
+let state_bind u f i = let (a, i') = u i in f a (i'+.5);;
+</pre>
+
+Gratifyingly, we can use the `treemonadizer` function without any
+modification whatsoever, except for replacing the (parametric) type
+`reader` with `state`:
+
+<pre>
+let rec treemonadizer (f:'a -> 'b state) (t:'a tree):('b tree) state =
+ match t with Leaf x -> state_bind (f x) (fun x' -> state_unit (Leaf x'))
+ | Node (l, r) -> state_bind (treemonadizer f l) (fun x ->
+ state_bind (treemonadizer f r) (fun y ->
+ state_unit (Node (x, y))));;
+</pre>
+
+Then we can count the number of nodes in the tree:
+
+<pre>
+# treemonadizer state_unit t1 0;;
+- : int tree * int =
+(Node (Node (Leaf 2, Leaf 3), Node (Leaf 5, Node (Leaf 7, Leaf 11))), 13)
+
+ .
+ ___|___
+ | |
+ . .
+_|__ _|__
+| | | |
+2 3 5 .
+ _|__
+ | |
+ 7 11
+</pre>
+
+Notice that we've counted each internal node twice---it's a good
+excerice to adjust the code to count each node once.
+
+One more revealing example before getting down to business: replacing
+`state` everywhere in `treemonadizer` with `list` gives us
+
+<pre>
+# treemonadizer (fun x -> [[x; square x]]) t1;;
+- : int list tree list =
+[Node
+ (Node (Leaf [2; 4], Leaf [3; 9]),
+ Node (Leaf [5; 25], Node (Leaf [7; 49], Leaf [11; 121])))]
+</pre>
+
+Unlike the previous cases, instead of turning a tree into a function
+from some input to a result, this transformer replaces each `int` with
+a list of `int`'s.
+
+Now for the main point. What if we wanted to convert a tree to a list
+of leaves?
+
+<pre>
+type ('a, 'r) continuation = ('a -> 'r) -> 'r;;
+let continuation_unit x c = c x;;
+let continuation_bind u f c = u (fun a -> f a c);;
+
+let rec treemonadizer (f:'a -> ('b, 'r) continuation) (t:'a tree):(('b tree), 'r) continuation =
+ match t with Leaf x -> continuation_bind (f x) (fun x' -> continuation_unit (Leaf x'))
+ | Node (l, r) -> continuation_bind (treemonadizer f l) (fun x ->
+ continuation_bind (treemonadizer f r) (fun y ->
+ continuation_unit (Node (x, y))));;
+</pre>
+
+We use the continuation monad described above, and insert the
+`continuation` type in the appropriate place in the `treemonadizer` code.
+We then compute:
+
+<pre>
+# treemonadizer (fun a c -> a :: (c a)) t1 (fun t -> []);;
+- : int list = [2; 3; 5; 7; 11]
+</pre>
+
+We have found a way of collapsing a tree into a list of its leaves.
+
+The continuation monad is amazingly flexible; we can use it to
+simulate some of the computations performed above. To see how, first
+note that an interestingly uninteresting thing happens if we use the
+continuation unit as our first argument to `treemonadizer`, and then
+apply the result to the identity function:
+
+<pre>
+# treemonadizer continuation_unit t1 (fun x -> x);;
+- : int tree =
+Node (Node (Leaf 2, Leaf 3), Node (Leaf 5, Node (Leaf 7, Leaf 11)))
+</pre>
+
+That is, nothing happens. But we can begin to substitute more
+interesting functions for the first argument of `treemonadizer`:
+
+<pre>
+(* Simulating the tree reader: distributing a operation over the leaves *)
+# treemonadizer (fun a c -> c (square a)) t1 (fun x -> x);;
+- : int tree =
+Node (Node (Leaf 4, Leaf 9), Node (Leaf 25, Node (Leaf 49, Leaf 121)))
+
+(* Simulating the int list tree list *)
+# treemonadizer (fun a c -> c [a; square a]) t1 (fun x -> x);;
+- : int list tree =
+Node
+ (Node (Leaf [2; 4], Leaf [3; 9]),
+ Node (Leaf [5; 25], Node (Leaf [7; 49], Leaf [11; 121])))
+
+(* Counting leaves *)
+# treemonadizer (fun a c -> 1 + c a) t1 (fun x -> 0);;
+- : int = 5
+</pre>
+
+We could simulate the tree state example too, but it would require
+generalizing the type of the continuation monad to
+
+ type ('a -> 'b -> 'c) continuation = ('a -> 'b) -> 'c;;