an order-independent analysis of order of evaluation.
In order to continue to explore continuations, we will proceed in the
-followin fashion.
+following fashion: we introduce the traditional continuation monad,
+and show how it solves the task, then generalize the task to
+include doubling of both the left and the right context.
## The continuation monad
-Let's take a look at some of our favorite monads from the point of
-view of types. Here, `==>` is the Kleisli arrow.
-
- Reader monad: types: Mα ==> β -> α
- ⇧: \ae.a : α -> Mα
- compose: \fghe.f(ghe)e : (Q->MR)->(P->MQ)->(P->MR)
- gloss: copy environment and distribute it to f and g
-
- State monad: types: α ==> β -> (α x β)
- ⇧: \ae.(a,e) : α -> Mα
- compose: \fghe.let (x,s) = ghe in fxs
- thread the state through g, then through f
-
- List monad: types: α ==> [α]
- ⇧: \a.[a] : α -> Mα
- compose: \fgh.concat(map f (gh))
- gloss: compose f and g pointwise
-
- Maybe monad: types: α ==> Nothing | Just α
- ⇧: \a. Just a
- compose: \fgh.
- case gh of Nothing -> Nothing
- | Just x -> case fx of Nothing -> Nothing
- | Just y -> Just y
- gloss: strong Kline
-
-Now we need a type for a continuation. A continuized term is one that
-expects its continuation as an argument. The continuation of a term
-is a function from the normal value of that term to a result. So if
-the term has type continuized term has type α, the continuized version
-has type (α -> ρ) -> ρ:
-
- Continuation monad: types: Mα => (α -> ρ) -> ρ
- ⇧: \ak.ka
- compose: \fghk.f(\f'.g h (\g'.f(g'h)
- gloss: first give the continuation to f, then build
- a continuation out of the result to give to
-
-The first thing we should do is demonstrate that this monad is
-suitable for accomplishing the task.
-
-We lift the computation `("a" ++ ("b" ++ ("c" ++ "d")))` into
-the monad as follows:
-
- t1 = (map1 ((++) "a") (map1 ((++) "b") (map1 ((++) "c") (mid "d"))))
-
-Here, `(++) "a"` is a function of type [Char] -> [Char] that prepends
-the string "a", so `map1 ((++) "a")` takes a string continuation k and
-returns a new string continuation that takes a string s returns "a" ++ k(s).
-So `t1 (\k->k) == "abcd"`.
+In order to build a monad, we start with a Kleisli arrow.
+
+ Continuation monad: types: given some ρ, Mα => (α -> ρ) -> ρ
+ ⇧ == \ak.ka : a -> Ma
+ bind == \ufk. u(\x.fxk)
+
+We'll first show that this monad solves the task, then we'll consider
+the monad in more detail.
+
+The unmonadized computation (without the shifty "S" operator) is
+
+ t1 = + a (+ b (+ c d)) ~~> abcd
+
+where "+" is string concatenation and the symbol a is shorthand for
+the string "a".
+
+In order to use the continuation monad to solve the list task,
+we choose α = ρ = [Char]. So "abcd" is a list of characters, and
+a boxed list has type M[Char] == ([Char] -> [Char]) -> [Char].
+
+Writing ¢ in between its arguments, t1 corresponds to the following
+monadic computation:
+
+ mt1 = ⇧+ ¢ ⇧a ¢ (⇧+ ¢ ⇧b ¢ (⇧+ ¢ ⇧c ¢ ⇧d))
+
+We have to lift each functor (+) and each object (e.g., "b") into the
+monad using mid (`⇧`), then combine them using monadic function
+application, where
+
+ ¢ M N = \k -> M (\f -> N (\a -> k(f x)))
+
+for the continuation monad.
+
+The way in which we extract a value from a continuation box is by
+applying it to a continuation; often, it is convenient to supply the
+trivial continuation, the identity function \k.k = I. So in fact,
+
+ t1 = mt1 I
+
+That is, the original computation is the monadic version applied to
+the trivial continuation.
+
+We can now add a shifty operator. We would like to replace just the
+one element, and we will do just that in a moment; but in order to
+simulate the original task, we'll have to take a different strategy
+initially. We'll start by imagining a shift operator that combined
+direction with the tail of the list, like this:
+
+ mt2 = ⇧+ ¢ ⇧a ¢ (⇧+ ¢ ⇧b ¢ (shift ¢ ⇧d))
We can now define a shift operator to perform the work of "S":
shift u k = u(\s.k(ks))
-Shift takes two arguments: a string continuation u of type (String -> String) -> String,
-and a string continuation k of type String -> String. Since u is the
-result returned by the argument to shift, it represents the tail of
-the list after the shift operator. Then k is the continuation of the
-expression headed by `shift`. So in order to execute the task, shift
-needs to invoke k twice.
+Shift takes two arguments: a string continuation u of type M[Char],
+and a string continuation k of type [Char] -> [Char]. Since u is the
+the argument to shift, it represents the tail of the list after the
+shift operator. Then k is the continuation of the expression headed
+by `shift`. So in order to execute the task, shift needs to invoke k
+twice. The expression `\s.k(ks)` is just the composition of k with itself.
-Note that the shift operator constructs a new continuation by
-composing its second argument with itself (i.e., the new doubled
-continuation is \s.k(ks)). Once it has constructed this
-new continuation, it delivers it as an argument to the remaining part
-of the computation!
+ mt2 I == "ababd"
- (map1 ((++) "a") (map1 ((++) "b") (shift (mid "d")))) (\k->k) == "ababd"
+just as desired.
Let's just make sure that we have the left-to-right evaluation we were
hoping for by evaluating "abSdeSf":
- t6 = map1 ((++) "a")
- (map1 ((++) "b")
- (shift
- (map1 ((++) "d")
- (map1 ((++) "e")
- (shift (mid "f"))))))
+ mt3 = ⇧+ ¢ ⇧a ¢ (⇧+ ¢ ⇧b ¢ (shift ¢ (⇧+ ¢ ⇧d ¢ (⇧+ ¢ ⇧e ¢ (shift ⇧f)))))
+
+Then
- t6 (\k->k) == "ababdeababdef"
+ mt3 I = "ababdeababdef" -- structure: (ababde)(ababde)f
+
As expected.
-In order to add a reset operator #, we can have
+For a reset operator #, we can have
- # u k = k(u(\k.k))
- ab#deSf ~~> abdedef
+ # u k = k(u(\k.k)) -- ex.: ab#deSf ~~> abdedef
-Note that the lifting of the original unmonadized computation treated
-prepending "a" as a one-place operation. If we decompose this
-operation into a two-place operation of appending combined with a
-string "a", an interesting thing happens.
+The reset operator executes the remainder of the list separately, by
+giving it the trivial continuation (\k.k), then feeds the result to
+the continuation corresponding to the position of the reset.
+So the continuation monad solves the list task using continuations in
+a way that conforms to our by-now familiar strategy of lifting a
+computation into a monad, and then writing a few key functions (shift,
+reset) that exploit the power of the monad.
- map2 f u v k = u(\u' -> v (\v' -> k(f u' v')))
- shift k = k (k "")
+## Generalizing to the tree doubling task
- t2 = map2 (++) (mid "a")
- (map2 (++) (mid "b")
- (map2 (++) shift
- (map2 (++) (mid "d")
- (mid []))))
- t2 (\k->k) == "ababdd"
-
-First, we need map2 instead of map1. Second, the type of the shift
-operator will be a string continuation, rather than a function from
-string continuations to string continuations.
-
-But here's the interesting part: from the point of view of the shift
-operator, the continuation that it will be fed will be the entire rest
-of the computation. This includes not only what has come before, but
-what will come after it as well. That means when the continuation is
-doubled (self-composed), the result duplicates not only the prefix
-`(ab ~~> abab)`, but also the suffix `(d ~~> dd)`. In some sense, then,
-continuations allow functions to see into the future!
-
-What do you expect will be the result of executing "aScSe" under the
-second perspective? The answer to this question is not determined by
-the informal specification of the task that we've been using, since
-under the new perspective, we're copying complete (bi-directional)
-contexts rather than just left contexts.
-
-It might be natural to assume that what execution does is choose an S,
-and double its context, temporarily treating all other shift operators
-as dumb letters, then choosing a remaining S to execute. If that was
-our interpreation of the task, then no string with more than one S
-would ever terminate, since the number S's after each reduction step
-would always be 2(n-1), where n is the number before reduction.
-
-But there is another equally natural way to answer the question.
-Assume the leftmost S is executed first. What will the value of its
-continuation k be? It will be a function that maps a string s to the
-result of computing `ascSe`, which will be `ascascee`. So `k(k "")`
-will be `k(acacee)`, which will result in `a(acacee)ca(acacee)cee`
-(the parentheses are added to show stages in the construction of the
-final result).
-
-So the continuation monad behaves in a way that we expect a
-continuation to behave. But where did the continuation monad come
-from? Let's consider some ways of deriving the continuation monad.
+Now we should consider what happens when we write a shift operator
+that takes the place of a single letter.
+
+ mt2 = ⇧+ ¢ ⇧a ¢ (⇧+ ¢ ⇧b ¢ (shift ¢ ⇧d))
+ mt4 = ⇧+ ¢ ⇧a ¢ (⇧+ ¢ ⇧b ¢ (⇧+ ¢ shift' ¢ ⇧d))
+
+Instead of mt2 (copied from above), we have mt4. So now the type of a
+leaf (a boxed string, type M[Char]) is the same as the type of the new
+shift operator, shift'.
+
+ shift' = \k.k(k"")
+
+This shift operator takes a continuation k of type [Char]->[Char], and
+invokes it twice. Since k requires an argument of type [Char], we
+need to use the first invocation of k to construction a [Char]; we do
+this by feeding it a string. Since the task does not replace the
+shift operator with any marker, we give the empty string "" as the
+argument.
+
+But now the new shift operator captures more than just the preceeding
+part of the construction---it captures the entire context, including
+the portion of the sequence that follows it. That is,
+
+ mt4 I = "ababdd"
+
+We have replaced "S" in "abSd" with "ab_d", where the underbar will be
+replaced with the empty string supplied in the definition of shift'.
+Crucially, not only is the prefix "ab" duplicated, so is the suffix
+"d".
+
+Things get interesting when we have more than one operator in the
+initial list. What should we expect if we start with "aScSe"?
+If we assume that when we evaluate each S, all the other S's become
+temporarily inert, we expect a reduction path like
+
+ aScSe ~~> aacSecSe
+
+But note that the output has just as many S's as the input--if that is
+what our reduction strategy delivers, then any initial string with
+more than one S will never reach a normal form.
+
+But that's not what the continuation operator shift' delivers.
+
+ mt5 = ⇧+ ¢ ⇧a ¢ (⇧+ ¢ shift' ¢ (⇧+ ¢ ⇧c ¢ (⇧+ ¢ shift' ¢ "e")))
+
+ mt5 I = "aacaceecaacaceecee" -- structure: "aacaceecaacaceecee"
+
+Huh?
+
+This is considerably harder to understand than the original list task.
+The key is figuring out in each case what function the argument k to
+the shift operator gets bound to.
+
+Let's go back to a simple one-shift example, "aSc". Let's trace what
+the shift' operator sees as its argument k by replacing ⇧ and ¢ with
+their definitions:
+
+<pre>
+ ⇧+ ¢ ⇧a ¢ (⇧+ ¢ shift' ¢ ⇧c) I
+ = \k.⇧+(\f.⇧a(\x.k(fx))) ¢ (⇧+ ¢ shift' ¢ ⇧c) I
+ = \k.(\k.⇧+(\f.⇧a(\x.k(fx))))(\f.(⇧+ ¢ shift' ¢ ⇧c)(\x.k(fx))) I
+ ~~> (\k.⇧+(\f.⇧a(\x.k(fx))))(\f.(⇧+ ¢ shift' ¢ ⇧c)(\x.I(fx)))
+ ~~> (\k.⇧+(\f.⇧a(\x.k(fx))))(\f.(⇧+ ¢ shift' ¢ ⇧c)(f))
+ ~~> ⇧+(\f.⇧a(\x.(\f.(⇧+ ¢ shift' ¢ ⇧c)(f))(fx))))
+ ~~> ⇧+(\f.⇧a(\x.(⇧+ ¢ shift' ¢ ⇧c)(fx)))
+ = (\k.k+)(\f.⇧a(\x.(⇧+ ¢ shift' ¢ ⇧c)(fx)))
+ ~~> ⇧a(\x.(⇧+ ¢ shift' ¢ ⇧c)(+x))
+ = (\k.ka)(\x.(⇧+ ¢ shift' ¢ ⇧c)(+x))
+ ~~> (⇧+ ¢ shift' ¢ ⇧c)(+a)
+ = (\k.⇧+(\f.shift(\x.k(fx)))) ¢ ⇧c (+a)
+ = (\k.(\k.⇧+(\f.shift(\x.k(fx))))(\f.⇧c(\x.k(fx))))(+a)
+ ~~> (\k.⇧+(\f.shift(\x.k(fx))))(\f'.⇧c(\x'.(+a)(f'x')))
+ ~~> ⇧+(\f.shift(\x.(\f'.⇧c(\x'.(+a)(f'x')))(fx)))
+ ~~> ⇧+(\f.shift(\x.⇧c(\x'.(+a)((fx)x'))))
+ = (\k.k+)(\f.shift(\x.⇧c(\x'.(+a)((fx)x'))))
+ ~~> shift(\x.⇧c(\x'.(+a)((+x)x'))))
+ = shift(\x.(\k.kc)(\x'.(+a)((+x)x'))))
+ ~~> shift(\x.(+a)((+x)c))
+</pre>
+
+So now we see what the argument of shift will be: a function k from
+strings x to the string asc. So shift k will be k(k "") = aacc.
+
+Ok, this is ridiculous. We need a way to get ahead of this deluge of
+lambda conversion. We'll see how to understand what is going on
+when we talk about quantifier raising in the next lecture.
## Viewing Montague's PTQ as CPS
quantifier corresponding to the proper name *John* is the quantifier
`\k.kj`.
-At this point, we have a type for our Kliesli arrow and a value for
-our mid. Given some result type (such as `t` in the Montague application),
-
- α ==> (α -> ρ) -> ρ
- ⇧a = \k.ka
-
-It remains only to find a suitable value for bind. Montague didn't
-provide one, but it's easy to find:
-
- bind :: Mα -> (α -> Mβ) -> Mβ
-
-given variables of the following types
-
- u :: Mα == (α -> ρ) -> ρ
- f :: α -> Mβ
- k :: β -> ρ
- x :: α
-
-We have
-
- bind u f = \k.u(\x.fxk)
-
-Let's carefully make sure that this types out:
-
- bind u f = \k. u (\x . f x k)
- -------- --
- α -> Mβ α
- ------------ ------
- Mβ β -> ρ
- -- --------------------
- α ρ
- ------------- ------------------------
- (α -> ρ) -> ρ α -> ρ
- ---------------------------------
- ρ
- -----------------------
- (β -> ρ) -> ρ
-
-Yep!
-
-Is there any other way of building a bind operator? Well, the
-challenge is getting hold of the "a" that is buried inside of `u`.
-In the Reader monad, we could get at the a inside of the box by
-applying the box to an environment. In the State monad, we could get
-at the a by applying to box to a state and deconstructing the
-resulting pair. In the continuation case, the only way to do it is to
-apply the boxed a (i.e., u) to a function that takes an a as an
-argument. That means that f must be invoked inside the scope of the
-functional argument to u. So we've deduced the structure
-
- ... u (\x. ... f x ...) ...
-
-At this point, in order to provide u with an argument of the
-appropriate type, the argument must not only take objects of type
-α as an argument, it must return a result of type ρ. That means that
-we must apply fx to an object of type β -> ρ. We can hypothesize such
-an object, as long as we eliminate that hypothesis later (by binding
-it), and we have the complete bind operation.
-
-The way in which the value of type α that is needed in order to unlock
-the function f is hidden inside of u is directly analogous to the
-concept of "data hiding" in object-oriented programming. See Pierce's
-discussion of how to extend system F with existential type
-quantification by encoding the existential using continuations.
-
-So the Kliesli type pretty much determines the bind operation.
-
-## What continuations are doing
-
-Ok, we have a continuation monad. We derived it from first
-principles, and we have seen that it behaves at least in some respects
-as we expect a continuation monad to behave (in that it allows us to
-give a good implementation of the task).
-
## How continuations can simulate other monads
Because the continuation monad allows the result type ρ to be any
Super cool.
-
-
-
-## Delimited versus undelimited continuations
-
-## Natural language requries delimited continuations
-
-
-
-
-
-