从柯里-霍华德同构中产生的最有趣的等价物是什么？

function composition      | syllogism

I really like this question. I don't know a whole lot, but I do have a few things (assisted by the Wikipedia article, which has some neat tables and such itself):

1. I think that sum types/union types (e.g. data Either a b = Left a | Right b) are equivalent to inclusive disjunction. And, though I'm not very well acquainted with Curry-Howard, I think this demonstrates it. Consider the following function:

   andImpliesOr :: (a,b) -> Either a b
   andImpliesOr (a,_) = Left a
   

   If I understand things correctly, the type says that (a ∧ b) → (a ★ b) and the definition says that this is true, where ★ is either inclusive or exclusive or, whichever Either represents. You have Either representing exclusive or, ⊕; however, (a ∧ b) ↛ (a ⊕ b). For instance, ⊤ ∧ ⊤ ≡ ⊤, but ⊤ ⊕ ⊥ ≡ ⊥, and ⊤ ↛ ⊥. In other words, if both a and b are true, then the hypothesis is true but the conclusion is false, and so this implication must be false. However, clearly, (a ∧ b) → (a ∨ b), since if both a and b are true, then at least one is true. Thus, if discriminated unions are some form of disjunction, they must be the inclusive variety. I think this holds as a proof, but feel more than free to disabuse me of this notion.

2. Similarly, your definitions for tautology and absurdity as the identity function and non-terminating functions, respectively, are a bit off. The true formula is represented by the unit type, which is the type which has only one element (data ⊤ = ⊤; often spelled () and/or Unit in functional programming languages). This makes sense: since that type is guaranteed to be inhabited, and since there's only one possible inhabitant, it must be true. The identity function just represents the particular tautology that a → a.

   Your comment about non-terminating functions is, depending on what precisely you meant, more off. Curry-Howard functions on the type system, but non-termination is not encoded there. According to Wikipedia, dealing with non-termination is an issue, as adding it produces inconsistent logics (e.g., I can define wrong :: a -> b by wrong x = wrong x, and thus “prove” that a → b for any a and b). If this is what you meant by “absurdity”, then you're exactly correct. If instead you meant the false statement, then what you want instead is any uninhabited type, e.g. something defined by data ⊥—that is, a data type without any way to construct it. This ensures that it has no values at all, and so it must be uninhabited, which is equivalent to false. I think you could probably also use a -> b, since if we forbid non-terminating functions, then this is also uninhabited, but I'm not 100% sure.

3. Wikipedia says that axioms are encoded in two different ways, depending on how you interpret Curry-Howard: either in the combinators or in the variables. I think the combinator view means that the primitive functions we are given encode the things we can say by default (similar to the way that modus ponens is an axiom because function application is primitive). And I think that the variable view may actually mean the same thing—combinators, after all, are just global variables which are particular functions. As for primitive types: if I'm thinking about this correctly, then I think that primitive types are the entities—the primitive objects that we're trying to prove things about.

4. According to my logic and semantics class, the fact that (a ∧ b) → c ≡ a → (b → c) (and also that b → (a → c)) is called the exportation equivalence law, at least in natural deduction proofs. I didn't notice at the time that it was just currying—I wish I had, because that's cool!

5. While we now have a way to represent inclusive disjunction, we don't have a way to represent the exclusive variety. We should be able to use the definition of exclusive disjunction to represent it: a ⊕ b ≡ (a ∨ b) ∧ ¬(a ∧ b). I don't know how to write negation, but I do know that ¬p ≡ p → ⊥, and both implication and falsehood are easy. We should thus able to represent exclusive disjunction by:

   data ⊥
   data Xor a b = Xor (Either a b) ((a,b) -> ⊥)
   

   This defines ⊥ to be the empty type with no values, which corresponds to falsity; Xor is then defined to contain both (and) Either an a or a b (or) and a function (implication) from (a,b) (and) to the bottom type (Xor1). Xor2 (Xor3 Now I do, see the next paragraph!) Xor4 (Xor3 Yes, Xor6.)

   Edit 1: Thanks to a5 (more particularly, the comments he left on it to help me out), I think I see what's going on here. To construct a value of type Xor a b, you need to provide two things. First, a witness to the existence of an element of either a or b as the first argument; that is, a Left a or a Right b. And second, a proof that there are not elements of both types a and b—in other words, a proof that (a,b) is uninhabited—as the second argument. Since you'll only be able to write a function from (a,b) -> ⊥ if (a,b) is uninhabited, what does it mean for that to be the case? That would mean that some part of an object of type (a,b) could not be constructed; in other words, that at least one, and possibly both, of a and b are uninhabited as well! In this case, if we're thinking about pattern matching, you couldn't possibly pattern-match on such a tuple: supposing that b is uninhabited, what would we write that could match the second part of that tuple? Thus, we cannot pattern match against it, which may help you see why this makes it uninhabited. Now, the only way to have a total function which takes no arguments (as this one must, since (a,b) is uninhabited) is for the result to be of an uninhabited type too—if we're thinking about this from a pattern-matching perspective, this means that even though the function has no cases, there's no possible a6 it could have either, and so everything's OK.

A lot of this is me thinking aloud/proving (hopefully) things on the fly, but I hope it's useful. I really recommend the Wikipedia article; I haven't read through it in any sort of detail, but its tables are a really nice summary, and it's very thorough.

You're muddying things a little bit regarding nontermination. Falsity is represented by uninhabited types, which by definition can't be non-terminating because there's nothing of that type to evaluate in the first place.

Non-termination represents contradiction--an inconsistent logic. An inconsistent logic will of course allow you to prove anything, including falsity, however.

Ignoring inconsistencies, type systems typically correspond to an intuitionistic logic, and are by necessity constructivist, which means certain pieces of classical logic can't be expressed directly, if at all. On the other hand this is useful, because if a type is a valid constructive proof, then a term of that type is a means of constructing whatever you've proven the existence of.

A major feature of the constructivist flavor is that double negation is not equivalent to non-negation. In fact, negation is rarely a primitive in a type system, so instead we can represent it as implying falsehood, e.g., not P becomes P -> Falsity. Double negation would thus be a function with type (P -> Falsity) -> Falsity, which clearly is not equivalent to something of just type P.

However, there's an interesting twist on this! In a language with parametric polymorphism, type variables range over all possible types, including uninhabited ones, so a fully polymorphic type such as ∀a. a is, in some sense, almost-false. So what if we write double almost-negation by using polymorphism? We get a type that looks like this: ∀a. (P -> a) -> a. Is that equivalent to something of type P? Indeed it is, merely apply it to the identity function.

But what's the point? Why write a type like that? Does it mean anything in programming terms? Well, you can think of it as a function that already has something of type P somewhere, and needs you to give it a function that takes P as an argument, with the whole thing being polymorphic in the final result type. In a sense, it represents a suspended computation, waiting for the rest to be provided. In this sense, these suspended computations can be composed together, passed around, invoked, whatever. This should begin to sound familiar to fans of some languages, like Scheme or Ruby--because what it means is that double-negation corresponds to continuation-passing style, and in fact the type I gave above is exactly the continuation monad in Haskell.

While it's not a simple isomorphism, this discussion of constructive LEM is a very interesting result. In particular, in the conclusion section, Oleg Kiselyov discusses how the use of monads to get double-negation elimination in a constructive logic is analogous to distinguishing computationally decidable propositions (for which LEM is valid in a constructive setting) from all propositions. The notion that monads capture computational effects is an old one, but this instance of the Curry--Howard isomorphism helps put it in perspective and helps get at what double-negation really "means".

Your chart is not quite right; in many cases you have confused types with terms.

function type              implication
function                   proof of implication
function argument          proof of hypothesis
function result            proof of conclusion
function application RULE  modus ponens
recursion                  n/a [1]
structural induction       fold (foldr for lists)
mathematical induction     fold for naturals (data N = Z | S N)
identity function          proof of A -> A, for all A
non-terminating function   n/a [2]
tuple                      normal proof of conjunction
sum                        disjunction
n/a [3]                    first-order universal quantification
parametric polymorphism    second-order universal quantification
currying                   (A,B) -> C -||- A -> (B -> C), for all A,B,C
primitive type             axiom
types of typeable terms    theory
function composition       syllogism
substitution               cut rule
value                      normal proof

[1] The logic for a Turing-complete functional language is inconsistent. Recursion has no correspondence in consistent theories. In an inconsistent logic/unsound proof theory you could call it a rule which causes inconsistency/unsoundness.

[2] Again, this is a consequence of completeness. This would be a proof of an anti-theorem if the logic were consistent -- thus, it can't exist.

[3] Doesn't exist in functional languages, since they elide first-order logical features: all quantification and parametrization is done over formulae. If you had first-order features, there would be a kind other than *, * -> *, etc.; the kind of elements of the domain of discourse. For example, in Father(X,Y) :- Parent(X,Y), Male(X), X and Y range over the domain of discourse (call it Dom), and Male :: Dom -> *.

Since you explicitly asked for the most interesting and obscure ones:

You can extend C-H to many interesting logics and formulations of logics to obtain a really wide variety of correspondences. Here I've tried to focus on some of the more interesting ones rather than on the obscure, plus a couple of fundamental ones that haven't come up yet.

evaluation             | proof normalisation/cut-elimination
variable               | assumption
S K combinators        | axiomatic formulation of logic
pattern matching       | left-sequent rules
subtyping              | implicit entailment (not reflected in expressions)
intersection types     | implicit conjunction
union types            | implicit disjunction
open code              | temporal next
closed code            | necessity
effects                | possibility
reachable state        | possible world
monadic metalanguage   | lax logic
non-termination        | truth in an unobservable possible world
distributed programs   | modal logic S5/Hybrid logic
meta variables         | modal assumptions
explicit substitutions | contextual modal necessity
pi-calculus            | linear logic

EDIT: A reference I'd recommend to anyone interested in learning more about extensions of C-H:

"A Judgmental Reconstruction of Modal Logic" http://www.cs.cmu.edu/~fp/papers/mscs00.pdf - this is a great place to start because it starts from first principles and much of it is aimed to be accessible to non-logicians/language theorists. (I'm the second author though, so I'm biased.)

Related to the relationship between continuations and double negation, the type of call/cc is Peirce's law http://en.wikipedia.org/wiki/Call-with-current-continuation

C-H is usually stated as correspondence between intuitionistic logic and programs. However if we add the call-with-current-continuation (callCC) operator (whose type corresponds to Peirce's law), we get a correspondence between classical logic and programs with callCC.

First-class continuations support allows you to express $P \lor \neg P$. The trick is based on the fact that not calling the continuation and exiting with some expression is equivalent to calling the continuation with that same expression.

For more detailed view please see: http://www.cs.cmu.edu/~rwh/courses/logic/www-old/handouts/callcc.pdf

2-continuation           | Sheffer stoke
n-continuation language  | Existential graph
Recursion                | Mathematical Induction

One thing that is important, but have not yet being investigated is the relationship of 2-continuation (continuations that takes 2 parameters) and Sheffer stroke. In classic logic, Sheffer stroke can form a complete logic system by itself (plus some non-operator concepts). Which means the familiar and, or, not can be implemented using only the Sheffer stoke or nand.

This is an important fact of its programming type correspondence because it prompts that a single type combinator can be used to form all other types.

The type signature of a 2-continuation is (a,b) -> Void. By this implementation we can define 1-continuation (normal continuations) as (a,a) -> Void, product type as ((a,b)->Void,(a,b)->Void)->Void, sum type as ((a,a)->Void,(b,b)->Void)->Void. This gives us an impressive of its power of expressiveness.

If we dig further, we will find out that Piece's existential graph is equivalent to a language with the only data type is n-continuation, but I didn't see any existing languages is in this form. So inventing one could be interesting, I think.

Here's a slightly obscure one that I'm surprised wasn't brought up earlier: "classical" functional reactive programming corresponds to temporal logic.

Of course, unless you're a philosopher, mathematician or obsessive functional programmer, this probably brings up several more questions.

So, first off: what is functional reactive programming? It's a declarative way to work with time-varying values. This is useful for writing things like user interfaces because inputs from the user are values that vary over time. "Classical" FRP has two basic data types: events and behaviors.

Events represent values which only exist at discrete times. Keystrokes are a great example: you can think of the inputs from the keyboard as a character at a given time. Each keypress is then just a pair with the character of the key and the time it was pressed.

Behaviors are values that exist constantly but can be changing continuously. The mouse position is a great example: it is just a behavior of x, y coordinates. After all, the mouse always has a position and, conceptually, this position changes continually as you move the mouse. After all, moving the mouse is a single protracted action, not a bunch of discrete steps.

And what is temporal logic? Appropriately enough, it's a set of logical rules for dealing with propositions quantified over time. Essentially, it extends normal first-order logic with two quantifiers: □ and ◇. The first means "always": read □φ as "φ always holds". The second is "eventually": ◇φ means that "φ will eventually hold". This is a particular kind of modal logic. The following two laws relate the quantifiers:

□φ ⇔ ¬◇¬φ
◇φ ⇔ ¬□¬φ

So □ and ◇ are dual to each other in the same way as ∀ and ∃.

These two quantifiers correspond to the two types in FRP. In particular, □ corresponds to behaviors and ◇ corresponds to events. If we think about how these types are inhabited, this should make sense: a behavior is inhabited at every possible time, while an event only happens once.