Proofs Theorem 1

post by Diffractor · 2021-12-03T18:49:27.663Z · LW · GW · 0 comments

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Theorem 1: Any sequence of infrakernels  which fulfill the niceness conditions have the infinite semidirect product  being well-defined and fulfilling the niceness conditions.

As a recap, the niceness conditions are:

1: Lower-semicontinuity for inputs: For all continuous bounded ,   is a lower-semicontinuous function.

2: 1-Lipschitzness for functions: For all  is 1-Lipschitz.

3: Compact-shared compact-almost-support: For all compact sets  and , there is a compact set  which is an -almost-support for all the  inframeasures where .

4: Constants increase: For all  and constant functions .

5: 1-normalization (only for the  type signature): For all 

Now,  is defined as: Fixing an arbitrary sequence of compact sets ,

Our task is to show that  is a well-defined infrakernel which fulfills these five properties.

We will be reusing the proofs from "Less Basic Inframeasure Theory" (henceforth abbreviated as LBIT) when possible, and commenting on the differences when applicable.

The proof sketch is:

Part 1: Show that the functions you're feeding into those  infrakernels are guaranteed to be continuous.

Part 2: Show that all the  are infrakernels which fulfill the niceness conditions, via induction.

Part 3: Show that if a function only depends on the first n coordinates of the input, then the  values monotonically increase as m does.

Part 4: Give a general procedure for taking a compact subset of the space  and making a compact subset of the space  with nice properties related to compact almost-support, that preserves its nice properties when projected down to any finite stage.

Almost-Monotone Lemma: This is a sufficiently useful utility tool in other theorems to be broken out into its own result. It says you can take any  and  and compact set  and pick a sequence of compact sets  for the defining sequence of the infinite semidirect product such that the defining sequence for all the  (with ) is -almost-monotone.

Part 5: Use parts 2, 3, and 4 to show that for any two different  sequences, the defining sequences for the infinite infrakernel will limit to each each other (so if one converges, all do, if one diverges, all do, and if one wiggles around forever, all do), and then apply the Almost-Monotone Lemma to rule out the "wiggle around forever" case. Thus, the limit to define  exists, and doesn't depend on the choice of the sequence of compact sets. This solves well-definedness.

Part 6: Using parts 2 and 5, clean up the basic inframeasure conditions for  (monotonicity and concavity), and show 1-Lipschitzness, increase of constants, and 1-normalization for  while we're at it. That's 3/5 niceness conditions down, and all inframeasure conditions except for compact almost-support.

Part 7: Use our trick from Part 4 and our freedom of picking our compact set sequence from Part 5 to show the compact-shared compact-almost-support property for . This also means that individual outputs of the kernel fulfill CAS, which verifies the last condition we need to conclude that  is always an inframeasure. Only lower-semicontinuity of the kernel remains to be verified.

Part 8: We use the Almost-Monotone Lemma to wrap up the last condition, the lower-semicontinuity of the infinite infrakernel.

We often use the usual "start with thing we're trying to prove, and keep reducing it to a simpler problem" technique from the last time this proof path was used.

T1.1 Our desired result is whether the function 
is continuous. This was already shown in "Less Basic Inframeasure Theory" (LBIT).

T1.2 The desired result is "if all the  have the five niceness properties, then all the  are infrakernels with the five niceness properties as well".

The proof sketch for this is that this splits into 6 properties we need to show induct up. Monotonicity (phase 1), concavity (phase 2), 1-Lipschitzness (phase 3), increasing constants (phase 4), shared compact-almost-support (phase 5), and lower-semicontinuity (phase 6), which splits into two parts, one where we show a particular function is continuous, and then show lower-semicontinuity in general. Then, we finish up by arguing that this gets everything we need.

For the base case, because  and we're assuming all the  have the niceness properties and are infrakernels,  trivially fulfills them.

Time for the induction step. Remember that 

T1.2.1 Proof of monotonicity: Assume . Then

And the same goes for  so if we could prove


we'd be successful. Now, by monotonicity for  (by induction assumption), we'd have that result if


Letting  be arbitrary, by applying monotonicity for , we'd have that result if

Which is true since . And so we're done, montonicity inducts up.

T1.2.2 Proof of concavity:

and then, by concavity for all , and monotonicity for  (by induction assumption), we have


and then, by concavity for  (by induction assumption), we have


and then this packs up as

and concavity inducts on up.

T1.2.3 Proof of 1-Lipschitzness: we have


And by 1-Lipschitzness for  (by induction assumption), we have


And by 1-Lipschitzness for , we have

And 1-Lipschitzness inducts on up.

T1.2.4 Proof of increasing constants (and 1-normalization): We have

And then by increasing constants for , and monotonicity for  (induction assumption), we have

Now just apply increasing constants for  (induction assumption) to get 

For 1-normalization in the  type signature, we can have , and then instead of an inequality, we have an equality, and the same proof path works, just using 1-normalization instead of increasing constants. They both induct up.

T1.2.5 Proof of the compact-shared CAS property: Our task is to take an arbitrary compact set , and find a compact set  where two functions  identical on the set only differ in expectation by  according to all  with .

Let , and define the set  as 

where the first compact set is a shared -almost-support for the  where  (exists by compact-shared CAS for , an induction assumption) and the second compact set is a shared -almost-support for the  where  is in  (exists by compact-shared CAS for , an assumed niceness condition). Let  be continuous and identical on . Then, we have


Now, we apply Lemma 2 from LBIT, where we can upper-bound this quantity by "Lipschitz constant of the inframeasure times how much the functions differ on the almost-support + level of almost-support times how much the functions differ in general". We use  as our compact set for the inner function. It was defined as a -almost support for all  with , and  is 1-Lipschitz (induction assumption). So our upper bound is:




Focusing on that second chunk, we can apply 1-Lipschitzness of  to yield



For the first chunk, we can apply Lemma 2 from LBIT again, with  as our compact set, which is a -almost support for all  with , and  is 1-Lipschitz. So our upper bound is:



Now, since  and  are identical on  that first term just vanishes, yielding


We upper-bound this by


Which then clearly just reduces to

And we're done, the compact-shared CAS property inducts up.

T1.2.6.1 Proof of lower-semicontinuity: We'll start by taking an extended detour to show that the function 

is lower-semicontinuous. Fix a convergent sequence of inputs,  which limit to . First up, the set

is compact in  since it converges and we have the limit point added in. By the compact-shared CAS property for , we can take any  and make a compact set  which is a shared -almost-support for all the  inframeasures. For any m, we can then apply the Lemma 2 (from LBIT) decomposition with the  -almost-support for all the  inframeasures (and 1-Lipschitzness of ) to get the inequality


That second term can be upper-bounded by , so doing that, we have

Now, the set  is a compact set, so any continuous bounded function  is uniformly continuous on it. For all , there is some  where two points only  apart within this set have  only differing by  on them. Since  limits to , for sufficiently large m, those two points will be within  of each either, so eventually 

will be  or less for late enough m. So, for late enough m, we have 

Since  can be arbitrary, we have that the sequences 

and

limit to each other. Therefore,

And then, by lower-semicontinuity for , we have

and so, lower-semicontinuity of the function

is shown. Time to return to the usual induction proof.

T1.2.6.2 For lower-semicontinuity in inputs, we first unpack the semidirect product. Fix a sequence  which limits to .

Since we showed that the function 

is lower-semicontinuous, we can apply the monotone convergence theorem for inframeasures and rewrite as

For any individual , call it , we have

We now run through the same proof path as earlier again. The set  is compact in  since it converges and we have the limit point added in. By the compact-shared CAS property for  (induction assumption), we can take any  and make a compact set  which is a shared -almost-support for all the  inframeasures. For any m, we can then apply the Lemma 2 (from LBIT) decomposition with the  -almost-support for all the  inframeasures (and 1-Lipschitzness of  by induction assumption) to get the inequality


That second term can be upper-bounded by , so doing that, we have

Now, the set  is a compact set, so any continuous bounded function f is uniformly continuous on it. For all , there is some  where two points only  apart within this set have  only differing by  on them. Since  limits to , for sufficiently large m, those two points will be within  of each either, so eventually 

will be  or less for late enough m. So, for late enough m, we have 

Since  can be arbitrary, we have that the sequences 

and

limit to each other. Taking a break to recap, we had

and for any  fulfilling those bounding conditions for the sup, we have

and from our fresh new result, we then have

and, by lower-semicontinuity for  (induction assumption), we have

Since  was arbitrary below 

this means that

Now, we can put our lower-semicontinuous upper bound back in to get

and we're done, induction applies for lower-semicontinuity.

All our induction steps have been shown. First, for showing that all the  are inframeasures, we have monotonicity and concavity. Lipschitzness is taken care of by our 1-Lipschitzness induction. Compact almost support is taken care of by our compact-shared CAS induction for the , because a single point is compact. And weak normalization (0 must map to 0 or more) is taken care of by our Constants Increase induction. So all the  are inframeasures.

For the 5 niceness conditions, we proved all of lower-semicontinuity, 1-Lipschitzness, compact-shared CAS, increasing constants, and 1-normalization by induction. So we can now assume that all  are nice.

T1.3 We must show that if we go far enough out in the , the value assigned to functions which only depend on finitely many inputs starts monotonically increasing. The result that we'd like to show at this point is:

Fix an arbitrary  and . Then, we can just go:

Since , that function at the end is a constant (doesn't depend on its input), so by Increasing Constants for  and Monotonicity for , we have

and we're done.

T1.4 Our desired result here is:



This says that if you pick any compact subset of , you can make a compact subset of  where the projection of it to coordinates 1 through  acts as a compact -almost-support for all the  infradistributions when  lies in your compact set .

The proof of this is word-for-word identical to the proof of this from LBIT, nothing changes. To recap the construction, fix some  and . Now, we recursively build up compact subsets of all the  via the following inductive process.

 is an arbitrary compact shared -almost-support for  where  is in  , these sets exist by compact-shared CAS for all the .

We define the abbreviations

and

This is the product of all the compact sets, and is compact. Notice the dependence of these on the starting compact set and . Notice that the projection of  to coordinates 1 through n is exactly .

Almost-Monotone Lemma: If  is a sequence of infrakernels fulfilling the niceness conditions, then



This says that for any compact subset of  and  you name, I can find a "good" sequence of compact sets where the defining sequence for all the  quantities is "almost monotone". Every time the sequence hits a certain value (at time n), it will never again be able to dip below  of that value as the sequence progresses. This proof progresses in 5 phases. The first phase is just doing some rewrites of our proof goal, the second, third, and fourth are showing setup results on functions undershooting other functions, and certain pairs of quantities being similar. The last phase is wrapping up the actual result.

L1.1 So, for the rewrites, let  be an arbitrary compact subset of , and  be arbitrary. Our proof goal is now



Let your sequence of compact sets be the  sequence recursively defined from  and . Then our proof goal becomes



Let , and  be arbitrary. Remember  is in . Then our proof goal becomes


First, let's define some abbreviations for later. The function

will be abbreviated as , and the function

will be abbreviated as . Both of these functions are continuous, by section 1. We'll need three key results before beginning. 

L1.2 Our first desired result is:

Unpacking this proof target, it is


If , this result is trivial, we have equality. So now we'll assume . Observe that it is now possible to factorize  as , therefore,

turns into

which is just

Packing up  on the left side of our proof target, our proof target is now


And then, since we can factorize  as , our proof target is now


Which is obviously true. So, we have our first result of

L1.3 Time for our second desired result. Our second desired result is that

For this, since  on the set , as we showed in our first desired result,  equals  on the set .

Further,  is an -almost-support for all the  with , as our  is. So, in particular, it's an -almost-support. Accordingly, we have

Now, for any input, either  is higher (and so the distance between the functions at that point is 0), or  is higher, and so the distance between the functions at that point is upper-bounded by . So, we have

At this point, we recall that both  and  were just , but taking worst-case inputs past a certain point, so a trivial bound on this quantity is . So, our net result is

L1.4 And it's time to move onto our third setup result. Our desired third setup result is that

For this, since  on the set , as we showed in our first desired result,  equals  on the set .

Further,  is an -almost-support for all the  with , as our  is. So, in particular, it's an -almost-support. Accordingly, we have

Now, for any input, either  is lower (and so the distance between the functions at that point is 0), or  is lower, and so the distance between the functions at that point is upper-bounded by . So, we have

At this point, we recall that both  and  were just , but taking worst-case inputs past a certain point, so a trivial bound on this quantity is . So, our net result is

Now that everything's in place, we can start working on our actual result.

L1.5 Remember, our overall proof target at this stage is


We can reshuffle this proof target a little to get the equivalent statement


So let's get cracking on that inequality.

First, we abbreviate it as

Then, we apply our second sublemma we proved to get

And undo the absolute value to get

and cancel out to get

and then, by monotonicity we have

and apply our third sublemma we proved to get

And undo the absolute value

And cancel

and at this point, we can unpack the inner function to get

And then, we apply our Part 3 result that for functions which only depend on finitely many inputs,  is monotonically increasing, to get

and we're done with the Almost-Monotone Lemma!

T1.5 Our aim here is to show that no matter what sequence of compact sets you have, they all limit to the same result. In order to do this, we'll have to show the result (letting  being your first sequence of nonempty compact sets to attempt to define the limit and  being your second sequence of nonempty compact sets, and abbreviating  as the product of the  from  to ) that,



In words, this is saying that for any two sequences of compact sets, there exists some threshold where if you pick any value of the defining sequence for  associated with using  as your compact sets, and the sequence associated with using  as your compact sets (as long as they're both past some shared threshold), they'll be close. So all choices of compact set must limit to each other, because  can be arbitrary.

Fix our  (input value, closeness parameter, two sequences of compact sets, function), and now we'll find our n to make


true. Do it in the following way. Use  as your compact seed set to invoke the technique in part 4 to construct your sequence , and then consider the set:

A finite union of compact sets is compact, and the product of compact sets is compact. If we restrict  to this set, it's uniformly continuous. In particular, using the standard product metric (which metrizes the product topology), defined as:

We can conclude that two sequences which agree up till time n must be, at most, distance  apart. Since  restricted to our compact set of interest is uniformly continuous, there is some  difference in inputs that only leads to an  difference in values. Now we can define our n as .

Now that we've picked our n, let m be arbitrary. Our goal is to now prove:


First-up, we use that  is an -almost support for , and 1-Lipschitzness, to apply Lemma 2 from LBIT to break up


as




We can upper-bound the second term with just , as the difference in values can't be any higher than the gap between the maximum value of  and the minimum value of . As for the first term, note that if  and  and (the latter two are the inf terms for a particular ) then we have

And same for . And these two points agree on , and n is large enough that the function itself varies by only  for any two points in that set which share the same prefix up to length n (and  fulfills that) So, we can break down the upper bound as

And so we're done here and have our result.

Moving on, the statement



is the same as



So all the defining sequences for  limit to each other. We've got three possible cases. One is divergence, that liminf of the defining sequences goes to infinity. This is fine, the limit exists. One is convergence, that liminf and limsup are finite and equal, ie, the limit exists. This is fine. And the third case, that liminf and limsup aren't equal, must be ruled out. We'll invoke the Almost-Monotone Lemma, that



Specializing to the compact set consisting of a single arbitrary point , and recalling that the defining sequence for that was the  sequence of almost-supports, and an arbitrary function , the lemma turns into



Fix an arbitrary  and  now. Just by definitions, we have

This sequence is monotonically increasing, so a lower bound on this is

and then, using  and  in the Almost-Monotone Lemma, we have

Since  was an arbitrary number, we have

and then we can lower-bound this by the limsup, yielding

Since the limsup is always equal or greater than the liminf, this implies that the limsup and liminf can be at most  apart for this sequence. And since all the defining sequences limit to each other, they all have the same limsup and liminf. Since  was arbitrary, we get that all the defining sequences limit to each other, and either converge to a fixed number, or diverge to infinity. The infinite semidirect product is now well-defined, and we can use whichever sequence of compact sets is the most convenient.

T1.6 Showing the following infradistribution properties for the infinite semidirect product: monotonicity and concavity. Also, the 1-Lipschitz property and 1-normalization property and Constants Increase property, for 4/5 inframeasure properties, and 3/5 niceness properties.

For monotonicity, concavity, and 1-Lipschitzness, the exact proof from LBIT works.

For constants increasing, observe that regardless of n,

Then, this bound transfers to the limit, so

The same proof applies to 1-normalization, but with equality signs, if we plug in 1, and the limit of the all-1 sequence is always 1.

T1.7 Showing compact-shared compact-almost-support for . Again, the exact proof from LBIT works here. We're up to 5/5 inframeasure properties,  and 4/5 niceness properties for the infinite semidirect product.

T1.8 Our task is to show lower-semicontinuity for . This will take some cunning. At the start, fix an , we'll see why later. Our task is to show that

For some arbitrary sequence of  which limits to . What we can do is first unpack.

Now, the sequence of sets we picked was important. It means we can now apply the Almost-Monotone Lemma. Regardless of m, the defining sequence for  is almost monotone now. We can fix a particular  (arbitrary) to get a lower bound of

And then, by lower-semicontinuity for , which was already established by induction, we get

But, since this holds for all , we can take a limit and get

But since  can be arbitrarily small, we have

and thus, lower-semicontinuity. And we're finally done!!

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