Proving Set Convergence with Random Procedure

In summary, the procedure of allocating n items to single-item bins and randomly moving items from the same set to the same bin will almost surely converge to a fixed number of non-empty bins, either 1 or 2, depending on whether A and B are disjoint or intersect. This is because the number of non-empty bins can only decrease and eventually reach a stable state.
  • #1
JimmyT
2
0
Suppose there are n items which are belong to two sets, A and B, such that A intersects B yields a non-empty set C. I apply the following procedure:

-------------------------------------------------
Allocate each of the n items to a single item bin (so there will be n single-item bins).
Repeat the following two steps many times:
(1) From the n items, randomly select two separate items i and j
(2) If items i and j are from the same set, move i to j's bin.
-------------------------------------------------

Questions: Will this procedure always converge to a fixed number of non-empty bins?
If yes, can you provide some clues how I can prove this?

Here are some of my thoughts (pls correct me if I am wrong):

The answer is obvious when A and B are disjoint --- there are two non-empty bins left after many iterations.

I find it a bit tricky if A intersects B yields a non-empty set C, then we may end up with one non-empty bin (especially when |C| is a lot larger than |A| and |B|), or we may end up with two non-empty bins (especially when |C| is a lot smaller than |A| and |B|). In any case, I am just interested to show that the procedure will (almost surely) converge to some constant number of non-empty bins, after many iterations.

Any help will be appreciated.

Thanks!
 
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  • #2
-------------------------------------------------
Allocate each of the n items to a single item bin (so there will be n single-item bins).
Repeat the following two steps many times:
(1) From the n items, randomly select two separate items i and j
(2) If items i and j are from the same set, move i to j's bin.
-------------------------------------------------
I assume from context that "j's bin" does not mean the bin j started in, but the bin j is in now. According to this interpretation, a bin once empty can never become nonempty. Therefore the number of nonempty bins is nonincreasing, but greater than 0, so it has to converge to some value. As you said, if A and B are disjoint, that value will be 2. If they intersect, that value will be 1. With a certain nonzero probability an element c of C can "pull" all the elements of A and B to the same bin that c is in, and once it has finished doing that, there will be only 1 bin left and no more changes.
 
  • #3
Thanks heaps. I am clearer now.
 

Related to Proving Set Convergence with Random Procedure

1. What is the definition of "proving set convergence"?

Proving set convergence refers to the process of determining whether a given sequence of sets will eventually settle on a single set, known as the limit set, as the sequence progresses. This is often done using mathematical proofs and various techniques, such as the random procedure method.

2. What is the random procedure method?

The random procedure method is a mathematical technique used to prove set convergence. It involves randomly selecting elements from a given sequence of sets and observing whether these elements eventually settle on the same set, indicating convergence.

3. How does the random procedure method work?

The random procedure method involves randomly selecting elements from the given sequence of sets and checking to see if these elements eventually settle on the same set. If they do, this provides evidence for set convergence. This process is repeated multiple times to increase the confidence in the result.

4. What are the advantages of using the random procedure method?

The random procedure method is a relatively simple and efficient way to prove set convergence. It also does not require extensive mathematical knowledge or complex calculations, making it accessible to a wide range of researchers and scientists.

5. Are there any limitations to the random procedure method?

While the random procedure method can be a useful tool for proving set convergence, it is not foolproof. There is always a possibility of error or misinterpretation of the results. Additionally, this method may not work for all types of sets and may not provide definitive proof of convergence in every case.

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